MD_in_Colab(ENG).ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/kimjc95/computational-chemistry/blob/main/MD_in_Colab(ENG).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "80CnOAJSxXyW"
      },
      "source": [
        "# MD in Colab"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tYJdP4FzFPCx"
      },
      "source": [
        "2024-08-21 by Joo-Chan Kim at [MSBL](https://msbl.kaist.ac.kr), KAIST\n",
        "\n",
        "YouTube Tutorial :\n",
        "\n",
        "* [protein-ligand MD](https://www.youtube.com/watch?v=3ZbKCC_DS-A)\n",
        "\n",
        "-------------------------------------\n",
        "\n",
        "This is a Google Colaboratory Notebook for the all-atom molecular dynamics simulation of proteins (and nucleic acids) with ligands / non-standard residues. (BSD-3 license)\n",
        "\n",
        "Please cite DOI:[10.5281/zenodo.13133762](https://doi.org/10.5281/zenodo.13685874) if you have used my code in your research.\n",
        "\n",
        "If you have any problems, please raise an issue in [GitHub](https://github.com/kimjc95/computational-chemistry/issues) or email me (kimjoochan@kaist.ac.kr).\n",
        "\n",
        "-------------------------------------\n",
        "\n",
        "**Things to Prepare :**\n",
        "\n",
        "1. Your system's PDB file or PDB ID\n",
        "\n",
        "2. (optional) SDF files for your custom residues\n",
        "\n",
        "3. Google account (for saving jobs in Google Drive), Internet connection (or additional Google Colab computing resources)\n",
        "\n",
        "-------------------------------------\n",
        "\n",
        "**with this notebook you CAN perform:**\n",
        "1. All-atom implicit/explicit solvent MD simulation of protein/nucleic acids/small molecules with canonical/non-canonical residues\n",
        "\n",
        "2. Post-run analyses including: clustering, RMSD, RMSF, RoG, FEL, H-bonds, SASA, DSSP, DCCM, PCA, and MM/GBSA\n",
        "\n",
        "**with this notbook you CANNOT perform:**\n",
        "1. MD simulation of systems with non-aqueous solvents or lipid bilayers\n",
        "\n",
        "2. Advanced MD options like steered MD, replica exchange sampling, simulated tempering, metadynamics, etc.\n",
        "\n",
        "3. Accurate binding energy calculation using MM/PBSA, 3D-RISM, umbrella sampling, alchemical transformation, etc.\n",
        "\n",
        "4. Binding energy calculation of ligands with ML- or XTB-forcefields\n",
        "\n",
        "----------------------------------------\n",
        "\n",
        "To start simulating, open each tabs to view cells and run each cell one at a time."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JnMbY1wFxzQF"
      },
      "source": [
        "## 0. Connect to Google Drive & Set working environment"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "HFtWxPd_mVmC"
      },
      "outputs": [],
      "source": [
        "gpu_info = !nvidia-smi\n",
        "gpu_info = '\\n'.join(gpu_info)\n",
        "assert gpu_info.find('command not found') <0, \"Please change to GPU runtime!\"\n",
        "\n",
        "#@markdown Runtime will be restarted shortly. Please wait.\n",
        "\n",
        "!pip install -q condacolab\n",
        "import condacolab\n",
        "condacolab.install()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "Uh2F1zMkUnFz"
      },
      "outputs": [],
      "source": [
        "#@markdown (Takes about 3 minutes) <br/>\n",
        "#@markdown Enter the name of the working directory within your Google Drive. <br/>\n",
        "#@markdown Do not include brakets or special characters in the name!\n",
        "\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n",
        "working_directory = \"UNEL-PI4P\" #@param {type:\"string\"}\n",
        "\n",
        "#@markdown Please authorize the Colab to get access to your Google Drive. MD Trajectory files are large, and Colab sessions are notorious for their instabilty.\n",
        "\n",
        "import subprocess\n",
        "\n",
        "print('Installing all required python packages...', end='')\n",
        "subprocess.run(['mamba', 'install', '-c', 'pytorch', '-c', 'nvidia', '-c', 'conda-forge',\n",
        "                'pytorch', 'pytorch-cuda=12.1', 'openmm=8', 'openmm-torch', 'openmm-ml',\n",
        "                'openmm-xtb', 'nnpops', 'espaloma', 'openmmforcefields', 'scikit-learn',\n",
        "                'scipy', 'ipywidgets=7', 'nglview', 'parmed', 'rdkit', 'pdbfixer', 'openbabel',\n",
        "                'plotly', 'mdtraj', 'lxml', '--yes'])\n",
        "subprocess.run(['pip', 'install', 'mace-torch', 'pytest-asyncio==0.21.0'])\n",
        "subprocess.run(['apt-get', 'install', 'python3-openbabel'])\n",
        "subprocess.run(['pip', 'install', '--no-deps', 'plip'])\n",
        "print('done.')\n",
        "\n",
        "from pdbfixer import PDBFixer\n",
        "from openmm import *\n",
        "from openmm.app import *\n",
        "from openmm.unit import *\n",
        "from openmmxtb import XtbForce\n",
        "from openmmml import MLPotential\n",
        "from openff.toolkit import Molecule\n",
        "from openmmforcefields.generators import GAFFTemplateGenerator\n",
        "from openmmforcefields.generators import SMIRNOFFTemplateGenerator\n",
        "from openmmforcefields.generators import EspalomaTemplateGenerator\n",
        "from openmm.app.internal import customgbforces\n",
        "from rdkit import Chem\n",
        "from rdkit.Chem import AllChem\n",
        "import io\n",
        "import os\n",
        "import locale\n",
        "import sys\n",
        "import glob\n",
        "import copy\n",
        "import warnings\n",
        "import threading\n",
        "import numpy as np\n",
        "import parmed as pmd\n",
        "import nglview as nv\n",
        "from time import sleep\n",
        "from tqdm.notebook import tqdm\n",
        "from IPython.display import display, clear_output\n",
        "import mdtraj as md\n",
        "from sklearn.cluster import AgglomerativeClustering\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.neighbors import KernelDensity\n",
        "from sklearn.model_selection import GridSearchCV\n",
        "from collections import Counter\n",
        "import openbabel\n",
        "from plip.structure.preparation import PDBComplex\n",
        "from plip.exchange.report import BindingSiteReport\n",
        "from scipy.spatial.transform import Rotation\n",
        "from sklearn.covariance import EmpiricalCovariance\n",
        "from collections import Counter\n",
        "import ipywidgets as widgets\n",
        "import plotly.graph_objects as go\n",
        "from plotly.subplots import make_subplots\n",
        "import plotly.io as pio\n",
        "pio.renderers.default = 'colab'\n",
        "from google.colab import output, files\n",
        "output.enable_custom_widget_manager()\n",
        "import torch\n",
        "torch._C._jit_set_nvfuser_enabled(False)\n",
        "\n",
        "\n",
        "def navigator(working_directory)->str:\n",
        "    work = \"/content/drive/MyDrive/\"+working_directory\n",
        "\n",
        "    if not os.path.isdir(work):\n",
        "        print(f'No directory named {working_directory} in your Google Drive.')\n",
        "        os.mkdir(work)\n",
        "        print(f'Created a new directory named {working_directory} in your Google Drive.')\n",
        "        print('You may now proceed to the cell# 1-1.')\n",
        "\n",
        "    elif os.path.exists(work+'/production_final.xtc'):\n",
        "        print(f'There is a finished MD simulation in the directory {working_directory}.')\n",
        "        print('You can extend your production run at cell# 3-3 if you want.')\n",
        "        print('To continue analysis, go to cell# 4-1.')\n",
        "        print('To calculate binding free energy, go to cell# 5-1.')\n",
        "\n",
        "    elif os.path.exists(work+'/production_0.xtc'):\n",
        "        print('Seems like you were performing production run.')\n",
        "        print('Go to cell# 3-3.')\n",
        "\n",
        "    elif os.path.exists(work+'/npt_0.xtc'):\n",
        "        print('Seems like you were performing NPT equilibration.')\n",
        "        print('Go to cell# 3-2.')\n",
        "\n",
        "    elif os.path.exists(work+'/nvt_0.xtc'):\n",
        "        print('Seems like you were performing NVT equilibration.')\n",
        "        print('Go to cell# 3-1.')\n",
        "\n",
        "    elif os.path.exists(work+'/start.xml'):\n",
        "        print('You have created your simulation object, but never started it.')\n",
        "        print('Go to cell# 3-1.')\n",
        "\n",
        "    elif os.path.exists(work+'/starting_structure.pdb'):\n",
        "        print('You have prepared the starting structure, but did not create the simulation object.')\n",
        "        print('Go to cell# 2-1.')\n",
        "\n",
        "    else:\n",
        "        print(f'There is a directory named {working_directory} in you Google Drive, but it is empty.')\n",
        "        print('Proceed to cell# 1-1.')\n",
        "\n",
        "    work += '/'\n",
        "    return work\n",
        "\n",
        "\n",
        "def read_settings(work:str)->dict:\n",
        "    \"\"\"\n",
        "    Read the parameters from the settings.txt file.\n",
        "    \"\"\"\n",
        "    if not os.path.exists(work+'settings.txt'):\n",
        "        return None\n",
        "\n",
        "    with open(work+'settings.txt', 'r') as f:\n",
        "        settings = {}\n",
        "        for line in f.readlines():\n",
        "            if line.strip().startswith('Forcefield'):\n",
        "                settings['forcefield'] = line.split(\":\")[1].strip()\n",
        "            elif line.strip().startswith('Watermodel'):\n",
        "                settings['watermodel'] = line.split(\":\")[1].strip()\n",
        "            elif line.strip().startswith('Constraints'):\n",
        "                settings['constraints'] = line.split(\":\")[1].strip()\n",
        "            elif line.strip().startswith('Rigidwater'):\n",
        "                settings['rigidwater'] = bool(line.split(\":\")[1].strip())\n",
        "            elif line.strip().startswith('Hydrogen mass'):\n",
        "                settings['hydrogen mass'] = float(line.split(\":\")[1].strip())*amu\n",
        "            elif line.strip().startswith('Precision'):\n",
        "                settings['precision'] = line.split(\":\")[1].strip()\n",
        "            elif line.strip().startswith('Temperature'):\n",
        "                settings['temperature'] = (float(line.split(\":\")[1].strip())+273.15)*kelvin\n",
        "            elif line.strip().startswith('Pressure'):\n",
        "                settings['pressure'] = float(line.split(\":\")[1].strip())*bar\n",
        "            elif line.strip().startswith('Time step'):\n",
        "                settings['stepsize'] = float(line.split(\":\")[1].strip())*femtosecond\n",
        "            elif line.strip().startswith('Ionic strength'):\n",
        "                settings['ionic strength'] = float(line.split(\":\")[1].strip())*molar\n",
        "            elif line.strip().startswith('Periodic Boundary Condition'):\n",
        "                settings['PBC'] = True if line.split(\":\")[1].strip()==\"True\" else False\n",
        "            elif line.strip().startswith('Padding'):\n",
        "                settings['padding'] = float(line.split(\":\")[1].strip())*nanometer\n",
        "            elif line.strip().startswith('Cation'):\n",
        "                settings['cation'] = line.split(\":\")[1].strip()\n",
        "            elif line.strip().startswith('Anion'):\n",
        "                settings['anion'] = line.split(\":\")[1].strip()\n",
        "            elif line.strip().startswith('Save interval'):\n",
        "                settings['save interval'] = int(line.split(\":\")[1].strip())*picosecond\n",
        "            elif line.strip().startswith('Restraint'):\n",
        "                settings['restraint'] = int(line.split(\":\")[1].strip())\n",
        "\n",
        "    return settings\n",
        "\n",
        "\n",
        "def read_non_standard_residues_list(work)->list:\n",
        "    \"\"\"\n",
        "    Read the nonstandard residue list from the non_standard_residues.txt file.\n",
        "    \"\"\"\n",
        "    if not os.path.exists(work+'non_standard_residues.txt'):\n",
        "        return []\n",
        "\n",
        "    with open(work+'non_standard_residues.txt', 'r') as f:\n",
        "        nsres = []\n",
        "        for line in f.readlines():\n",
        "            if not line.startswith('#'):\n",
        "                data = line.strip().split( )\n",
        "                if len(data) > 1:\n",
        "                    if data[1] == 'ligand':\n",
        "                        lig = True\n",
        "                    elif data[1] == 'residue':\n",
        "                        lig = False\n",
        "                    nsres.append({'name':data[0], 'lig':lig, 'ff':data[2]})\n",
        "                else:\n",
        "                    nsres.append({'name':data[0]})\n",
        "    return nsres\n",
        "\n",
        "def determine_forcefield(forcefield, watermodel)->tuple:\n",
        "    \"\"\"\n",
        "    Assign the macromolecular forcefield & water model from the choice.\n",
        "    \"\"\"\n",
        "    if forcefield == \"Amber14\":\n",
        "        ff = ForceField('amber14-all.xml')\n",
        "        if watermodel == \"(explicit) TIP3P\":\n",
        "            ff.loadFile('amber14/tip3p.xml')\n",
        "            water = 'tip3p'\n",
        "        elif watermodel == \"(explicit) SPC/E\":\n",
        "            ff.loadFile('amber14/spce.xml')\n",
        "            water = 'spce'\n",
        "        elif watermodel == \"(explicit) TIP4P-Ew\":\n",
        "            ff.loadFile('amber14/tip4pew.xml')\n",
        "            water = 'tip4pew'\n",
        "        elif watermodel == \"(explicit) TIP5P\":\n",
        "            print(\"ERROR : AMBER forcefield does not support TIP5P water model!\")\n",
        "            print(\"Please choose other options.\")\n",
        "            return None, \"\"\n",
        "        elif watermodel == \"(explicit) OPC\":\n",
        "            ff.loadFile('amber14/opc.xml')\n",
        "            water = 'tip4pew'\n",
        "        elif watermodel == \"(explicit) OPC3\":\n",
        "            ff.loadFile('amber14/opc3.xml')\n",
        "            water = 'tip3p'\n",
        "        elif watermodel == \"(implicit) HCT (igb=1)\":\n",
        "            ff.loadFile('amber14/tip3p.xml')\n",
        "            ff.loadFile('implicit/hct.xml')\n",
        "            water = \"\"\n",
        "        elif watermodel == \"(implicit) OBC1 (igb=2)\":\n",
        "            ff.loadFile('amber14/tip3p.xml')\n",
        "            ff.loadFile('implicit/obc1.xml')\n",
        "            water = \"\"\n",
        "        elif watermodel == \"(implicit) OBC2 (igb=5)\":\n",
        "            ff.loadFile('amber14/tip3p.xml')\n",
        "            ff.loadFile('implicit/obc2.xml')\n",
        "            water = \"\"\n",
        "        elif watermodel == \"(implicit) GBn (igb=7)\":\n",
        "            ff.loadFile('amber14/tip3p.xml')\n",
        "            ff.loadFile('implicit/gbn.xml')\n",
        "            water = \"\"\n",
        "        elif watermodel == \"(implicit) GBn2 (igb=8)\":\n",
        "            ff.loadFile('amber14/tip3p.xml')\n",
        "            ff.loadFile('implicit/gbn2.xml')\n",
        "            water = \"\"\n",
        "        else:\n",
        "            print('Error in reading AMBER forcefield parameters.')\n",
        "            return None, \"\"\n",
        "\n",
        "    elif forcefield == \"CHARMM36\":\n",
        "        if watermodel == \"(explicit) TIP3P\":\n",
        "            ff = ForceField('charmm36.xml', 'charmm36/water.xml')\n",
        "            water = 'tip3p'\n",
        "        elif watermodel == \"(explicit) SPC/E\":\n",
        "            ff = ForceField('charmm36.xml', 'charmm36/spce.xml')\n",
        "            water = 'spce'\n",
        "        elif watermodel == \"(explicit) TIP4P-Ew\":\n",
        "            ff = ForceField('charmm36.xml', 'charmm36/tip4pew.xml')\n",
        "            water = 'tip4pew'\n",
        "        elif watermodel == \"(explicit) TIP5P\":\n",
        "            ff = ForceField('charmm36.xml', 'charmm36/tip5p.xml')\n",
        "            water = 'tip5p'\n",
        "        elif watermodel == \"(explicit) OPC\":\n",
        "            print(\"ERROR : CHARMM forcefield does not support OPC water models!\")\n",
        "            print(\"Please choose other options.\")\n",
        "            return None, \"\"\n",
        "        elif watermodel == \"(explicit) OPC3\":\n",
        "            print(\"ERROR : CHARMM forcefield does not support OPC water models!\")\n",
        "            print(\"Please choose other options.\")\n",
        "            return None, \"\"\n",
        "        elif watermodel == \"(implicit) HCT (igb=1)\":\n",
        "            ff = ForceField('charmm36.xml', 'charmm36/water.xml', 'implicit/hct.xml')\n",
        "            water = ''\n",
        "        elif watermodel == \"(implicit) OBC1 (igb=2)\":\n",
        "            ff = ForceField('charmm36.xml', 'charmm36/water.xml', 'implicit/obc1.xml')\n",
        "            water = ''\n",
        "        elif watermodel == \"(implicit) OBC2 (igb=5)\":\n",
        "            ff = ForceField('charmm36.xml', 'charmm36/water.xml', 'implicit/obc2.xml')\n",
        "            water = ''\n",
        "        elif watermodel == \"(implicit) GBn (igb=7)\":\n",
        "            ff = ForceField('charmm36.xml', 'charmm36/water.xml', 'implicit/gbn.xml')\n",
        "            water = ''\n",
        "        elif watermodel == \"(implicit) GBn2 (igb=8)\":\n",
        "            ff = ForceField('charmm36.xml', 'charmm36/water.xml', 'implicit/gbn2.xml')\n",
        "            water = ''\n",
        "        else:\n",
        "            print(\"Error in reading the CHARMM forcefield parameters\")\n",
        "            return None, \"\"\n",
        "\n",
        "    else:\n",
        "        return \"\", \"\"\n",
        "\n",
        "    return ff, water\n",
        "\n",
        "\n",
        "class SimulationStream(io.StringIO):\n",
        "    \"\"\"\n",
        "    StringIO's child class to capture stdout simulation output.\n",
        "    \"\"\"\n",
        "    def __init__(self):\n",
        "        super().__init__()\n",
        "        self.string = \"\"\n",
        "\n",
        "    def write(self, string):\n",
        "        self.string += string\n",
        "\n",
        "    def read(self, size=-1)->str:\n",
        "        if size < 0:\n",
        "            result = self.string\n",
        "            self.string = \"\"\n",
        "        else:\n",
        "            result = self.string[:size]\n",
        "            self.string = self.string[size:]\n",
        "        return result\n",
        "\n",
        "\n",
        "def apply_restraints(work, simulation, restraint):\n",
        "    \"\"\"\n",
        "    Apply a harmonic positional restraint potential to the heavy atoms.\n",
        "    \"\"\"\n",
        "    if restraint > 0:\n",
        "        posres = CustomExternalForce(\"k*periodicdistance(x, y, z, x0, y0, z0)^2\")\n",
        "        posres.addGlobalParameter(\"k\", restraint)\n",
        "        posres.addPerParticleParameter(\"x0\")\n",
        "        posres.addPerParticleParameter(\"y0\")\n",
        "        posres.addPerParticleParameter(\"z0\")\n",
        "\n",
        "        pdb = PDBFile(work+'minimized.pdb')\n",
        "        heavy = []\n",
        "        for i, a in enumerate(pdb.topology.atoms()):\n",
        "            if a.element.symbol != 'H':\n",
        "                heavy.append(i)\n",
        "\n",
        "        positions = simulation.context.getState(getPositions=True).getPositions(asNumpy=True)\n",
        "        for i in range(np.shape(positions)[0]):\n",
        "            if i in heavy:\n",
        "                posres.addParticle(i, positions[i])\n",
        "        simulation.system.addForce(posres)\n",
        "    return simulation\n",
        "\n",
        "\n",
        "\n",
        "def restore_simulation_from_state(work, stage):\n",
        "    \"\"\"\n",
        "    Restore a simulation object from a state file.\n",
        "    \"\"\"\n",
        "    s = read_settings(work)\n",
        "    pdb = PDBFile(work+'minimized.pdb')\n",
        "    system = XmlSerializer.deserialize(open(work+'system.xml').read())\n",
        "    integrator = XmlSerializer.deserialize(open(work+'integrator.xml').read())\n",
        "    platform = Platform.getPlatformByName('CUDA')\n",
        "    properties = {'Precision': s['precision']}\n",
        "    simulation = Simulation(pdb.topology, system, integrator, platform, properties)\n",
        "    statename = work+stage+'.xml'\n",
        "    simulation.context.setState(XmlSerializer.deserialize(open(statename).read()))\n",
        "    change_flag = False # When the context is changed, reinitialize it\n",
        "    if stage in ['npt', 'production'] and s['PBC']:\n",
        "        barostat = MonteCarloBarostat(s['pressure'], s['temperature'])\n",
        "        simulation.system.addForce(barostat)\n",
        "        change_flag = True\n",
        "    if stage != 'production' and stage != 'start':\n",
        "        simulation = apply_restraints(work, simulation, s['restraint'])\n",
        "        change_flag = True\n",
        "    if change_flag:\n",
        "        simulation.context.reinitialize(preserveState=True)\n",
        "\n",
        "    return simulation\n",
        "\n",
        "\n",
        "def recall_simulation(work):\n",
        "    \"\"\"\n",
        "    Recall a simulation object from the working directory.\n",
        "    \"\"\"\n",
        "    if os.path.exists(work+'production.xml'):\n",
        "        stage = \"production\"\n",
        "        print('Resuming production run...', end='')\n",
        "        simulation = restore_simulation_from_state(work, 'production')\n",
        "\n",
        "    elif os.path.exists(work+'npt.xml'):\n",
        "        stage = \"npt\"\n",
        "        print('Resuming NPT equilibration...', end='')\n",
        "        simulation = restore_simulation_from_state(work, 'npt')\n",
        "\n",
        "    elif os.path.exists(work+'nvt.xml'):\n",
        "        stage = \"nvt\"\n",
        "        print('Resuming NVT equilibration...', end='')\n",
        "        simulation = restore_simulation_from_state(work, 'nvt')\n",
        "\n",
        "    elif os.path.exists(work+'start.xml'):\n",
        "        stage = \"start\"\n",
        "        print('Starting the simulation...', end='')\n",
        "        simulation = restore_simulation_from_state(work, 'start')\n",
        "\n",
        "    else:\n",
        "        print('Error in reading the simulation object.')\n",
        "        return None, \"\"\n",
        "\n",
        "    print('done.')\n",
        "    return simulation, stage\n",
        "\n",
        "\n",
        "def run_simulation(work, stage, simulation, stream, stepsize, temperature, length, save_period, backup_period):\n",
        "    \"\"\"\n",
        "    Run the simulation object for length picoseconds.\n",
        "    \"\"\"\n",
        "\n",
        "    s = read_settings(work)\n",
        "\n",
        "    runtime = 0.0\n",
        "    time = simulation.context.getTime().value_in_unit(picosecond)\n",
        "\n",
        "    simulation.context.getIntegrator().setStepSize(stepsize*femtoseconds)\n",
        "    simulation.context.getIntegrator().setTemperature((temperature+273.15)*kelvin)\n",
        "\n",
        "    if s['PBC'] and stage in ['npt', 'production']:\n",
        "        simulation.context.setParameter(MonteCarloBarostat.Temperature(), (temperature+273.15)*kelvin)\n",
        "\n",
        "    while runtime < length:\n",
        "        step = simulation.context.getStepCount()\n",
        "        log = StateDataReporter(stream, 50, step=True, potentialEnergy=True,\n",
        "                                temperature=True, speed=True, time=True,\n",
        "                                density=s['PBC'])\n",
        "\n",
        "        i = 0\n",
        "        for f in glob.glob(work+stage+'_*.xtc'):\n",
        "            i += 1\n",
        "\n",
        "        save_freq = int(save_period/(stepsize*femtosecond))\n",
        "        xtc = XTCReporter(work+stage+f'_{i}.xtc', save_freq, False, s['PBC'])\n",
        "\n",
        "        simulation.reporters.clear()\n",
        "        simulation.reporters.append(log)\n",
        "        simulation.reporters.append(xtc)\n",
        "\n",
        "        for i in range(backup_period*60):\n",
        "            simulation.runForClockTime(1*second)\n",
        "            newStep = simulation.context.getStepCount()\n",
        "            now = simulation.context.getTime().value_in_unit(picosecond)\n",
        "            runtime = now - time\n",
        "            if runtime >= length:\n",
        "                break\n",
        "            lines = stream.read()\n",
        "            with open(work+stage+'_log.txt', 'a') as f:\n",
        "                f.write(lines)\n",
        "            line = lines.split('\\n')\n",
        "            if len(line) < 2:\n",
        "                continue\n",
        "            data = line[-2].split(',')\n",
        "            print('', end='\\r')\n",
        "            if len(data) < 6:\n",
        "                speed = float(data[4])\n",
        "                density = ''\n",
        "            else:\n",
        "                speed = float(data[5])\n",
        "                density = f'Density: {float(data[4]):.4f} g/mL, '\n",
        "            if stage != 'production':\n",
        "                T = f'Time: {float(data[1]):.1f} ps, '\n",
        "            else:\n",
        "                T = f'Time: {float(data[1])/1000:.2f} ns, '\n",
        "\n",
        "            if speed > 0:\n",
        "                d, hs = divmod((length - runtime)/speed/1000*24, 24)\n",
        "                h, mins = divmod(hs*60, 60)\n",
        "                min, secs = divmod(mins*60, 60)\n",
        "                sec = int(secs)\n",
        "                remaining = f'{str(int(d))+\":\" if d > 0 else \"\"}{int(h):0>2}:{int(min):0>2}:{sec:0>2} left, '\n",
        "            else:\n",
        "                remaining = '--:--:-- left, '\n",
        "\n",
        "            print(f'{remaining}Step: {data[0]}, {T}Temperature: {(float(data[3])-273.15):.2f} C, {density}Speed: {speed:.1f} ns/day', end='')\n",
        "\n",
        "        state = simulation.context.getState(getPositions=True, getVelocities=True)\n",
        "        with open(work+stage+'.xml', 'w') as f:\n",
        "            f.write(XmlSerializer.serialize(state))\n",
        "\n",
        "    print('\\nSimulation finished!')\n",
        "    return\n",
        "\n",
        "work = navigator(working_directory)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xoA5kbSMqkv5"
      },
      "source": [
        "## 1. PDB Input Preparation"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 614
        },
        "collapsed": true,
        "id": "5QASovvjuj2l",
        "outputId": "83f699b1-c412-456e-a01d-592473daf3eb"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Upload your PDB file.\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-706b4e9b-6b60-4b31-8646-17646444ca83\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-706b4e9b-6b60-4b31-8646-17646444ca83\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Saving start.pdb to start.pdb\n",
            "Adding missing atoms...done.\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "919107c599364819b4808553a4a5fc3f",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "NGLWidget()"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "#@title 1-1. Add missing atoms & Remove unrecognized molecules\n",
        "\n",
        "assert 'work' in globals(), \"Run cell# 0 to set working directory.\"\n",
        "\n",
        "#@markdown Enter the 4-letter PDB ID to fetch PDB file.<br/>\n",
        "#@markdown If you want to upload your PDB file, leave it as empty.\n",
        "PDB_ID = \"\" #@param {type:\"string\"}\n",
        "#@markdown For ligands/non-standard residues that are defined in [RCSB Chemical Component Dictionary](https://www.wwpdb.org/data/ccd),\n",
        "#@markdown enter the residue name below. <br/>For more than one non-standard residues, separate them using commas without spaces.\n",
        "#@markdown <br/>**The residue names you entered must match with the ones present in the PDB file!**\n",
        "non_standard_residues = \"PI4\" #@param {type:\"string\"}\n",
        "#@markdown For ligands/non-standard residues that are not defined on the RCSB Dictionary, run the next cell to upload the SDF file.<br/>\n",
        "#@markdown <br/> Check the box below to remove the water molecules present in your PDB.\n",
        "remove_crystallographic_water = False #@param {type:\"boolean\"}\n",
        "\n",
        "amino_acids = ['ALA', 'CYS', 'ASP', 'GLU', 'PHE', 'GLY', 'HIS', 'ILE', 'LYS', 'LEU',\n",
        "               'MET', 'ASN', 'PRO', 'GLN', 'ARG', 'SER', 'THR', 'VAL', 'TRP', 'TYR']\n",
        "nucleic_acids = ['A', 'T', 'G', 'C', 'U', 'I', 'DA', 'DT', 'DG', 'DC', 'DI']\n",
        "\n",
        "if non_standard_residues == \"\":\n",
        "    nsres = []\n",
        "else:\n",
        "    nsres = non_standard_residues.split(',')\n",
        "\n",
        "with open(work+'non_standard_residues.txt', 'w') as f:\n",
        "    f.write('# User-defined Non-standard Residues\\n')\n",
        "    for res in nsres:\n",
        "        f.write(res.upper()+'\\n')\n",
        "\n",
        "if PDB_ID == \"\":\n",
        "    print(\"Upload your PDB file.\")\n",
        "    pdbfile = files.upload()\n",
        "    try:\n",
        "        fixer = PDBFixer(filename=next(iter(pdbfile)))\n",
        "    except:\n",
        "        print('Error in reading the input pdbfile.')\n",
        "else:\n",
        "    try:\n",
        "        fixer = PDBFixer(pdbid=PDB_ID.upper())\n",
        "    except:\n",
        "        print('Error in fetching the pdb file from the RCSB.')\n",
        "\n",
        "print('Adding missing atoms...', end='')\n",
        "fixer.findMissingResidues()\n",
        "terminal_missing_res = []\n",
        "chains = list(fixer.topology.chains())\n",
        "for key in fixer.missingResidues.keys():\n",
        "    if key[1] == 0 or key[1] == len(list(chains[key[0]].residues())):\n",
        "        terminal_missing_res.append(key)\n",
        "for key in terminal_missing_res:\n",
        "    del fixer.missingResidues[key]\n",
        "fixer.findMissingAtoms()\n",
        "fixer.addMissingAtoms()\n",
        "\n",
        "model = Modeller(fixer.topology, fixer.positions)\n",
        "res_to_del = []\n",
        "for res in model.topology.residues():\n",
        "    if remove_crystallographic_water:\n",
        "        if res.name not in amino_acids+nucleic_acids+nsres:\n",
        "            res_to_del.append(res)\n",
        "    else:\n",
        "        if res.name not in (amino_acids+nucleic_acids+nsres+['HOH']):\n",
        "            res_to_del.append(res)\n",
        "\n",
        "model.delete(res_to_del)\n",
        "\n",
        "print('done.')\n",
        "\n",
        "with open(work+\"fixed.pdb\", 'w') as f:\n",
        "    PDBFile.writeFile(model.topology, model.positions, f)\n",
        "\n",
        "custom_info = {}\n",
        "\n",
        "view1 = nv.NGLWidget()\n",
        "view1._set_size('750px','500px')\n",
        "view1.add_component(nv.FileStructure(work+\"fixed.pdb\"))\n",
        "view1.add_licorice()\n",
        "display(view1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 478
        },
        "id": "LWF6fBt3OqU7",
        "outputId": "55d7ab61-0bd5-4692-bec1-4652bc2a1aaa"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Upload your ligand SDF file.\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-511848a6-14ed-42b5-9495-a401d1cbf013\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-511848a6-14ed-42b5-9495-a401d1cbf013\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Saving pi4.sdf to pi4.sdf\n",
            "Assign residue name to the structures of the residues you uploaded.\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f011d646a6dd477fa8219bd6b9d84b22",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Dropdown(description='Custom residue', options=('pi4.sdf',), value='pi4.sdf')"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "5a7db04c3394433390a96b4b9b3c11f0",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "NGLWidget()"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "4706b37205fe4796b0845b825328a4bc",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Dropdown(description='Choose residue name:', options=('PI4',), value='PI4')"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "#@title (Optional) Upload SDF files for Custom Ligands/Residues\n",
        "#@markdown For ligands/non-standard residues not defined on RCSB Chemical Component Dictionary, <br/>\n",
        "#@markdown run this cell to upload SDF file(s). <br/>\n",
        "\n",
        "assert 'work' in globals(), \"Please run the cell #0 to set working directory.\"\n",
        "assert len(nsres) > 0, \"No non-standard residues entered in the above cell!\"\n",
        "\n",
        "print(\"Upload your ligand SDF file.\")\n",
        "ligfiles = files.upload()\n",
        "\n",
        "lignames = list(ligfiles.keys())\n",
        "lig_select = widgets.Dropdown(options=lignames, value=lignames[0], description='Custom residue')\n",
        "view0 = nv.NGLWidget()\n",
        "view0._set_size('400px','300px')\n",
        "\n",
        "for lig in lignames:\n",
        "    custom_info[lig] = {}\n",
        "custom_info[lig_select.value]['id'] = view0.add_component(nv.FileStructure(lig_select.value))\n",
        "\n",
        "res_select = widgets.Dropdown(options=nsres, value=nsres[0], description='Choose residue name:')\n",
        "custom_info[lig_select.value]['name'] = res_select.value\n",
        "\n",
        "def update_mol2(change): # callback function to interactively update viewer\n",
        "    view0.remove_component(custom_info[change.old]['id'])\n",
        "    custom_info[change.new]['id'] = view0.add_component(nv.FileStructure(change.new))\n",
        "    view0.center()\n",
        "    custom_info[change.new]['name'] = res_select.value\n",
        "\n",
        "def update_name(change):\n",
        "    custom_info[lig_select.value]['name'] = change.new\n",
        "\n",
        "lig_select.observe(update_mol2, names='value')\n",
        "res_select.observe(update_name, names='value')\n",
        "\n",
        "print('Assign residue name to the structures of the residues you uploaded.')\n",
        "\n",
        "display(lig_select, view0, res_select)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 702
        },
        "id": "SYA6pxmcgyti",
        "outputId": "ae34695c-995f-4682-9bb3-62a720f5dcc4"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Here is your fixed pdb file.\n"
          ]
        },
        {
          "data": {
            "application/javascript": [
              "\n",
              "    async function download(id, filename, size) {\n",
              "      if (!google.colab.kernel.accessAllowed) {\n",
              "        return;\n",
              "      }\n",
              "      const div = document.createElement('div');\n",
              "      const label = document.createElement('label');\n",
              "      label.textContent = `Downloading \"${filename}\": `;\n",
              "      div.appendChild(label);\n",
              "      const progress = document.createElement('progress');\n",
              "      progress.max = size;\n",
              "      div.appendChild(progress);\n",
              "      document.body.appendChild(div);\n",
              "\n",
              "      const buffers = [];\n",
              "      let downloaded = 0;\n",
              "\n",
              "      const channel = await google.colab.kernel.comms.open(id);\n",
              "      // Send a message to notify the kernel that we're ready.\n",
              "      channel.send({})\n",
              "\n",
              "      for await (const message of channel.messages) {\n",
              "        // Send a message to notify the kernel that we're ready.\n",
              "        channel.send({})\n",
              "        if (message.buffers) {\n",
              "          for (const buffer of message.buffers) {\n",
              "            buffers.push(buffer);\n",
              "            downloaded += buffer.byteLength;\n",
              "            progress.value = downloaded;\n",
              "          }\n",
              "        }\n",
              "      }\n",
              "      const blob = new Blob(buffers, {type: 'application/binary'});\n",
              "      const a = document.createElement('a');\n",
              "      a.href = window.URL.createObjectURL(blob);\n",
              "      a.download = filename;\n",
              "      div.appendChild(a);\n",
              "      a.click();\n",
              "      div.remove();\n",
              "    }\n",
              "  "
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/javascript": [
              "download(\"download_3c5f5d4c-7b7f-4304-b00c-f5997aca5a9e\", \"fixed.pdb\", 157571)"
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Now upload the pdb file with all the hydrogens.\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-7c4ff368-c664-4782-a29a-0ceccfea3c85\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-7c4ff368-c664-4782-a29a-0ceccfea3c85\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Saving start.pdb to start (2).pdb\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "382e4027e7c747e9803bdd35f3b73e5b",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Dropdown(description='Focus at', options=('whole structure', <Residue 111 (PI4) of chain 1>), value='whole str…"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "a296bc3143b14da39b4f150890681aee",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "NGLWidget()"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "The protonated structure also is saved at the 'starting_structure.pdb' in your working directory.\n",
            "Please double check the protonation state of all residues, especially for non-standard ones!\n",
            "Subsequent steps will fail with incorrectly assigned atoms.\n"
          ]
        }
      ],
      "source": [
        "#@title 1-2. Add hydrogen atoms to the PDB file\n",
        "\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'fixed.pdb'), \"Please run the cell# 1-1 first.\"\n",
        "\n",
        "#@markdown Choose a method to add hydrogen atoms to your system : <br/>\n",
        "#@markdown * PDB2PQR - Uses PropKa to protonate systems without ligands.\n",
        "#@markdown * REDUCE - Works for ligands too, but only for physiological pH.\n",
        "#@markdown * OpenBabel - Can automatically protonate any system, but often buggy\n",
        "#@markdown * PDBFixer - Only works for standard residues\n",
        "#@markdown * Custom - Upload your PDB file with hydrogens (use external tools like\n",
        "#@markdown [DelPhipKa](http://compbio.clemson.edu/pka_webserver/),\n",
        "#@markdown [H++](http://newbiophysics.cs.vt.edu/H++/),\n",
        "#@markdown [PypKa](https://pypka.org/run-pypka/), etc.\n",
        "\n",
        "protonation_method = \"Custom\" #@param ['PDB2PQR', 'REDUCE', 'OpenBabel', 'PDBFixer', 'Custom']\n",
        "\n",
        "#@markdown Choose the reference pH for the determination of protonation state.\n",
        "pH = 7.4 #@param {type:\"slider\", min:0.0, max:14.0, step:0.1}\n",
        "\n",
        "for key, value in custom_info.items():\n",
        "    subprocess.run(f'cp {key} {work}{value[\"name\"]}.sdf', shell=True)\n",
        "\n",
        "\n",
        "def protonate_w_pdbfixer(work, removeH, pH)->None:\n",
        "    \"\"\"\n",
        "    Add missing hydrogen atoms to the PDB file using PDBFixer.\n",
        "    \"\"\"\n",
        "    print('Adding hydrogens using PDBFixer...', end='')\n",
        "    pdb = PDBFile(work+'fixed.pdb')\n",
        "    model = Modeller(pdb.topology, pdb.positions)\n",
        "\n",
        "    if removeH:\n",
        "        Hs = []\n",
        "        for a in model.topology.atoms():\n",
        "            if a.element.symbol == 'H':\n",
        "                Hs.append(a)\n",
        "        model.delete(Hs)\n",
        "\n",
        "    try:\n",
        "        model.addHydrogens(pH=pH)\n",
        "        with open(work+'starting_structure.pdb', 'w') as f:\n",
        "            PDBFile.writeFile(model.topology, model.positions, f)\n",
        "    except Exception as e:\n",
        "        print(e)\n",
        "    print('done.')\n",
        "    return\n",
        "\n",
        "\n",
        "def protonate_manually(work)->None:\n",
        "    \"\"\"\n",
        "    Enable uploading of custom PDB file.\n",
        "    \"\"\"\n",
        "    print('Here is your fixed pdb file.')\n",
        "    files.download(work+'fixed.pdb')\n",
        "    sleep(10)\n",
        "    print('Now upload the pdb file with all the hydrogens.')\n",
        "    fixed_wH = files.upload()\n",
        "    filename = next(iter(fixed_wH))\n",
        "    subprocess.run(f'cp -rf {filename} {work}starting_structure.pdb', shell=True)\n",
        "    return\n",
        "\n",
        "\n",
        "def protonate_w_openbabel(work, nsres, pH)->None:\n",
        "    \"\"\"\n",
        "    Add missing hydrogen atoms to the PDB file using OpenBabel.\n",
        "    Since OpenBabel names all the hydrogen as 'H', we need to rename them.\n",
        "    \"\"\"\n",
        "    print('Adding hydrogens using OpenBabel...', end='')\n",
        "\n",
        "    # save atom names before OpenBabel butchers them\n",
        "    pdb = PDBFile(work+'fixed.pdb')\n",
        "    nsatoms = []\n",
        "    for res in pdb.topology.residues():\n",
        "        if res.name in nsres:\n",
        "            atoms = []\n",
        "            for a in res.atoms():\n",
        "                atoms.append(a.name)\n",
        "            nsatoms.append({'name':res.name, 'chain':res.chain.id, 'index':res.id, 'atoms':atoms})\n",
        "\n",
        "    locale.getpreferredencoding = lambda: \"UTF-8\"\n",
        "    subprocess.run(['obabel', f'{work}fixed.pdb', '-O', 'tmp.pdb', '-xk', '-p', f'{pH}'])\n",
        "\n",
        "    with open('tmp.pdb', 'r') as f: # just number Hs so that OpenMM can discriminate them\n",
        "        lines = f.readlines()\n",
        "        chain = ''\n",
        "        resi = -100\n",
        "        headlines = ''\n",
        "        bodylines = []\n",
        "        taillines = ''\n",
        "        headflag = True\n",
        "        for line in lines:\n",
        "            if line.startswith('ATOM') or line.startswith('HETATM'):\n",
        "                headflag = False\n",
        "                if line[17:20] == 'UNL': # ligands/ncAAs\n",
        "                    if line[21] != chain: # reset index\n",
        "                        chain = line[21]\n",
        "                        resi = -100\n",
        "                    if int(line[22:26]) > resi:\n",
        "                        resi = int(line[22:26])\n",
        "                        count = 0 # 0-based index of nsres\n",
        "                        Hcount = 1 # 1-based index of Hs in the residue\n",
        "                    if line[77] == 'H':\n",
        "                        name = 'H'+str(Hcount)\n",
        "                        Hcount += 1\n",
        "                    else:\n",
        "                        name = nsatoms[resi-1]['atoms'][count]\n",
        "                        count += 1\n",
        "                    resname = nsatoms[resi-1]['name']\n",
        "                    chainid = nsatoms[resi-1]['chain']\n",
        "                    resindex = nsatoms[resi-1]['index']\n",
        "                    newinfo = f'{name:^4} {resname:>3} {chainid}{resindex:>4}'\n",
        "                elif line[77] == 'H': # element symbol\n",
        "                    if line[21] != chain: # chain ID\n",
        "                        chain = line[21]\n",
        "                        resi = -100\n",
        "                    if int(line[22:26]) > resi:\n",
        "                        resi = int(line[22:26])\n",
        "                        Hcount = 1\n",
        "                    name = 'H'+str(Hcount) # count number of Hs in a residue\n",
        "                    Hcount += 1\n",
        "                    newinfo = f'{name:^4}'+line[16:26]\n",
        "                else:\n",
        "                    newinfo = line[12:26]\n",
        "                newline = line[:12]\n",
        "                newline += newinfo\n",
        "                newline += line[26:]\n",
        "                bodylines.append(newline)\n",
        "            elif headflag:\n",
        "                headlines += line\n",
        "            else:\n",
        "                taillines += line\n",
        "\n",
        "    with open('tmp2.pdb', 'w') as f:\n",
        "        f.write(headlines)\n",
        "        for line in sorted(bodylines, key=lambda x: (x[21], int(x[22:26]))):\n",
        "            f.write(line)  # sort by chainID then residue index\n",
        "        f.write(taillines)\n",
        "\n",
        "    warnings.filterwarnings('ignore')\n",
        "    pdb2 = PDBFile('tmp2.pdb')\n",
        "\n",
        "    bonds_wH = []\n",
        "    for bond in pdb2.topology.bonds():\n",
        "        if bond[0].element.symbol == 'H':\n",
        "            bonds_wH.append([bond[1], bond[0]])\n",
        "        elif bond[1].element.symbol == 'H':\n",
        "            bonds_wH.append([bond[0], bond[1]])\n",
        "        else:\n",
        "            continue\n",
        "\n",
        "    counter = 4\n",
        "    for bond in bonds_wH:\n",
        "        multi = [b[0] for b in bonds_wH].count(bond[0]) # number of equivalent Hs\n",
        "        bond[1].residue = bond[0].residue\n",
        "        if counter > multi or counter == 0:\n",
        "            counter = multi\n",
        "        if bond[0].name == 'N':\n",
        "            if multi == 3: # N-terminus\n",
        "                bond[1].name = 'H'+str(counter)\n",
        "                counter -= 1\n",
        "            else:          # amide proton\n",
        "                bond[1].name = 'H'\n",
        "                counter -= 1\n",
        "        else:\n",
        "            if multi == 1:\n",
        "                bond[1].name = 'H'+bond[0].name[1:]\n",
        "                counter -= 1\n",
        "            elif multi == 2: # AMBER atom naming scheme (HB2, HB3 connected to CB)\n",
        "                if bond[0].element.symbol == 'C':\n",
        "                    bond[1].name = 'H'+bond[0].name[1:]+str(counter+1)\n",
        "                    counter -= 1\n",
        "                else:\n",
        "                    bond[1].name = 'H'+bond[0].name[1:]+str(counter)\n",
        "                    counter -= 1\n",
        "            elif multi == 3:\n",
        "                bond[1].name = 'H'+bond[0].name[1:]+str(counter)\n",
        "                counter -= 1\n",
        "\n",
        "    with open(work+'starting_structure.pdb', 'w') as f:\n",
        "        PDBFile.writeFile(pdb2.topology, pdb2.positions, f)\n",
        "    print('done.')\n",
        "    return\n",
        "\n",
        "\n",
        "\n",
        "def protonate_w_pdb2pqr(work, removeH, pH)->None:\n",
        "    \"\"\"\n",
        "    Add missing hydrogen atoms to the PDB file using PDB2PQR.\n",
        "    \"\"\"\n",
        "    print('Adding hydrogens using PDB2PQR...', end='')\n",
        "\n",
        "    if removeH:\n",
        "        pdb = PDBFile(work+'fixed.pdb')\n",
        "        model = Modeller(pdb.topology, pdb.positions)\n",
        "        Hs = []\n",
        "        for a in model.topology.atoms():\n",
        "            if a.element.symbol == 'H':\n",
        "                Hs.append(a)\n",
        "        model.delete(Hs)\n",
        "\n",
        "        with open('fixed-H.pdb', 'w') as f:\n",
        "            PDBFile.writeFile(model.topology, model.positions, f)\n",
        "\n",
        "        params = ' fixed-H.pdb fixed.pqr'\n",
        "\n",
        "    else:\n",
        "        params = f' {work}fixed.pdb fixed.pqr'\n",
        "\n",
        "\n",
        "    params += f' --ff AMBER --ffout AMBER --pdb-output {work}starting_structure.pdb'\n",
        "    params += f' --titration-state-method propka --with-ph {pH} --pH {pH} --drop-water'\n",
        "    subprocess.run(\"pdb2pqr\"+params, shell=True)\n",
        "    print('done.')\n",
        "    return\n",
        "\n",
        "\n",
        "\n",
        "def get_parmed_atom_from_name(structure, res_top, name):\n",
        "    for i, res in enumerate(structure.topology.residues()):\n",
        "        if res.name == res_top.name and res.index == res_top.index:\n",
        "            residue = structure.residues[i]\n",
        "            break\n",
        "    for atom in residue.atoms:\n",
        "        if atom.name == name:\n",
        "            return atom\n",
        "\n",
        "def get_parmed_res_from_top(structure, res_top):\n",
        "    for i, res in enumerate(structure.topology.residues()):\n",
        "        if res.name == res_top.name and res.index == res_top.index:\n",
        "            return structure.residues[i]\n",
        "\n",
        "def find_coordinate(structure, atom):\n",
        "    for i, a in enumerate(structure.atoms):\n",
        "        if a is atom:\n",
        "            return np.array([structure[i].xx, structure[i].xy, structure[i].xz])\n",
        "\n",
        "def add_missed_proton(structure, residue, coords)->None:\n",
        "    \"\"\"\n",
        "    Rarely, REDUCE program omits amide proton of some residues.\n",
        "    This function adds them back.\n",
        "    \"\"\"\n",
        "    H = pmd.Atom(name='H', atomic_number=1, type='H', mass=1.008, charge=0.0)\n",
        "\n",
        "    pmd_res = get_parmed_res_from_top(structure, residue)\n",
        "\n",
        "    structure.add_atom_to_residue(H, pmd_res)\n",
        "\n",
        "    for i, a in enumerate(structure.atoms):\n",
        "        if a is H:\n",
        "            structure[i].xx = coords[0]\n",
        "            structure[i].xy = coords[1]\n",
        "            structure[i].xz = coords[2]\n",
        "\n",
        "    structure.assign_bonds()\n",
        "\n",
        "    print(f'Added a missing amide proton at {residue}!')\n",
        "\n",
        "    return\n",
        "\n",
        "\n",
        "\n",
        "def protonate_w_reduce(work, removeH)->None:\n",
        "    \"\"\"\n",
        "    Add missing hydrogen atoms to the PDB file using REDUCE.\n",
        "    \"\"\"\n",
        "    print('Warning: With REDUCE, the reference pH is fixed to 7.4!')\n",
        "    print('Adding hydrogens using REDUCE...', end='')\n",
        "\n",
        "    if removeH:\n",
        "        Hflag = '-DROP_HYDROGENS_ON_ATOM_RECORDS '\n",
        "    else:\n",
        "        Hflag = ''\n",
        "    subprocess.run(f'reduce -BUILD {Hflag}{work}fixed.pdb > reduced.pdb', shell=True)\n",
        "    print('done.')\n",
        "\n",
        "    struc = pmd.load_file(\"reduced.pdb\")\n",
        "    struc.assign_bonds()\n",
        "\n",
        "    for chain in struc.topology.chains():\n",
        "        for i, res in enumerate(chain.residues()):\n",
        "            if i == 0 or res.name == 'PRO':\n",
        "                C = get_parmed_atom_from_name(struc, res, 'C')\n",
        "                O = get_parmed_atom_from_name(struc, res, 'O')\n",
        "                continue\n",
        "            N = get_parmed_atom_from_name(struc, res, 'N')\n",
        "\n",
        "            # In most cases, N-H is antiparallel to C=O\n",
        "            a_names = [atom.name for atom in res.atoms()]\n",
        "            if 'N' in a_names and 'CA' in a_names and 'C' in a_names and 'O' in a_names and 'H' not in a_names:\n",
        "                v_c = find_coordinate(struc, C) - find_coordinate(struc, O)\n",
        "                pos_H = find_coordinate(struc, N) + 1.01*v_c/np.linalg.norm(v_c)\n",
        "                add_missed_proton(struc, res, pos_H)\n",
        "\n",
        "            C = get_parmed_atom_from_name(struc, res, 'C')\n",
        "            O = get_parmed_atom_from_name(struc, res, 'O')\n",
        "\n",
        "    with open(work+'starting_structure.pdb', 'w') as f:\n",
        "        PDBFile.writeFile(struc.topology, struc.positions, f)\n",
        "    return\n",
        "\n",
        "\n",
        "#@markdown Check below box to ignore the hydrogen atoms currently present in your PDB.\n",
        "ignore_current_Hs = False #@param {type:\"boolean\"}\n",
        "\n",
        "if protonation_method == \"PDBFixer\":\n",
        "    protonate_w_pdbfixer(work, ignore_current_Hs, pH)\n",
        "\n",
        "elif protonation_method == \"OpenBabel\":\n",
        "    print('Installing OpenBabel...', end='')\n",
        "    subprocess.run(['mamba', 'install', '-c', 'conda-forge', 'openbabel'])\n",
        "    print('done.')\n",
        "    protonate_w_openbabel(work, nsres, pH)\n",
        "\n",
        "elif protonation_method == \"PDB2PQR\":\n",
        "    print('Installing PDB2PQR...', end='')\n",
        "    subprocess.run(['pip', 'install', 'pdb2pqr'])\n",
        "    print('done.')\n",
        "    protonate_w_pdb2pqr(work, ignore_current_Hs, pH)\n",
        "\n",
        "elif protonation_method == 'REDUCE':\n",
        "    print('Installing REDUCE...', end='')\n",
        "    subprocess.run(['mamba', 'install', '-c', 'bioconda', 'reduce'])\n",
        "    print('done.')\n",
        "    protonate_w_reduce(work, ignore_current_Hs)\n",
        "\n",
        "else:\n",
        "    protonate_manually(work)\n",
        "\n",
        "\n",
        "\n",
        "#@markdown Select the center of focus to zoom in/out.<br/>\n",
        "#@markdown You may also long-click an atom to center zoom and translate molecule with a right drag.\n",
        "\n",
        "to_lookat = []\n",
        "\n",
        "pdb = PDBFile(work+'starting_structure.pdb')\n",
        "\n",
        "for res in pdb.topology.residues():\n",
        "    if res.name in nsres:\n",
        "        to_lookat.append(res)\n",
        "\n",
        "# Interactively shows the protonated structure\n",
        "select_res = widgets.Dropdown(options=['whole structure']+to_lookat, value='whole structure', description='Focus at', continuous_update=True)\n",
        "view2 = nv.NGLWidget()\n",
        "view2._set_size('750px','500px')\n",
        "try:\n",
        "    view2.add_component(nv.FileStructure(work+\"starting_structure.pdb\"))\n",
        "except:\n",
        "    print(f\"While adding hydrogen atoms, an Error occurred in {protonation_method}.\")\n",
        "\n",
        "view2.add_licorice()\n",
        "view2.center()\n",
        "\n",
        "def center_of_view(change): # callback function for the update\n",
        "    view2.center(f'{change.new.id} and :{change.new.chain.id}' if change.new != 'whole structure' else None)\n",
        "\n",
        "select_res.observe(center_of_view, names='value')\n",
        "\n",
        "display(select_res, view2)\n",
        "\n",
        "print(\"The protonated structure also is saved at the 'starting_structure.pdb' in your working directory.\")\n",
        "print(\"Please double check the protonation state of all residues, especially for non-standard ones!\")\n",
        "print(\"Subsequent steps will fail with incorrectly assigned atoms.\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g0Ou4jzVqqi5"
      },
      "source": [
        "## 2. Create Simulation Object"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 418
        },
        "id": "yN-yWp8R4aoe",
        "outputId": "b6c85329-735f-4f1a-a5e8-94114a46e353"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "New residue infos must be registered to the Amber14 forcefield.\n",
            "Select a small molecule forcefield to compute the parameters of the residue with the structure shown below.\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "2d1a4a963f3e4d34bede317fcb93f684",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Dropdown(description='New residue', options=('PI4',), value='PI4')"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "15928b545018446d95da0d626a2022a6",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "NGLWidget()"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "4d42ecdc63b947818f6b66a51b2b0890",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Dropdown(description='forcefield', index=3, options=('GAFF-2.11', 'Sage-2.2.1', 'MACE-off23', 'GFN-FF', 'Custo…"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "#@title 2-1. Select a Forcefield\n",
        "assert 'work' in globals(), \"Please run the cell #0 to set working directory.\"\n",
        "\n",
        "def identify_new_res(fftype, forcefield, model, non_standard_residue_list)->list:\n",
        "    \"\"\"\n",
        "    Returns a list of nonstandard residues that\n",
        "    are not present in the given macromolecular forcefield.\n",
        "    \"\"\"\n",
        "\n",
        "    ions = ['AL', 'BA', 'BR', 'CA', 'CD', 'CL', 'CE', 'CO', 'CS', 'CU', 'EU',\n",
        "            'EU3', 'F', 'FE', 'FE2', 'GD3', 'HG', 'IN', 'IOD', 'K', 'LA', 'LI',\n",
        "            'LU', 'MG', 'MN', 'NA', 'NI', 'PB', 'PD', 'PR', 'PT', 'RB',\n",
        "            'SM', 'SR', 'TB', 'V', 'YB2', 'YB3', 'ZN']\n",
        "\n",
        "    if len(non_standard_residue_list) == 0:\n",
        "        return []\n",
        "\n",
        "    # Prepare copied modeller objects with a single nonstandard residue\n",
        "    models = {}\n",
        "    for res in non_standard_residue_list:\n",
        "        models[res] = copy.deepcopy(model)\n",
        "    for key, value in models.items():\n",
        "        other_res = []\n",
        "        for res in value.topology.residues():\n",
        "            if res.name in non_standard_residue_list and res.name != key:\n",
        "                other_res.append(res)\n",
        "        if len(other_res) > 0:\n",
        "            value.delete(other_res)\n",
        "\n",
        "    new_res = []\n",
        "\n",
        "    for key, value in models.items():\n",
        "        if key in ions:\n",
        "            continue\n",
        "        try:\n",
        "            if fftype == 'Amber14':\n",
        "                value.addExtraParticles(forcefield)\n",
        "            elif fftype == 'CHARMM36': #due to patches, CHARMM forcefield gives errors with addExtraParticles()\n",
        "                forcefield.createSystem(value.topology)\n",
        "            print(f'Found the residue template for {key} in the {fftype} forcefield!')\n",
        "\n",
        "        except ValueError: # Usually raised when no matching residue templates are found.\n",
        "            #print(str(e)[:41])\n",
        "            # Trim other residues and save first appearing structure of the nonstandard residue\n",
        "            res_to_del = []\n",
        "            counter = 0\n",
        "            for res in value.topology.residues():\n",
        "                if res.name != key or counter > 0:\n",
        "                    res_to_del.append(res)\n",
        "                else:\n",
        "                    counter += 1\n",
        "            value.delete(res_to_del)\n",
        "            with open(f'{key}.pdb', 'w') as f:\n",
        "                PDBFile.writeFile(value.topology, value.positions, f)\n",
        "            new_res.append(key)\n",
        "    return new_res\n",
        "\n",
        "\n",
        "def isLigand(model, name)->bool:\n",
        "    \"\"\"\n",
        "    Check whether the given residue is connected to the other residues.\n",
        "    If not, it is considered as a ligand.\n",
        "    \"\"\"\n",
        "    for res in model.topology.residues():\n",
        "        if res.name == name:\n",
        "            if len(list(res.external_bonds())) > 0:\n",
        "                return False\n",
        "            else:\n",
        "                return True\n",
        "\n",
        "def scan_elements(model, name)->bool:\n",
        "    \"\"\"\n",
        "    Check whether the given residue contains the elements that\n",
        "    are not supported by GAFF/SMIRNOFF/espaloma/MACE.\n",
        "    \"\"\"\n",
        "    gaff_elements = ['H', 'C', 'N', 'O', 'S', 'P', 'F', 'Cl', 'Br', 'I']\n",
        "\n",
        "    for res in model.topology.residues():\n",
        "        if res.name == name:\n",
        "            residue = res\n",
        "            break\n",
        "\n",
        "    elements = []\n",
        "    for atom in residue.atoms():\n",
        "        if atom.element.symbol not in elements:\n",
        "            elements.append(atom.element.symbol)\n",
        "\n",
        "    elements = list(set(elements))\n",
        "\n",
        "    for ele in elements:\n",
        "        if ele not in gaff_elements:\n",
        "            return False\n",
        "\n",
        "    return True\n",
        "\n",
        "\n",
        "#@markdown Select a forcefield to apply on your system's macromolecules.\n",
        "forcefield = 'Amber14' #@param ['Amber14', 'CHARMM36']\n",
        "\n",
        "#@markdown Select a water model.\n",
        "watermodel = \"(explicit) TIP3P\" #@param [\"(explicit) TIP3P\", \"(explicit) SPC/E\", \"(explicit) TIP4P-Ew\", \"(explicit) TIP5P\", \"(explicit) OPC\", \"(explicit) OPC3\", \"(implicit) HCT (igb=1)\", \"(implicit) OBC1 (igb=2)\", \"(implicit) OBC2 (igb=5)\", \"(implicit) GBn (igb=7)\", \"(implicit) GBn2 (igb=8)\"]\n",
        "\n",
        "#@markdown For ligands and non-standard residues, you should select a small molecule forcefield to apply on them below.\n",
        "#@markdown * GFN-FF : Semiempirical tight binding forcefield (can simulate chemical reactions, but slow)\n",
        "#@markdown * MACE-off : Machine-learning forcefield (currently having issues with temperature blowing up)\n",
        "#@markdown * GAFF : Uses Ambertool's GAFF template generator\n",
        "#@markdown * Sage : Uses OpenForceField's Smirnoff template generator\n",
        "#@markdown * espaloma : Small molecule forcefield parametrized by a neural network\n",
        "#@markdown * Custom : You should upload a XML file that contains the residue/atoms infos to the forcefield.\n",
        "\n",
        "ff, water = determine_forcefield(forcefield, watermodel)\n",
        "\n",
        "assert ff is not None, \"Forcefield not set.\"\n",
        "\n",
        "pdb = PDBFile(work+'starting_structure.pdb')\n",
        "model = Modeller(pdb.topology, pdb.positions)\n",
        "\n",
        "nsres = [a['name'] for a in read_non_standard_residues_list(work)]\n",
        "uaas = identify_new_res(forcefield, ff, model, nsres)\n",
        "uaa_info = {}\n",
        "uaa_atom_info = []\n",
        "\n",
        "\n",
        "if len(uaas) > 0:\n",
        "    print(f'New residue infos must be registered to the {forcefield} forcefield.')\n",
        "    print('Select a small molecule forcefield to compute the parameters of the residue with the structure shown below.')\n",
        "    if len(uaas) > 1:\n",
        "        print('Toggle the dropdown menu to select forcefield for other residue(s), too.')\n",
        "\n",
        "    for uaa in uaas:\n",
        "        lig_flag = isLigand(model, uaa)\n",
        "        viable_ffs = ['GFN-FF'] # GFN-FF is applicable to all elements on the Periodic Table.\n",
        "        if scan_elements(model, uaa):\n",
        "            viable_ffs = ['MACE-off23'] + viable_ffs # Machine Learning forcefields\n",
        "        if scan_elements(model, uaa) and lig_flag:\n",
        "            viable_ffs = ['GAFF-2.11', 'Sage-2.2.1'] + viable_ffs # small molecule forcefields\n",
        "        viable_ffs.append('Custom')\n",
        "        uaa_info[uaa] = {'name':uaa, 'file':f'{uaa}.pdb', 'lig':lig_flag, 'ff':'GFN-FF', 'ffs':viable_ffs}\n",
        "\n",
        "    pdb_select = widgets.Dropdown(options=uaas, value=uaas[0], description='New residue', continuous_update=True)\n",
        "    view3 = nv.NGLWidget()\n",
        "    view3._set_size('400px','300px')\n",
        "    # save NGLView component id to remove it later\n",
        "    uaa_info[pdb_select.value]['id'] = view3.add_component(nv.FileStructure(uaa_info[pdb_select.value]['file']))\n",
        "    ff_select = widgets.Dropdown(options=uaa_info[uaas[0]]['ffs'], value='GFN-FF', description='forcefield', continuous_update=True)\n",
        "\n",
        "    def update_pdb(change): # callback function to interactively update viewer\n",
        "        view3.remove_component(uaa_info[change.old]['id'])\n",
        "        uaa_info[change.new]['id'] = view3.add_component(nv.FileStructure(uaa_info[change.new]['file']))\n",
        "        view3.center(change.new)\n",
        "        ff_select.options = uaa_info[change.new]['ffs']\n",
        "        ff_select.value = uaa_info[change.new]['ff']\n",
        "\n",
        "    def update_ff(change): # callback function to interactively update residue infos\n",
        "        uaa_info[pdb_select.value]['ff'] = change.new\n",
        "        ffs =[]\n",
        "        for info in uaa_info.values():\n",
        "            ffs.append(info['ff'])\n",
        "\n",
        "    pdb_select.observe(update_pdb, names='value')\n",
        "    ff_select.observe(update_ff, names='value')\n",
        "\n",
        "    display(pdb_select, view3, ff_select)\n",
        "\n",
        "else:\n",
        "    print('All residues assigned to the forcefield! You can skip the next cell.')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true,
        "id": "GaqRQQMN629M",
        "outputId": "002e2a59-dc70-44da-b060-391a1e356a89"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "No non-ligand residue found!\n"
          ]
        }
      ],
      "source": [
        "#@title 2-2. Set buffer region around XTB/ML atoms\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert 'uaas' in globals(), \"Please run cell# 2-1 first.\"\n",
        "\n",
        "#@markdown Values for atomic partial charges and Leonnard-Jones parameters of non-standard residues are only approximate. <br/>\n",
        "#@markdown So constructing a buffer region with XTB/ML atoms to minimize the error from the non-bonded interaction between MM atoms and XTB/ML atoms is highly recommended. <br/>\n",
        "#@markdown Adjust cutoff distances around each nonstandard residues to set a buffer region. <br/>\n",
        "#@markdown **Do not run this cell more than once in a row!**\n",
        "\n",
        "def make_xml_for_custom_residues(fftype, ff, model, residue_infos)->bool:\n",
        "    \"\"\"\n",
        "    Generate a template XML file for custom residues.\n",
        "    \"\"\"\n",
        "    ncAA = []\n",
        "    for value in residue_infos.values():\n",
        "        if value['ff'] == 'Custom':\n",
        "            ncAA.append(value['name'])\n",
        "    if len(ncAA) == 0:\n",
        "        return False\n",
        "\n",
        "    templates, residues = ff.generateTemplatesForUnmatchedResidues(model.topology)\n",
        "\n",
        "    with open('template.xml', 'w') as f:\n",
        "        f.write(\"<ForceField>\\n\")\n",
        "        f.write(\" <AtomTypes>\\n\")\n",
        "        f.write(\" </AtomTypes>\\n\")\n",
        "        f.write(\" <Residues>\\n\")\n",
        "        for i, temp in enumerate(templates):\n",
        "            if temp.name in ncAA:\n",
        "                f.write(f'  <Residue name=\"{temp.name}\">\\n')\n",
        "                for atom in residues[i].atoms():\n",
        "                    f.write(f'   <Atom name=\"{atom.name}\" type=\"Enter_atom_type\"/>\\n')\n",
        "                for bond in residues[i].internal_bonds():\n",
        "                    f.write(f'   <Bond atomName1=\"{bond[0].name}\" atomName2=\"{bond[1].name}\"/>\\n')\n",
        "                for bond in residues[i].external_bonds():\n",
        "                    if bond[0] in list(residues[i].atoms()):\n",
        "                        atom = bond[0]\n",
        "                    elif bond[1] in list(residues[i].atoms()):\n",
        "                        atom = bond[1]\n",
        "                    f.write(f'   <ExternalBond atomName=\"{atom.name}\"/>\\n')\n",
        "                f.write('  </Residue>\\n')\n",
        "        f.write(\" </Residues>\\n\")\n",
        "        f.write(\" <HarmonicBondForce>\\n\")\n",
        "        f.write(\" </HarmonicBondForce>\\n\")\n",
        "        f.write(\" <HarmonicAngleForce>\\n\")\n",
        "        f.write(\" </HarmonicAngleForce>\\n\")\n",
        "        if fftype == 'CHARMM36':\n",
        "            f.write(' <AmoebaUreyBradleyForce>\\n')\n",
        "            f.write(\" </AmoebaUreyBradleyForce>\\n\")\n",
        "        if fftype == 'Amber14':\n",
        "            f.write(' <PeriodicTorsionForce ordering=\"amber\">\\n')\n",
        "        elif fftype == 'CHARMM36':\n",
        "            f.write(' <PeriodicTorsionForce ordering=\"charmm\">\\n')\n",
        "        f.write(\" </PeriodicTorsionForce>\\n\")\n",
        "        if fftype == 'CHARMM36':\n",
        "            f.write(' <CMAPTorsionForce>\\n')\n",
        "            f.write(\" </CMAPTorsionForce>\\n\")\n",
        "        if fftype == 'Amber14':\n",
        "            f.write(' <NonbondedForce coulomb14scale=\"0.8333333333333334\" lj14scale=\"0.5\">\\n')\n",
        "        elif fftype == 'CHARMM36':\n",
        "            f.write(' <NonbondedForce coulomb14scale=\"1.0\" lj14scale=\"1.0\" useDispersionCorrection=\"False\">\\n')\n",
        "        f.write('  <UseAttributeFromResidue name=\"charge\"/>\\n')\n",
        "        f.write(' </NonbondedForce>\\n')\n",
        "        if fftype == 'CHARMM36':\n",
        "            f.write(' <LennardJonesForce lj14scale=\"1.0\" useDispersionCorrection=\"False\">\\n')\n",
        "            f.write(' </LennardJonesForce>\\n')\n",
        "        f.write(\"</ForceField>\\n\")\n",
        "\n",
        "    files.download('template.xml')\n",
        "    sleep(5)\n",
        "    return True\n",
        "\n",
        "\n",
        "def find_terminal_form(pdb)->str:\n",
        "\n",
        "    mol = Chem.MolFromPDBFile(pdb, removeHs=False)\n",
        "\n",
        "    nterm = Chem.MolFromSmarts('[NH3+][CH1]C(=O)')\n",
        "    nterm_atoms = list(mol.GetSubstructMatch(nterm))\n",
        "    if len(nterm_atoms) > 0:\n",
        "        return 'N'\n",
        "\n",
        "    cterm = Chem.MolFromSmarts('[NH1][CH1]C(=O)[O-]')\n",
        "    cterm_atoms = list(mol.GetSubstructMatch(cterm))\n",
        "    if len(cterm_atoms) > 0:\n",
        "        return 'C'\n",
        "\n",
        "    pbackbone = Chem.MolFromSmarts('[NH1][CH1]C(=O)')\n",
        "    pbbatoms = list(mol.GetSubstructMatch(pbackbone))\n",
        "    if len(pbbatoms) > 0:\n",
        "        return 'bb-p'\n",
        "\n",
        "    return '-'\n",
        "\n",
        "\n",
        "def assign_partial_charges(name, residue_infos)->dict:\n",
        "\n",
        "    pdb = residue_infos[name]['file']\n",
        "    subprocess.run(f'obabel {pdb} -O {name}.mol2 --partialcharge mmff94', shell=True)\n",
        "\n",
        "    charges = {}\n",
        "\n",
        "    with open(f'{name}.mol2', 'r') as f:\n",
        "        lines = f.readlines()\n",
        "        atom_flag = False\n",
        "        for line in lines:\n",
        "            if line.strip().startswith('@<TRIPOS>ATOM'):\n",
        "                atom_flag = True\n",
        "                continue\n",
        "            elif line.strip().startswith('@<TRIPOS>BOND'):\n",
        "                atom_flag = False\n",
        "                break\n",
        "            if atom_flag:\n",
        "                data = line.strip().split( )\n",
        "                charges[data[1]] = round(float(data[-1]), 4)\n",
        "\n",
        "    term = find_terminal_form(pdb)\n",
        "    sum = 0.0\n",
        "    for q in charges.values():\n",
        "        sum += q\n",
        "    offset = float(int(sum))-sum\n",
        "\n",
        "    if term == \"-\":\n",
        "        for key, value in charges.items():\n",
        "            value += offset/len(charges)\n",
        "\n",
        "    elif term == \"N\":\n",
        "        before = 0.0\n",
        "        for key, value in charges.items():\n",
        "            if key == 'N':\n",
        "                before += value\n",
        "                value = -0.3\n",
        "            elif key == 'H1' or key == 'H2' or key == 'H3':\n",
        "                before += value\n",
        "                value = 0.33\n",
        "            elif key == 'CA':\n",
        "                before += value\n",
        "                value = 0.21\n",
        "            elif key == 'HA':\n",
        "                before += value\n",
        "                value = 0.1\n",
        "            elif key == 'C':\n",
        "                before += value\n",
        "                value = 0.51\n",
        "            elif key == 'O':\n",
        "                before += value\n",
        "                value = -0.51\n",
        "        offset += (before - 1) # N-terminus has +1 charge\n",
        "\n",
        "        for key, value in charges.items():\n",
        "            if key not in ['N', 'H1', 'H2', 'H3', 'CA', 'HA', 'C', 'O']:\n",
        "                value += offset/(len(charges)-8)\n",
        "\n",
        "    elif term == \"C\":\n",
        "        before = 0.0\n",
        "        for key, value in charges.items():\n",
        "            if key == 'C':\n",
        "                before += value\n",
        "                value = 0.34\n",
        "            elif key == 'O':\n",
        "                before += value\n",
        "                value = -0.67\n",
        "            elif key == 'OXT':\n",
        "                before += value\n",
        "                value = -0.67\n",
        "        offset += (before + 2) # C-terminus has -1 charge & formal charge for amide N is -1\n",
        "\n",
        "        for key, value in charges.items():\n",
        "            if key not in ['C', 'O', 'OXT']:\n",
        "                value += offset/(len(charges)-3)\n",
        "\n",
        "    elif term == 'bb-p':\n",
        "        before = 0.0\n",
        "        for key, value in charges.items():\n",
        "            if key == 'N':\n",
        "                before += value\n",
        "                value = -0.47\n",
        "            elif key == 'H':\n",
        "                before += value\n",
        "                value = 0.31\n",
        "            elif key == 'CA':\n",
        "                before += value\n",
        "                value = 0.07\n",
        "            elif key == 'HA':\n",
        "                before += value\n",
        "                value = 0.09\n",
        "            elif key == 'C':\n",
        "                before += value\n",
        "                value = 0.51\n",
        "            elif key == 'O':\n",
        "                before += value\n",
        "                value = -0.51\n",
        "        offset += (before + 1) # formal charge for amide N is -1, so correct it.\n",
        "\n",
        "        for key, value in charges.items():\n",
        "            if key not in ['N', 'H', 'CA', 'HA', 'C', 'O']:\n",
        "                value += offset/(len(charges)-6)\n",
        "\n",
        "    return charges\n",
        "\n",
        "\n",
        "\n",
        "def assign_LJ_parameters(fftype, ff, model, atomtype, element)->tuple:\n",
        "\n",
        "    resname = atomtype.split('_')[0]\n",
        "    atomname = atomtype.split('_')[1]\n",
        "\n",
        "    amber14LJ = {'C':(0.25104, 0.402), 'O':(0.79496, 0.333), 'N':(0.54392, 0.386)}\n",
        "    # parameters from\n",
        "    # M. Freindorf, Y. Shao, T. R. Furiani, and J. Kong.\n",
        "    # \"Lennard-Jones parameters for the combined QM/MM method using the B3LYP/6-31G*/AMBER potential\"\n",
        "    # J. Comput. Chem. 2005, 26(12): 1270-1278.\n",
        "    # https://doi.org/10.1002/jcc.20264\n",
        "\n",
        "    gaff2AB = {'S':(1.9825, 0.2824), 'P':(2.0732, 0.2295), 'F':(1.7029, 0.0832), 'Cl':(1.9452, 0.2638),\n",
        "                 'Br':(2.0275, 0.3932), 'I':(2.1558, 0.4955)}\n",
        "    amberions = {'Al':'AL', 'Ag':'Ag', 'Ba':'BA', 'Br':'BR', 'Be':'Be', 'Ca':'CA', 'Cd':'CD',\n",
        "                 'Cl':'CL', 'Co':'CO', 'Cs':'CS', 'Cu':'CU', 'Dy':'Dy', 'Er':'Er',\n",
        "                 'F':'F', 'Gd':'GD3', 'Hg':'HG', 'Hf':'Hf',\n",
        "                 'In':'IN', 'I':'IOD', 'K':'K', 'La':'LA', 'Li':'LI', 'Lu':'LU', 'Mg':'MG',\n",
        "                 'Mn':'MN', 'Na':'NA', 'Ni':'NI', 'Nd':'Nd', 'Pb':'PB', 'Pd':'PD', 'Pr':'PR',\n",
        "                 'Pt':'PT', 'Pu':'Pu', 'Rb':'RB', 'Ra':'Ra', 'Sm':'Sm', 'Sr':'SR', 'Sn':'Sn',\n",
        "                 'Tb':'TB', 'Th':'Th', 'Tl':'Tl', 'Tm':'Tm', 'U':'U4+', 'V':'V2+', 'Y':'Y',\n",
        "                 'Yb':'YB2', 'Zn':'ZN', 'Zr':'Zr'}\n",
        "    charmm36LJ = {'N':(0.8368, 0.329632525712), 'F':(0.56484, 0.290432982114), 'Si':(2.5104, 0.391995435982),\n",
        "                  'Al':(0.4460144, 0.039377723342), 'P':(2.44764, 0.3830864488), 'Cl':(1.435112, 0.34032331033),\n",
        "                  'Se':(2.606632, 0.387540942391), 'Br':(2.25936, 0.356359487256), 'I':(2.17568, 0.399122625727),\n",
        "                  'Be':(0.4250944, 0.007127189745), 'Sc':(0.589944, 0.195445360786), 'Ti':(1.7016328, 0.344011631023),\n",
        "                  'V':(0.6732056, 0.196656983042), 'Cr':(0.6974728, 0.188727984451), 'Mn':(0.7050040, 0.214474957405),\n",
        "                  'Fe':(0.667348, 0.192451941093), 'Co':(0.6439176, 0.165279530189), 'Ni':(0.5999856, 0.139033653953),\n",
        "                  'Cu':(0.7748768, 0.153590939007), 'Ga':(0.5045904, 0.040428983829), 'Sr':(0.9572992, 0.330683786199),\n",
        "                  'Y':(0.6928704, 0.251839249644), 'Rh':(0.537644, 0.082194315736), 'Pd':(0.7288528, 0.165190440318),\n",
        "                  'Ag':(1.200808, 0.216363662688), 'In':(0.6163032, 0.154357111905), 'Sn':(0.7861736, 0.295422014935),\n",
        "                  'La':(0.7932864, 0.315859231529), 'Ce':(0.7702744, 0.304954631219), 'Pr':(0.7627432, 0.295618012653),\n",
        "                  'Nd':(0.7497728, 0.288633366703), 'Pm':(0.74266, 0.29527947114), 'Sm':(1.0242432,0.330790694046),\n",
        "                  'Eu':(0.9907712,0.327922000173), 'Gd':(0.7209032, 0.26816051416), 'Tb':(0.7083512,0.262815121851),\n",
        "                  'Dy':(0.6999832,0.257362821696), 'Ho':(0.6928704, 0.247794569464), 'Er':(0.6845024,0.243625163463),\n",
        "                  'Tm':(0.677808, 0.240293202257), 'Yb':(0.8593936, 0.286691207498), 'Lu':(0.6644192, 0.24075646959),\n",
        "                  'Pt':(0.6824104, 0.142027073646), 'Au':(1.4907592, 0.112502690127), 'Hg':(0.8593936, 0.21057282102),\n",
        "                  'Tl':(0.6815736, 0.154891651136), 'Pb':(1.0016496, 0.313239989298), 'Bi':(0.77404, 0.243785525232),\n",
        "                  'Ra':(1.2631496,0.372377846208), 'U':(0.7932864, 0.30311937986), 'Pu':(0.7702744,0.297506717936)}\n",
        "    charmmions = {'Li':'LIT', 'Na':'SOD', 'Mg':'MG', 'K':'POT', 'Ca':'CAL', 'Rb':'RUB',\n",
        "                  'Cs':'CES', 'Ba':'BAR', 'Zn':'ZN', 'Cd':'CAD', 'Cl':'CLA'}\n",
        "\n",
        "    if fftype == 'Amber14':\n",
        "        if element == 'H':\n",
        "            for res in model.topology.residues():\n",
        "                if res.name == resname:\n",
        "                    for bond in res.bonds():\n",
        "                        if bond[0].name == atomname:\n",
        "                            parent = bond[1].element.symbol\n",
        "                            break\n",
        "                        elif bond[1].name == atomname:\n",
        "                            parent = bond[0].element.symbol\n",
        "                            break\n",
        "                        else:\n",
        "                            continue\n",
        "                    if parent == 'C': # nonpolar H\n",
        "                        lj = (0.12552, 0.222)\n",
        "                    else:             # polar H\n",
        "                        lj = (0.12552, 0.106)\n",
        "                    break\n",
        "            return lj\n",
        "        elif element in gaff2AB: # parm99.dat in Amber forcefield\n",
        "            A = gaff2AB[element][0]\n",
        "            B = gaff2AB[element][1]\n",
        "            sigma = ((A/B)**(1/6))/10  # sigma in Angstom\n",
        "            epsilon = B/4/(sigma**6)*4.184 # epsilon in kcal/mol\n",
        "            return (epsilon, sigma)\n",
        "        elif element in amber14LJ:\n",
        "            return amber14LJ[element]\n",
        "        elif element in amberions: # use parameters in ions definition\n",
        "            top = Topology()\n",
        "            chain = top.addChain(id='X')\n",
        "            residue = top.addResidue(amberions[element], chain)\n",
        "            top.addAtom(element, Element.getBySymbol(element), residue)\n",
        "            system = ff.createSystem(top, residueTemplates=dict(residue = amberions[element]))\n",
        "            for f in system.getForces():\n",
        "                if f.getName() == 'NonbondedForce':\n",
        "                    q, s, e = f.getParticleParameters(0)\n",
        "                    break\n",
        "            return (e,s)\n",
        "    elif fftype == 'CHARMM36':\n",
        "        if element == 'H':\n",
        "            for res in model.topology.residues():\n",
        "                if res.name == resname:\n",
        "                    for bond in res.bonds():\n",
        "                        if bond[0].name == atomname:\n",
        "                            parent = bond[1].element.symbol\n",
        "                            break\n",
        "                        elif bond[1].name == atomname:\n",
        "                            parent = bond[0].element.symbol\n",
        "                            break\n",
        "                        else:\n",
        "                            continue\n",
        "                    if parent == 'C': # nonpolar H\n",
        "                        lj = (0.192464, 0.040001352445)\n",
        "                    else:             # polar H\n",
        "                        lj = (0.092048, 0.235197261589)\n",
        "                    return lj\n",
        "        elif element == 'C':\n",
        "            for res in model.topology.residues():\n",
        "                if res.name == resname:\n",
        "                    count = 0\n",
        "                    for bond in res.bonds():\n",
        "                        if bond[0].name == atomname or bond[1].name == atomname:\n",
        "                            count += 1\n",
        "                    if count < 4: # aromatic / carbonyl C\n",
        "                        lj = (0.29288, 0.355005321205)\n",
        "                    else:         # aliphatic C\n",
        "                        lj = (0.08368, 0.405358916754)\n",
        "                    return lj\n",
        "        elif element == 'S':\n",
        "            for res in model.topology.residues():\n",
        "                if res.name == resname:\n",
        "                    count = 0\n",
        "                    for bond in res.bonds():\n",
        "                        if bond[0].name == atomname or bond[1].name == atomname:\n",
        "                            count += 1\n",
        "                    if count > 1: # thioether S\n",
        "                        lj = (1.8828, 0.356359487256)\n",
        "                    else:         # thiolate S\n",
        "                        lj = (1.96648, 0.391995435982)\n",
        "                    return lj\n",
        "        elif element == 'O':\n",
        "            for res in model.topology.residues():\n",
        "                if res.name == resname:\n",
        "                    count = 0\n",
        "                    for bond in res.bonds():\n",
        "                        if bond[0].name == atomname or bond[1].name == atomname:\n",
        "                            count += 1\n",
        "                    if count > 1: # ether O\n",
        "                        lj = (0.4184, 0.293996576986)\n",
        "                    else:         # anionic O\n",
        "                        lj = (0.50208, 0.302905564168)\n",
        "                    return lj\n",
        "        elif element in charmm36LJ:\n",
        "            return charmm36LJ[element]\n",
        "\n",
        "        elif element in charmmions: # use parameters in ions definition\n",
        "            top = Topology()\n",
        "            chain = top.addChain(id='X')\n",
        "            residue = top.addResidue(charmmions[element], chain)\n",
        "            top.addAtom(element, Element.getBySymbol(element), residue)\n",
        "            system = ff.createSystem(top)\n",
        "            for f in system.getForces():\n",
        "                if f.getName() in ['NonbondedForce', 'LennardJonesForce']:\n",
        "                    q, s, e = f.getParticleParameters(0)\n",
        "                    break\n",
        "            return (e,s)\n",
        "\n",
        "    # For elements not defined in AMBER/CHARMM, use OpenKIM Universal LJ parameters\n",
        "    # DOI : https://doi.org/10.25950/962b4967\n",
        "    if not os.path.exists('/content/LennardJones612_UniversalShifted.params'):\n",
        "        subprocess.run('wget https://openkim.org/files/MO_959249795837_003/LennardJones612_UniversalShifted.params', shell=True)\n",
        "    with open('LennardJones612_UniversalShifted.params', 'r') as f:\n",
        "        lines = f.readlines()\n",
        "        for line in lines:\n",
        "            if line and not line.startswith('#'):\n",
        "                data = line.strip().split( )\n",
        "                if len(data) == 5 and data[0] == element:\n",
        "                    epsilon = float(data[3])\n",
        "                    sigma = float(data[4])\n",
        "                    break\n",
        "    return (epsilon*96.485, sigma/10) # eV to kJ/mol, Anstrom to nm\n",
        "\n",
        "\n",
        "\n",
        "def assign_parameters(fftype, ff, model, residue_infos)->list:\n",
        "    \"\"\"\n",
        "    Assign those novel atom / residue types to the macromolecular forcefield.\n",
        "    \"\"\"\n",
        "    ambertype = {'N':'protein-N', 'CA':'protein-CX', 'C':'protein-C', 'O':'protein-O', 'H':'protein-H', 'HA':'protein-H1'}\n",
        "    charmmtype = {'N':'NH1', 'CA':'CT1', 'C':'C', 'O':'O', 'H':'H', 'HA':'HB1'}\n",
        "\n",
        "    templates, residues = ff.generateTemplatesForUnmatchedResidues(model.topology)\n",
        "    ncAA = []\n",
        "    for value in residue_infos.values():\n",
        "        if value['ff'] in ['GFN-FF', 'MACE-off23']:\n",
        "            ncAA.append(value['name'])\n",
        "    if len(ncAA) == 0:\n",
        "        return []\n",
        "\n",
        "    new_type = []\n",
        "    unk_index = 0\n",
        "    uaa_res = []\n",
        "    lj_parms = {}\n",
        "\n",
        "    for i, temp in enumerate(templates):\n",
        "        if temp.name not in ncAA:\n",
        "            for bond in residues[i].external_bonds(): # Search for normal atoms connected to the nonstandard atoms\n",
        "                if bond[0].residue is residues[i]:    # e.g. metal coordinating nitrogen in Histidine\n",
        "                    ext_atom = bond[1]\n",
        "                    int_atom = bond[0]\n",
        "                elif bond[1].residue is residues[i]:\n",
        "                    ext_atom = bond[0]\n",
        "                    int_atom = bond[1]\n",
        "                else:\n",
        "                    continue\n",
        "                if int_atom.name not in ambertype.keys(): # Remove bond from the topology\n",
        "                    if ext_atom.residue.name in [value['name'] for value in residue_infos.values()]:\n",
        "                        print(f'WARNING: A bond between atom {int_atom.name} in {int_atom.residue} and atom {ext_atom.name} in {ext_atom.residue} found!')\n",
        "                        print(f'You should consider adding {int_atom.residue} to the buffer region.')\n",
        "                        model.delete(bond)\n",
        "            continue # some normal residues (especially terminal ones) show up in this list, so skip them\n",
        "\n",
        "        lig_flag = residue_infos[temp.name]['lig']\n",
        "\n",
        "        if residue_infos[temp.name]['ff'] != 'GFN-FF':\n",
        "            charges = assign_partial_charges(temp.name, residue_infos)\n",
        "\n",
        "        for atom in temp.atoms:\n",
        "            if residue_infos[temp.name]['ff'] != 'GFN-FF':\n",
        "                atom.parameters = dict(charge=0.0)\n",
        "            else:\n",
        "                atom.parameters = dict(charge=charges[atom.name])\n",
        "\n",
        "            if not lig_flag and fftype == 'Amber14' and atom.name in ambertype.keys():\n",
        "                name = atom.name\n",
        "                atom.type = ambertype[atom.name] # For backbone atoms, follow AMBER scheme\n",
        "\n",
        "            elif not lig_flag and fftype == 'CHARMM36' and atom.name in charmmtype.keys():\n",
        "                name = atom.name\n",
        "                atom.type = charmmtype[atom.name] # For backbone atoms, follow CHARMM scheme\n",
        "\n",
        "            else:\n",
        "                name = temp.name+'_'+atom.name # For other atoms, register new atom type\n",
        "                atom.type = name\n",
        "                mass = atom.element.mass.value_in_unit(amu)\n",
        "                element = atom.element.symbol\n",
        "                ff.registerAtomType({'name':name, 'class':name, 'mass':mass, 'element':element})\n",
        "                new_type.append(name)\n",
        "                if residue_infos[temp.name]['ff'] != 'GFN-FF':\n",
        "                    lj_parms[name] = (0.0, 1.0)\n",
        "                else:\n",
        "                    lj_parms[name] = assign_LJ_parameters(fftype, ff, model, name, element)\n",
        "\n",
        "        try:\n",
        "            ff.registerResidueTemplate(temp)\n",
        "        except:\n",
        "            # search for duplicate residue name, and if present, rename it\n",
        "            print(f'There already is a residue template named {temp.name} in {fftype} forcefield!')\n",
        "            newName = 'UK'+str(unk_index)\n",
        "            print(f'Changing the residue name from {temp.name} to {newName}.')\n",
        "            residues[i].name = newName\n",
        "            ncAA[ncAA.index(temp.name)] = newName\n",
        "            temp.name = newName\n",
        "            ff.registerResidueTemplate(temp)\n",
        "            unk_index += 1\n",
        "\n",
        "        for res in model.topology.residues():\n",
        "            if res.name == temp.name:\n",
        "                uaa_res.append(res)\n",
        "\n",
        "\n",
        "    with open('userff.xml', 'w') as f: # Add custom xml file to set LJ parameters to zeros\n",
        "        f.write(\"<ForceField>\\n\")\n",
        "        if fftype == \"Amber14\":\n",
        "            f.write(' <NonbondedForce coulomb14scale=\"0.8333333333333334\" lj14scale=\"0.5\">\\n')\n",
        "            f.write('  <UseAttributeFromResidue name=\"charge\"/>\\n')\n",
        "            for at in new_type:\n",
        "                f.write(f'  <Atom class=\"{at}\" sigma=\"{lj_parms[at][1]}\" epsilon=\"{lj_parms[at][0]}\"/>\\n')\n",
        "        elif fftype == \"CHARMM36\":\n",
        "            f.write(' <NonbondedForce coulomb14scale=\"1.0\" lj14scale=\"1.0\" useDispersionCorrection=\"False\">\\n')\n",
        "            f.write('  <UseAttributeFromResidue name=\"charge\"/>\\n')\n",
        "            for at in new_type:\n",
        "                f.write(f'  <Atom class=\"{at}\" epsilon=\"{lj_parms[at][0]}\" sigma=\"{lj_parms[at][1]}\"/>\\n')\n",
        "        f.write(' </NonbondedForce>\\n')\n",
        "        if fftype == 'CHARMM36':\n",
        "            f.write(' <LennardJonesForce lj14scale=\"1.0\" useDispersionCorrection=\"False\">\\n')\n",
        "            for at in new_type:\n",
        "                f.write(f'  <Atom epsilon=\"{lj_parms[at][0]}\" sigma=\"{lj_parms[at][1]}\" type=\"{at}\"/>\\n')\n",
        "                #f.write(f'  <Atom epsilon=\"0.0\" epsilon14=\"0.0\" sigma=\"1.0\" sigma14=\"1.0\" type=\"{at}\"/>\\n')\n",
        "            f.write(' </LennardJonesForce>\\n')\n",
        "        f.write(\"</ForceField>\\n\")\n",
        "\n",
        "    ff.loadFile('userff.xml')\n",
        "    return uaa_res\n",
        "\n",
        "\n",
        "def update_qm_region(model, atomlist)->int:\n",
        "    \"\"\"\n",
        "    Similar to ONIOM, the MM/XTB or MM/ML boundary must be at isotropic bonds.\n",
        "    If not placed at carbon-carbon bond, expand the XTB/ML region.\n",
        "    \"\"\"\n",
        "    atoms_to_add = []\n",
        "    counter = 0\n",
        "    for atom1 in atomlist:\n",
        "        for bond in model.topology.bonds():\n",
        "            if bond[0] == atom1:\n",
        "                atom2 = bond[1]\n",
        "            elif bond[1] == atom1:\n",
        "                atom2 = bond[0]\n",
        "            else:\n",
        "                continue\n",
        "            if atom2 in atomlist:\n",
        "                continue\n",
        "            elif atom1.element.symbol != 'C' or atom2.element.symbol != 'C':\n",
        "                atoms_to_add.append(atom2)\n",
        "                counter += 1\n",
        "            elif atom1.residue.name in ['HIS', 'HIP', 'HID', 'HIE', 'PHE', 'TYR', 'TRP']:\n",
        "                if atom1.name not in  ['C', 'O', 'N', 'H', 'CA', 'HA', 'CB', 'HB1', 'HB2', 'HB3']:\n",
        "                    if atom2.name != 'CB':\n",
        "                        atoms_to_add.append(atom2)\n",
        "                        counter += 1\n",
        "    atomlist += atoms_to_add\n",
        "    return counter\n",
        "\n",
        "\n",
        "def find_neighbors(model, res_atoms, cutoff)->list:\n",
        "    \"\"\"\n",
        "    Find atoms within a cutoff distance from the given residue.\n",
        "    \"\"\"\n",
        "    contact_atoms = []\n",
        "    for i in res_atoms:\n",
        "        v1 = model.positions[i]\n",
        "        for j, v2 in enumerate(model.positions):\n",
        "            if j in res_atoms:\n",
        "                continue\n",
        "            if np.linalg.norm(np.array([v1.x-v2.x, v1.y-v2.y, v1.z-v2.z])) < cutoff:\n",
        "                contact_atoms.append(j)\n",
        "\n",
        "    qm_atoms = []\n",
        "    for atom in model.topology.atoms():\n",
        "        if atom.index in set(res_atoms+contact_atoms):\n",
        "            qm_atoms.append(atom)\n",
        "\n",
        "    counter = -1\n",
        "    while counter != 0:\n",
        "        counter = update_qm_region(model, qm_atoms)\n",
        "\n",
        "    return [a.index for a in qm_atoms]\n",
        "\n",
        "\n",
        "if len(uaas) == 0:\n",
        "    print('No need to run this cell!')\n",
        "else:\n",
        "    with open(work+'non_standard_residues.txt', 'w') as f:\n",
        "        f.write('# User-defined Non-standard Residues\\n')\n",
        "        f.write('#name\\t#type\\t#forcefield\\n')\n",
        "        for uaa in uaa_info.values():\n",
        "            f.write(f\"{uaa['name']}\\t{'ligand' if uaa['lig'] else 'residue'}\\t{uaa['ff']}\\n\")\n",
        "\n",
        "    if make_xml_for_custom_residues(forcefield, ff, model, uaa_info):\n",
        "        print('Upload a XML file for the non-standard residue definition.')\n",
        "        custom_xml = files.upload()\n",
        "        ff.loadFile(next(iter(custom_xml)))\n",
        "\n",
        "    uaa_res = assign_parameters(forcefield, ff, model, uaa_info)\n",
        "\n",
        "    if len(uaa_res) != 0:\n",
        "        uaa_res_names = [f'{res.name}_{res.index}{res.chain}' for res in uaa_res]\n",
        "        # Interactively determine the group of atoms to be treated differently\n",
        "        res_select = widgets.Dropdown(options=uaa_res_names, value=uaa_res_names[0], description='residue', continuous_update=True)\n",
        "        uaa_atom_info = []\n",
        "        for res in uaa_res:\n",
        "            atoms = []\n",
        "            for a in res.atoms():\n",
        "                atoms.append(a.index)\n",
        "            uaa_atom_info.append({'res':res, 'atoms':atoms, 'cutoff':0.0, 'neighbor':find_neighbors(model, atoms, 0.5), 'charge':0, 'spin':1})\n",
        "\n",
        "        cutoff_select = widgets.FloatSlider(value=0.0, min=0.0, max=1.5, step=0.1, description='cutoff(nm)', continuous_update=True)\n",
        "        charge_input = widgets.IntText(value=0, description='Total charge:', disabled=False, continuous_update=True)\n",
        "        spin_input = widgets.IntText(value=1, description='Spin :', disabled=False, continuous_update=True)\n",
        "\n",
        "        view4 = nv.NGLWidget()\n",
        "        view4._set_size('750px','500px')\n",
        "        view4.add_component(nv.FileStructure(work+\"starting_structure.pdb\"), defaultRepresentation=False)\n",
        "        view4.add_cartoon(\"protein or nucleic\")\n",
        "        view4.add_line()\n",
        "        uaa_atom_info[0]['cutoff'] = cutoff_select.value\n",
        "        neighbor = find_neighbors(model, uaa_atom_info[0]['atoms'], cutoff_select.value)\n",
        "        uaa_atom_info[0]['neighbor'] = neighbor\n",
        "        uaa_atom_info[0]['charge'] = charge_input.value\n",
        "        uaa_atom_info[0]['spin'] = spin_input.value\n",
        "        neighborhood = '@'+','.join([str(i) for i in neighbor])\n",
        "        view4.add_ball_and_stick(neighborhood)\n",
        "        view4.center(neighborhood)\n",
        "\n",
        "        def update_res(change):\n",
        "            res_index = uaa_res_names.index(change.new)\n",
        "            view4.clear_representations()\n",
        "            view4.add_cartoon(\"protein or nucleic\")\n",
        "            view4.add_line()\n",
        "            uaa_atom_info[res_index]['charge'] = charge_input.value\n",
        "            uaa_atom_info[res_index]['spin'] = spin_input.value\n",
        "            neighbor = find_neighbors(model, uaa_atom_info[res_index]['atoms'], cutoff_select.value)\n",
        "            neighborhood = '@'+','.join([str(i) for i in neighbor])\n",
        "            view4.add_ball_and_stick(neighborhood)\n",
        "            view4.center(neighborhood)\n",
        "\n",
        "        def update_cutoff(change):\n",
        "            res_index = uaa_res_names.index(res_select.value)\n",
        "            view4.clear_representations()\n",
        "            view4.add_cartoon(\"protein or nucleic\")\n",
        "            view4.add_line(\"not water\")\n",
        "            uaa_atom_info[res_index]['cutoff'] = change.new\n",
        "            neighbor = find_neighbors(model, uaa_atom_info[res_index]['atoms'], change.new)\n",
        "            neighborhood = '@'+','.join([str(i) for i in neighbor])\n",
        "            view4.add_ball_and_stick(neighborhood)\n",
        "            view4.center(neighborhood)\n",
        "            uaa_atom_info[res_index]['neighbor'] = neighbor\n",
        "            uaa_atom_info[res_index]['charge'] = charge_input.value\n",
        "            uaa_atom_info[res_index]['spin'] = spin_input.value\n",
        "\n",
        "        def update_charge(change):\n",
        "            res_index = uaa_res_names.index(res_select.value)\n",
        "            uaa_atom_info[res_index]['charge'] = change.new\n",
        "\n",
        "        def update_spin(change):\n",
        "            res_index = uaa_res_names.index(res_select.value)\n",
        "            uaa_atom_info[res_index]['spin'] = change.new\n",
        "\n",
        "        res_select.observe(update_res, names='value')\n",
        "        cutoff_select.observe(update_cutoff, names='value')\n",
        "        charge_input.observe(update_charge, names='value')\n",
        "        spin_input.observe(update_spin, names='value')\n",
        "\n",
        "        display(res_select, cutoff_select, view4, charge_input, spin_input)\n",
        "    else:\n",
        "        for uaa in uaa_info.values():\n",
        "            assert uaa['lig'], 'Did you run this cell more than once? Run again from the cell# 2-1.'\n",
        "        print('No non-ligand residue found!')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "A5kqyHcPryj3"
      },
      "source": [
        "### 2-3. Prepare Simulation"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "SCYS8pxLys66"
      },
      "outputs": [],
      "source": [
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert 'uaas' in globals(), \"Please run from the cell# 2-1.\"\n",
        "\n",
        "#@markdown Set the ionic strength of the solution in mol/L.\n",
        "ion_conc = 0.15 #@param {type:\"slider\", min:0.0, max:2.0, step:0.05}\n",
        "#@markdown For explicit water models, set the additional parameters below.\n",
        "\n",
        "#@markdown Set the thickness of the solvent pad around the protein in nanometers.\n",
        "padding = 2 #@param {type:\"slider\", min:1.0, max:5.0, step:0.1}\n",
        "cation = \"Na+\" #@param [\"Li+\", \"Na+\", \"K+\", \"Rb+\", \"Cs+\"]\n",
        "anion = \"Cl-\" #@param [\"F-\", \"Cl-\", \"Br-\", \"I-\"]\n",
        "#@markdown Set below constraints / increase the hydrogen mass to allow larger integration step sizes.\n",
        "rigidWater = True #@param {type:\"boolean\"}\n",
        "constraints = \"HBonds\" #@param [\"None\", \"HBonds\", \"AllBonds\", \"HAngles\"]\n",
        "hydrogenMass = 2 #@param {type:\"slider\", min:1.0, max:3.0, step:0.1}\n",
        "#@markdown Set the precision of the calculation: (cost-efficient) single -> mixed -> double (high precision)\n",
        "precision = \"mixed\" #@param [\"single\", \"mixed\", \"double\"]\n",
        "temperature = 0\n",
        "\n",
        "assert forcefield != \"CHARMM36\" or all(p['ff'] != 'MACE-off23' for p in uaa_info.values()), \"Currently, ML forcefield can only be coupled with AMBER forcefield!\"\n",
        "assert forcefield != \"CHARMM36\" or padding >= 1.2, \"The minimum padding distance must be larger than the cutoff distance of 1.2 nm!\"\n",
        "assert all(p['ff'] != 'MACE-off23' for p in uaa_info.values()) or water != '', 'ML forcefield does not support implicit solvation model!'\n",
        "\n",
        "def get_openff_ligand(work, ligand_info):\n",
        "    \"\"\"\n",
        "    Register ligand template to the macromolecular forcefield.\n",
        "    \"\"\"\n",
        "    name = ligand_info[\"name\"]\n",
        "\n",
        "    if os.path.exists(work+name+'.sdf'):\n",
        "        sdf_file = work + name+'.sdf'\n",
        "    elif os.path.exists(name+'_ideal.sdf'):\n",
        "        sdf_file = name+'_ideal.sdf'\n",
        "    else:\n",
        "        subprocess.run(f'wget https://files.rcsb.org/ligands/download/{name}_ideal.sdf', shell=True)\n",
        "        sdf_file = f'{name}_ideal.sdf'\n",
        "\n",
        "    SDF = Chem.rdmolfiles.SDMolSupplier(sdf_file)[0]\n",
        "    PDB = AllChem.MolFromPDBFile(f'{name}.pdb', removeHs=True)\n",
        "    ligand_noH = AllChem.AssignBondOrdersFromTemplate(SDF, PDB)\n",
        "    ligand = AllChem.MolFromPDBFile(f'{name}.pdb', removeHs=False)\n",
        "\n",
        "    for bond in ligand_noH.GetBonds():\n",
        "        pos1 = ligand_noH.GetConformer().GetAtomPosition(bond.GetBeginAtomIdx())\n",
        "        pos2 = ligand_noH.GetConformer().GetAtomPosition(bond.GetEndAtomIdx())\n",
        "        for i in range(ligand.GetNumAtoms()):\n",
        "            pos = ligand.GetConformer().GetAtomPosition(i)\n",
        "            if all(pos[j] == pos1[j] for j in range(3)):\n",
        "                aid1 = i\n",
        "            elif all(pos[j] == pos2[j] for j in range(3)):\n",
        "                aid2 = i\n",
        "            else:\n",
        "                continue\n",
        "        ligand.GetBondBetweenAtoms(aid1, aid2).SetBondType(bond.GetBondType())\n",
        "\n",
        "    Chem.SanitizeMol(ligand)\n",
        "\n",
        "    Chem.rdmolops.AssignStereochemistryFrom3D(ligand)\n",
        "    openff_ligand = Molecule.from_rdkit(ligand, hydrogens_are_explicit=True)\n",
        "    openff_ligand.name = name\n",
        "    openff_ligand.assign_partial_charges('mmff94')\n",
        "\n",
        "    with open(f'{work}{name}.json', 'w') as f:\n",
        "        f.write(openff_ligand.to_json())\n",
        "\n",
        "    return openff_ligand\n",
        "\n",
        "\n",
        "def register_ml_residues(system, topology, pbc, residue_infos, atom_infos):\n",
        "    \"\"\"\n",
        "    Create MM-ML or MM-XTB mixed system\n",
        "    \"\"\"\n",
        "\n",
        "    xtb_atoms = []\n",
        "    total_charge = 0\n",
        "    total_e = 0\n",
        "    ml_atoms = []\n",
        "\n",
        "    for key1, value1 in residue_infos.items():\n",
        "        for res in atom_infos:\n",
        "            if res['res'].name == key1:\n",
        "                if value1['ff'] == 'GFN-FF':\n",
        "                    xtb_atoms.extend(res['neighbor'])\n",
        "                    total_charge += res['charge']\n",
        "                    total_e += float(res['spin']-1)/2\n",
        "                elif value1['ff'] == 'MACE-off23':\n",
        "                    ml_atoms.extend(res['neighbor'])\n",
        "\n",
        "    xtb_atoms = set(xtb_atoms)\n",
        "    ml_atoms = set(ml_atoms)\n",
        "\n",
        "    element_list = []\n",
        "\n",
        "    for a in list(xtb_atoms):\n",
        "        for atom in topology.atoms():\n",
        "            if atom.index == a:\n",
        "                element_list.append(atom.element.atomic_number)\n",
        "\n",
        "    if len(xtb_atoms&ml_atoms)>0:\n",
        "        print('An atom cannot be allocated to two or more different forcefields!')\n",
        "        print('Unify your small molecule forcefields or decrease cutoffs to remove overlapping atoms.')\n",
        "        return None\n",
        "\n",
        "    if len(ml_atoms) > 0:\n",
        "        potential = MLPotential('mace-off23-small')\n",
        "        print(\"Creating MM-ML Mixed system...\")\n",
        "        warnings.filterwarnings('ignore')\n",
        "        system2 = potential.createMixedSystem(topology, system, ml_atoms,\n",
        "                                              removeConstraints=False,\n",
        "                                              implementation='nnpops',\n",
        "                                              precision='single')\n",
        "        print(\"done.\")\n",
        "    else:\n",
        "        system2 = system\n",
        "\n",
        "    if len(xtb_atoms) > 0:\n",
        "        print(\"Creating MM-XTB Mixed system...\")\n",
        "        system2.addForce(XtbForce(XtbForce.GFNFF, total_charge, int(total_e/2+1),\n",
        "                                  pbc, xtb_atoms, element_list))\n",
        "        print(\"done.\")\n",
        "\n",
        "    return system2\n",
        "\n",
        "\n",
        "def save_settings(work, forcefield, watermodel, ion_conc, pbc, cation, anion, padding, rigidWater, constraints, hydrogenMass, precision):\n",
        "    \"\"\"\n",
        "    Save simulation settings to settings.txt file.\n",
        "    \"\"\"\n",
        "    settings = f\"\"\"\n",
        "    Forcefield : {forcefield}\n",
        "    Watermodel : {watermodel}\n",
        "    Ionic strength (in mol/L) : {ion_conc}\n",
        "    Periodic Boundary Condition : {pbc}\n",
        "    Cation : {cation}\n",
        "    Anion : {anion}\n",
        "    Padding (in nm) : {padding}\n",
        "    Rigidwater : {rigidWater}\n",
        "    Constraints : {constraints}\n",
        "    Hydrogen mass (in amu) : {hydrogenMass}\n",
        "    Precision : {precision}\n",
        "    \"\"\"\n",
        "    with open(work+\"settings.txt\", 'w') as f:\n",
        "        f.write(settings)\n",
        "    return\n",
        "\n",
        "\n",
        "\n",
        "gaff = []\n",
        "smirnoff = []\n",
        "espaloma = []\n",
        "\n",
        "for key, value in uaa_info.items():\n",
        "    if value['ff'] == 'GAFF-2.11':\n",
        "        gaff.append(get_openff_ligand(work, value))\n",
        "    elif value['ff'] == 'Sage-2.2.1':\n",
        "        smirnoff.append(get_openff_ligand(work, value))\n",
        "    elif value['ff'] == 'espaloma-0.3.2':\n",
        "        espaloma.append(get_openff_ligand(work, value))\n",
        "\n",
        "if len(gaff) > 0:\n",
        "    gaff_g = GAFFTemplateGenerator(molecules=gaff)\n",
        "    ff.registerTemplateGenerator(gaff_g.generator)\n",
        "if len(smirnoff) > 0:\n",
        "    smirnoff_g = SMIRNOFFTemplateGenerator(molecules=smirnoff)\n",
        "    ff.registerTemplateGenerator(smirnoff_g.generator)\n",
        "if len(espaloma) > 0:\n",
        "    espaloma_g = EspalomaTemplateGenerator(molecules=espaloma)\n",
        "    ff.registerTemplateGenerator(espaloma_g.generator)\n",
        "\n",
        "if water != '':\n",
        "    print(\"Adding solvent...\", end='')\n",
        "    model.addSolvent(ff, model=water, padding=padding*nanometers, positiveIon=cation,\n",
        "                     negativeIon=anion, ionicStrength=ion_conc*molar, neutralize=True)\n",
        "    print(\"done.\")\n",
        "\n",
        "    print(\"Creating system...\", end='')\n",
        "\n",
        "    if forcefield == \"Amber14\":\n",
        "        system = ff.createSystem(model.topology, nonbondedMethod=PME,\n",
        "                                 nonbondedCutoff=1.0 *nanometer, constraints=constraints,\n",
        "                                 rigidWater=rigidWater, removeCMMotion=True,\n",
        "                                 hydrogenMass=hydrogenMass*amu)\n",
        "    elif forcefield == \"CHARMM36\":\n",
        "        # CHARMM forcefield recommends the use of switch distance at 1.0 nm and cutoff distance at 1.2 nm.\n",
        "        system = ff.createSystem(model.topology, nonbondedMethod=PME,\n",
        "                                 nonbondedCutoff=1.2*nanometer, constraints=constraints,\n",
        "                                 rigidWater=rigidWater, removeCMMotion=True,\n",
        "                                 switchDistance=1.0*nanometer,\n",
        "                                 hydrogenMass=float(hydrogenMass)*amu)\n",
        "\n",
        "else:\n",
        "    print(\"Creating system...\", end='')\n",
        "\n",
        "    kappa = 367.434915*sqrt(float(ion_conc)/78.5/(int(temperature)+273.15))\n",
        "\n",
        "    if forcefield == \"Amber14\":\n",
        "        system = ff.createSystem(model.topology, nonbondedMethod=CutoffNonPeriodic,implicitSolventKappa=kappa,\n",
        "                                 nonbondedCutoff=1.0*nanometer, constraints=constraints, hydrogenMass=float(hydrogenMass)*amu)\n",
        "\n",
        "    elif forcefield == \"CHARMM36\":\n",
        "        system = ff.createSystem(model.topology, nonbondedMethod=CutoffNonPeriodic,implicitSolventKappa=kappa,\n",
        "                                 nonbondedCutoff=1.2*nanometer, switchDistance=1.0*nanometer, constraints=constraints,\n",
        "                                 hydrogenMass=float(hydrogenMass)*amu)\n",
        "\n",
        "print('done.')\n",
        "\n",
        "\n",
        "\n",
        "if water == '':\n",
        "    pbc = False\n",
        "else:\n",
        "    pbc = True\n",
        "\n",
        "final_system = register_ml_residues(system, model.topology, pbc, uaa_info, uaa_atom_info)\n",
        "\n",
        "assert final_system is not None, \"System not created!\"\n",
        "\n",
        "\n",
        "with open(work+'system.xml', 'w') as f:\n",
        "    f.write(XmlSerializer.serialize(final_system))\n",
        "\n",
        "print(\"Creating simulation...\", end='')\n",
        "T = 273.15*kelvin\n",
        "\n",
        "if any([p['ff'] == 'MACE-off23' for p in uaa_info.values()]):\n",
        "\n",
        "    integrator = NoseHooverIntegrator(0.001*femtoseconds)\n",
        "\n",
        "    ml_atoms = []\n",
        "    for p in uaa_atom_info:\n",
        "        ml_atoms.extend(p['neighbor'])\n",
        "    ml_atoms = set(ml_atoms)\n",
        "\n",
        "    mm_atoms = []\n",
        "    for a in model.topology.atoms():\n",
        "        if a.index not in ml_atoms:\n",
        "            mm_atoms.append(a.index)\n",
        "\n",
        "    integrator.addSubsystemThermostat(thermostatedParticles=mm_atoms,\n",
        "                                      thermostatedPairs=[],\n",
        "                                      temperature=T, relativeTemperature=T,\n",
        "                                      collisionFrequency=1/picosecond,\n",
        "                                      relativeCollisionFrequency=1/picosecond,\n",
        "                                      chainLength=3, numMTS=3, numYoshidaSuzuki=7)\n",
        "\n",
        "    integrator.addSubsystemThermostat(thermostatedParticles=list(ml_atoms),\n",
        "                                      thermostatedPairs=[],\n",
        "                                      temperature=T, relativeTemperature=T,\n",
        "                                      collisionFrequency=200/picosecond,\n",
        "                                      relativeCollisionFrequency=200/picosecond,\n",
        "                                      chainLength=5, numMTS=5, numYoshidaSuzuki=7)\n",
        "\n",
        "elif water != '':\n",
        "    integrator = NoseHooverIntegrator(0.1*femtoseconds)\n",
        "\n",
        "    integrator.addThermostat(temperature=T, collisionFrequency=1/picosecond,\n",
        "                             chainLength=3, numMTS=3, numYoshidaSuzuki=7)\n",
        "\n",
        "else:\n",
        "    integrator = LangevinMiddleIntegrator(T, 1/picosecond, 0.1*femtoseconds)\n",
        "\n",
        "with open(work+'integrator.xml', 'w') as f:\n",
        "    f.write(XmlSerializer.serialize(integrator))\n",
        "\n",
        "platform = Platform.getPlatformByName('CUDA')\n",
        "properties = {'Precision': precision}\n",
        "simulation = Simulation(model.topology, final_system, integrator, platform, properties)\n",
        "print(\"done.\")\n",
        "\n",
        "print(\"Minimizing...\", end='')\n",
        "simulation.context.setPositions(model.positions)\n",
        "simulation.minimizeEnergy(tolerance=0.001*kilojoules/(nanometer*mole))\n",
        "positions = simulation.context.getState(getPositions=True).getPositions()\n",
        "\n",
        "with open(work+\"minimized.pdb\", 'w') as f:\n",
        "    PDBFile.writeFile(simulation.topology, positions, f)\n",
        "print(\"done.\")\n",
        "\n",
        "save_settings(work, forcefield, watermodel, ion_conc, pbc, cation, anion, padding, rigidWater, constraints, hydrogenMass, precision)\n",
        "\n",
        "simulation.context.setStepCount(0)\n",
        "simulation.context.setTime(0)\n",
        "state = simulation.context.getState(getPositions=True, getVelocities=True)\n",
        "with open(work+\"start.xml\", 'w') as f:\n",
        "    f.write(XmlSerializer.serialize(state))\n",
        "stage = 'start'\n",
        "\n",
        "print(\"You are now ready to start the simulation!\")\n",
        "\n",
        "view3 = nv.NGLWidget()\n",
        "view3._set_size('750px','500px')\n",
        "view3.add_component(nv.FileStructure(work+\"minimized.pdb\"))\n",
        "view3.add_licorice()\n",
        "if water != '':\n",
        "    view3.add_point(\"water\")\n",
        "    view3.add_spacefill(\"ion\")\n",
        "view3.center()\n",
        "view3"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7Xf2GSRAqxDg"
      },
      "source": [
        "## 3. Run the Simulation"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "y_rBhzYx6K3m"
      },
      "outputs": [],
      "source": [
        "#@title 3-1. NVT Equilibration\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "\n",
        "#@markdown Equilibrate the system for n more picoseconds.\n",
        "eq_time = 50 #@param {type:\"slider\", min:0.0, max:1000.0, step:10.0}\n",
        "#@markdown Set the integration step size in femtoseconds.\n",
        "step_size = 1 #@param {type:\"slider\", min:0.01, max:1, step:0.01}\n",
        "#@markdown Set the temperature of the system in **degrees Celsius**.\n",
        "temperature = 25 #@param {type:\"slider\", min:0.0, max:100.0, step:1.0}\n",
        "#@markdown Backup the production run's progress to the GoogleDrive every n realtime minutes.\n",
        "#@markdown Set it to smaller values if you are using free Colab sessions.\n",
        "backup_interval = 15 #@param {type:\"slider\", min:1, max:60, step:1}\n",
        "#@markdown Spring constant (in kJ/mol*nm^2) for the positional restraint on heavy atoms\n",
        "positional_restraint = 1200 #@param {type:\"slider\", min:0, max:3000, step:100}\n",
        "\n",
        "simulation, stage = recall_simulation(work)\n",
        "\n",
        "assert stage != 'npt', 'NPT equilibration is already started.'\n",
        "assert stage != 'production', 'Production run already started.'\n",
        "assert eq_time > 0, 'You set the equilibration time to zero. No more NVT equilibration performing.'\n",
        "\n",
        "if stage == 'start':\n",
        "    simulation = apply_restraints(work, simulation, int(positional_restraint))\n",
        "    simulation.context.setVelocitiesToTemperature((int(temperature)+273.15)*kelvin)\n",
        "    print('Now starting the NVT equilibration!')\n",
        "    print(f'Running NVT run for {eq_time} picoseconds.')\n",
        "    stage = 'nvt'\n",
        "    state = simulation.context.getState(getPositions=True, getVelocities=True)\n",
        "    with open(work+'nvt_step_0.xml', 'w') as f:\n",
        "        f.write(XmlSerializer.serialize(state))\n",
        "    assert os.path.exists(work+'nvt_step_0.xml'), 'State data not recorded.'\n",
        "\n",
        "else:\n",
        "    print(f'NVT equilbration has been performed for {simulation.context.getTime()} picoseconds.')\n",
        "    print(f'Running NVT run for {eq_time} more picoseconds.')\n",
        "\n",
        "subprocess.run(f'echo \"\\tTime step (in fs) : {step_size}\" >> {work}settings.txt', shell=True)\n",
        "subprocess.run(f'echo \"\\tTemperature (in Celsius) : {temperature}\" >> {work}settings.txt', shell=True)\n",
        "subprocess.run(f'echo \"\\tRestraint (NVT, kJ/mol*nm^2) : {positional_restraint}\" >> {work}settings.txt', shell=True)\n",
        "\n",
        "stream = SimulationStream()\n",
        "f = open(work+\"nvt_log.txt\", 'a')\n",
        "f.close()\n",
        "run_simulation(work, stage, simulation, stream, step_size, temperature,\n",
        "               float(eq_time), 5*picoseconds, int(backup_interval))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "Ut9NEwrxnPA9"
      },
      "outputs": [],
      "source": [
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'nvt_log.txt'), \"Please run the cell# 3-1 first.\"\n",
        "\n",
        "#@markdown Verify temperature convergence\n",
        "time = []\n",
        "temp = []\n",
        "s = read_settings(work)\n",
        "\n",
        "with open(work+\"nvt_log.txt\", 'r') as f:\n",
        "    for line in f.readlines():\n",
        "        if line.startswith(\"#\"):\n",
        "            continue\n",
        "        line = line.strip().split(',')\n",
        "        step = float(line[0])\n",
        "        time.append(step*s['stepsize']/picoseconds)\n",
        "        temp.append(round(float(line[3]),2))\n",
        "\n",
        "target_temp = round(s['temperature']/kelvin, 2)\n",
        "\n",
        "fig1 = go.Figure()\n",
        "fig1.add_trace(go.Scatter(x=time, y=temp, mode='lines', name='Temperature'))\n",
        "fig1.add_hline(y=target_temp, annotation_text=\"target T : \"+str(target_temp)+\" K\")\n",
        "fig1.update_layout(title='NVT equilibration', xaxis_title='Time (ps)', yaxis_title='Temperature (K)', width=750, height=500)\n",
        "fig1.show()\n",
        "\n",
        "print(\"Check whether the system's apparent temperature stabilizes (flattens).\")\n",
        "print(\"If not, run the above cell again to extend the equilibration run.\")\n",
        "print(\"If yes, proceed to the next cell.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "WZzkMi5eMgqh"
      },
      "outputs": [],
      "source": [
        "#@title 3-2. NPT Equilibration\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "\n",
        "#@markdown Equilibrate the system for n more picoseconds.\n",
        "eq_time = 50 #@param {type:\"slider\", min:0.0, max:1000.0, step:10.0}\n",
        "#@markdown Set the integration step size in femtoseconds.\n",
        "step_size = 2 #@param {type:\"slider\", min:0.1, max:4, step:0.1}\n",
        "#@markdown Set the temperature of the system in **degrees Celsius**.\n",
        "temperature = 25 #@param {type:\"slider\", min:0.0, max:100.0, step:1.0}\n",
        "#@markdown Pressure on the system in bar.\n",
        "pressure = 1 #@param {type:\"slider\", min:0.0, max:100.0, step:1.0}\n",
        "#@markdown Backup the production run's progress to the GoogleDrive every n realtime minutes.\n",
        "#@markdown Set it to smaller values if you are using free Colab sessions.\n",
        "backup_interval = 15 #@param {type:\"slider\", min:5, max:60, step:5}\n",
        "#@markdown Spring constant (in kJ/mol*nm^2) for the positional restraint on heavy atoms\n",
        "positional_restraint = 600 #@param {type:\"slider\", min:0, max:3000, step:100}\n",
        "\n",
        "\n",
        "s = read_settings(work)\n",
        "\n",
        "simulation, stage = recall_simulation(work)\n",
        "\n",
        "assert s['PBC'], 'No periodic boundary condition defined. Cannot run NPT equilibrium.'\n",
        "assert stage != 'start', 'Run NVT equilibration first!'\n",
        "assert stage != 'production', 'Production run already started. You can no longer run this cell.'\n",
        "assert eq_time > 0, 'You set the equilibration time to zero. No more NPT equilibration performing.'\n",
        "\n",
        "if stage == 'nvt':\n",
        "    barostat = MonteCarloBarostat(int(pressure)*bar, s['temperature'])\n",
        "    simulation.system.addForce(barostat)\n",
        "    simulation.context.reinitialize(preserveState=True)\n",
        "    simulation.context.setTime(0)\n",
        "    simulation.context.setStepCount(0)\n",
        "    state = simulation.context.getState(getPositions=True, getVelocities=True)\n",
        "    with open(work+\"npt_step_0.xml\", 'w') as f:\n",
        "        f.write(XmlSerializer.serialize(state))\n",
        "    simulation.saveCheckpoint(work+\"npt.chk\")\n",
        "    print('Now starting the NPT equilibration!')\n",
        "    print(f'Running NPT run for {eq_time} picoseconds.')\n",
        "    stage = 'npt'\n",
        "elif stage == 'npt':\n",
        "    print(f'NPT equilbration has been performed for {simulation.context.getTime()} picoseconds.')\n",
        "    print(f'Running NPT run for {eq_time} more picoseconds.')\n",
        "\n",
        "subprocess.run(f'echo \"\\tTime step (in fs) : {step_size}\" >> {work}settings.txt', shell=True)\n",
        "subprocess.run(f'echo \"\\tTemperature (in Celsius) : {temperature}\" >> {work}settings.txt', shell=True)\n",
        "subprocess.run(f'echo \"\\tPressure (in bar) : {pressure}\" >> {work}settings.txt', shell=True)\n",
        "subprocess.run(f'echo \"\\tRestraint (NPT, kJ/mol*nm^2) : {positional_restraint}\" >> {work}settings.txt', shell=True)\n",
        "\n",
        "stream = SimulationStream()\n",
        "f = open(work+\"npt_log.txt\", 'a')\n",
        "f.close()\n",
        "run_simulation(work, stage, simulation, stream, step_size, temperature,\n",
        "               float(eq_time), 5*picoseconds, int(backup_interval))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "2SEEPsZyqQph"
      },
      "outputs": [],
      "source": [
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'nvt_log.txt'), \"Please run the cell# 3-2 first.\"\n",
        "\n",
        "#@markdown Verify temperature & density convergence\n",
        "time = []\n",
        "temp = []\n",
        "dens = []\n",
        "\n",
        "with open(work+\"npt_log.txt\", 'r') as f:\n",
        "    for line in f.readlines():\n",
        "        if line.startswith(\"#\"):\n",
        "            continue\n",
        "        line = line.strip().split(',')\n",
        "        step = float(line[0])\n",
        "        time.append(step*s['stepsize']/picoseconds)\n",
        "        temp.append(round(float(line[3]),2))\n",
        "        dens.append(round(float(line[5]),5))\n",
        "\n",
        "target_temp = round(s['temperature']/kelvin,2)\n",
        "\n",
        "fig2 = make_subplots(specs=[[{\"secondary_y\":True}]])\n",
        "fig2.add_trace(go.Scatter(x=time, y=temp, mode='lines', name='Temperature'), secondary_y=False)\n",
        "fig2.add_hline(y=target_temp, annotation_text=\"target T : \"+str(target_temp)+\" K\")\n",
        "fig2.add_trace(go.Scatter(x=time, y=dens, mode='lines', name='Density'), secondary_y=True)\n",
        "fig2.update_layout(title='NPT equilibration', width=750, height=500)\n",
        "fig2.update_xaxes(title_text=\"Time (ps)\")\n",
        "fig2.update_yaxes(title_text=\"Temperature (K)\", secondary_y=False)\n",
        "fig2.update_yaxes(title_text=\"Density (g/mL)\", secondary_y=True)\n",
        "fig2.show()\n",
        "\n",
        "print(\"Check whether the system's apparent temperature stabilizes to the desired value.\")\n",
        "print(\"Check also the system's density stabilizes to a value near 1.04 g/mL for physiological conditions.\")\n",
        "print(\"If not, go back to the cell# 3-2.\")\n",
        "print(\"If yes, proceed to the next cell.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "jT4Ii0UGMrjI"
      },
      "outputs": [],
      "source": [
        "#@title 3-3. Production Run\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "\n",
        "#@markdown Run the production MD simulation for n nanoseconds.\n",
        "run_time = 10 #@param {type:\"slider\", min:1, max:500.0, step:1}\n",
        "#@markdown Set the integration step size in femtoseconds.\n",
        "step_size = 2.5 #@param {type:\"slider\", min:0.1, max:4, step:0.1}\n",
        "#@markdown Set the temperature of the system in **degrees Celsius**.\n",
        "temperature = 25 #@param {type:\"slider\", min:0.0, max:100.0, step:1.0}\n",
        "#@markdown Save the trajectory in every n picoseconds.\n",
        "save_interval = 5 #@param {type:\"slider\", min:1, max:50, step:1}\n",
        "#@markdown Backup the production run's progress to the GoogleDrive every n realtime minutes.\n",
        "#@markdown Set it to smaller values if you are using free Colab sessions.\n",
        "backup_interval = 15 #@param {type:\"slider\", min:5, max:60, step:5}\n",
        "\n",
        "s = read_settings(work)\n",
        "\n",
        "simulation, stage = recall_simulation(work)\n",
        "\n",
        "if stage != 'production':\n",
        "    if stage == 'start':\n",
        "        simulation.context.setVelocitiesToTemperature((int(temperature)+273.15)*kelvin)\n",
        "    simulation.context.setTime(0)\n",
        "    simulation.context.setStepCount(0)\n",
        "    state = simulation.context.getState(getPositions=True, getVelocities=True)\n",
        "    with open(work+\"production.xml\", 'w') as f:\n",
        "        f.write(XmlSerializer.serialize(state))\n",
        "    simulation = restore_simulation_from_state(work, 'production')\n",
        "    if s['PBC']:\n",
        "        barostat = MonteCarloBarostat(s['pressure'], s['temperature'])\n",
        "        simulation.system.addForce(barostat)\n",
        "        simulation.context.reinitialize(preserveState=True)\n",
        "\n",
        "    simulation.saveCheckpoint(work+\"production.chk\")\n",
        "    print('Now starting the MD production run!')\n",
        "    print(f'Running for {run_time} nanoseconds.')\n",
        "    stage = 'production'\n",
        "else:\n",
        "    print(f'MD run has been performed for {round(simulation.context.getTime().value_in_unit(nanosecond), 1)} nanoseconds.')\n",
        "    print(f'Running for {run_time} more nanoseconds.')\n",
        "\n",
        "subprocess.run(f'echo \"\\tTime step (in fs) : {step_size}\" >> {work}settings.txt', shell=True)\n",
        "subprocess.run(f'echo \"\\tTemperature (in Celsius) : {temperature}\" >> {work}settings.txt', shell=True)\n",
        "subprocess.run(f'echo \"\\tSave interval (in ps) : {save_interval}\" >> {work}settings.txt', shell=True)\n",
        "stream = SimulationStream()\n",
        "f = open(work+\"production_log.txt\", 'a')\n",
        "f.close()\n",
        "run_simulation(work, stage, simulation, stream, step_size, temperature,\n",
        "               int(run_time)*1000, int(save_interval)*picoseconds, int(backup_interval))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "colab": {
          "background_save": true
        },
        "id": "5CtPtIP2v2K1"
      },
      "outputs": [],
      "source": [
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'minimized.pdb'), \"Please run the cell# 3-1 first.\"\n",
        "\n",
        "#@markdown Check the snapshot of current state\n",
        "view_water_box = False #@param {type:\"boolean\"}\n",
        "s = read_settings(work)\n",
        "\n",
        "view4 = nv.NGLWidget()\n",
        "view4._set_size('750px','500px')\n",
        "view4.add_component(nv.FileStructure(work+\"minimized.pdb\"), defaultRepresentation=False)\n",
        "view4.add_cartoon(\"protein or nucleic\")\n",
        "view4.add_simplified_base(\"nucleic\")\n",
        "view4.add_licorice(\"protein or nucleic or ligand\")\n",
        "if s['PBC'] and view_water_box:\n",
        "    view4.add_point(\"water\")\n",
        "    view4.add_spacefill(\"ion\")\n",
        "state = simulation.context.getState(getPositions=True, enforcePeriodicBox=s['PBC'])\n",
        "view4.set_coordinates({0:state.getPositions(asNumpy=True)*10})\n",
        "view4.update_representation(component=0)\n",
        "view4.center()\n",
        "display(view4)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ktFrmmAnqyp1"
      },
      "source": [
        "## 4. Trajectory Analysis"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "colab": {
          "background_save": true
        },
        "id": "UPwZPr-83OnW"
      },
      "outputs": [],
      "source": [
        "#@title 4-1. Wrap and View Trajectory\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "\n",
        "#@markdown This cell will concatenate the trajectories generated during the Step 3-1, 3-2, and 3-3. <br/>\n",
        "#@markdown Check the box below to produce a 'smoothed' final trajectory. <br/>\n",
        "#@markdown Download your trajectories whose names end with _final.xtc from your GoogleDrive!\n",
        "\n",
        "smooth_trajectory = False #@param {type:\"boolean\"}\n",
        "\n",
        "def wrap_trajectories(work, stage):\n",
        "    \"\"\"\n",
        "    1. Merge the trajectory XTC files into one\n",
        "    2. Wrap around PBC box if necessary\n",
        "    3. Align the trajectory to the first frame\n",
        "    4. Save the processed trajectory to the XTC and PDB files.\n",
        "    \"\"\"\n",
        "    s = read_settings(work)\n",
        "    print(f'Reading the {stage} trajectory files...', end='')\n",
        "    trajs = []\n",
        "    for t in sorted(glob.glob(work+stage+'_*.xtc')):\n",
        "        if t != work+stage+'_final.xtc':\n",
        "            trajs.append(md.load(t, top=work+'minimized.pdb'))\n",
        "    trj = md.join(trajs)\n",
        "    print('done.')\n",
        "\n",
        "    if s['PBC']:\n",
        "        print('Wrapping the trajectory...', end='')\n",
        "        trj.image_molecules(inplace=True, anchor_molecules=trj.topology.guess_anchor_molecules())\n",
        "        print(\"done.\")\n",
        "\n",
        "    trj.save_hdf5(work+stage+'.h5')\n",
        "\n",
        "    print(\"Aligning the trajectory...\", end='')\n",
        "    alphas = trj.topology.select_atom_indices('alpha')\n",
        "    if len(alphas) > 0:\n",
        "        traj2 = trj.superpose(trj, 0, atom_indices=trj.topology.select_atom_indices('alpha'))\n",
        "    else:\n",
        "        nucleic = 'resname A or resname T or resname G or resname C or resname U or resname DA or resname DT or resname DG or resname DC'\n",
        "        traj2 = trj.superpose(trj, 0, atom_indices=trj.topology.select(f'({nucleic}) and (symbol == \"P\" or symbol == \"O\" or symbol == \"N\")'))\n",
        "    print('done.')\n",
        "\n",
        "    print(f'Writing the {stage} trajectory...', end='')\n",
        "\n",
        "    if smooth_trajectory:\n",
        "        filter_width = max(12*picoseconds/s['save interval'], 1)\n",
        "        if filter_width > 3:\n",
        "            traj2.smooth(int(filter_width), order=3, inplace=True)\n",
        "\n",
        "    traj2.save_xtc(work+stage+'_final.xtc')\n",
        "\n",
        "    print('done.')\n",
        "\n",
        "    return\n",
        "\n",
        "\n",
        "to_view = {}\n",
        "if os.path.exists(work+'nvt_0.xtc'):\n",
        "    wrap_trajectories(work, 'nvt')\n",
        "if os.path.exists(work+'npt_0.xtc'):\n",
        "    wrap_trajectories(work, 'npt')\n",
        "if os.path.exists(work+'production_0.xtc'):\n",
        "    wrap_trajectories(work, 'production')\n",
        "\n",
        "if os.path.exists(work+'nvt_final.xtc'):\n",
        "    to_view['nvt'] = md.load(work+'nvt_final.xtc', top=work+'minimized.pdb')\n",
        "if os.path.exists(work+'npt_final.xtc'):\n",
        "    to_view['npt'] = md.load(work+'npt_final.xtc', top=work+'minimized.pdb')\n",
        "if os.path.exists(work+'production_final.xtc'):\n",
        "    to_view['production'] = md.load(work+'production_final.xtc', top=work+'minimized.pdb')\n",
        "\n",
        "assert len(to_view) > 0, \"No trajectory result XTC files found! Did you erase it?\"\n",
        "\n",
        "choice = widgets.Dropdown(options=to_view.keys(), value='production',\n",
        "                          description='trajectory to view',\n",
        "                          style={'description_width': 'initial'},\n",
        "                          layout=widgets.Layout(width='750px'),\n",
        "                          continuous_update=True)\n",
        "\n",
        "def update_choice(change):\n",
        "    with view_traj:\n",
        "        clear_output(wait=True)\n",
        "        view = nv.show_mdtraj(to_view[change.new], defaultRepresentation=False)\n",
        "        view._set_size('750px','500px')\n",
        "        view.add_cartoon()\n",
        "        view.add_simplified_base(\"nucleic\")\n",
        "        view.add_ball_and_stick(\"ligand\")\n",
        "        view.center()\n",
        "        display(view)\n",
        "\n",
        "choice.observe(update_choice, names='value')\n",
        "\n",
        "view_traj = widgets.Output()\n",
        "\n",
        "with view_traj:\n",
        "    view = nv.show_mdtraj(to_view['production'], defaultRepresentation=False)\n",
        "    view._set_size('750px','500px')\n",
        "    view.add_cartoon()\n",
        "    view.add_simplified_base(\"nucleic\")\n",
        "    view.add_ball_and_stick(\"ligand\")\n",
        "    view.center()\n",
        "    display(view)\n",
        "\n",
        "print('Select a trajectory to view in a NGLViewer Widget.')\n",
        "print('Wait for the widget to restart upon selection.')\n",
        "display(choice)\n",
        "display(view_traj)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "colab": {
          "background_save": true
        },
        "id": "p27P31aeNR5t"
      },
      "outputs": [],
      "source": [
        "#@title 4-2. Frame Clustering\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "if 'traj' not in globals():\n",
        "    traj = md.load(work+'production.h5')\n",
        "\n",
        "#@markdown Set the RMSD threshold value (in nanometers) for the trajectory frame clustering. The structures within this threshold will be grouped into the same cluster.\n",
        "rmsd_threshold = 0.15 #@param {type:\"slider\", min:0.05, max:1.0, step:0.05}\n",
        "\n",
        "#@markdown Centroid structures (representative structures) of each clusters will be saved to different frames of \"clustered.pdb\" file.\n",
        "rmsd_matrix = np.zeros((traj.n_frames, traj.n_frames))\n",
        "\n",
        "for i in tqdm(range(traj.n_frames)):\n",
        "    rmsd_matrix[i] = md.rmsd(traj, traj, frame=i, atom_indices=traj.topology.select_atom_indices('heavy'))\n",
        "\n",
        "clustering = AgglomerativeClustering(n_clusters=None, distance_threshold=rmsd_threshold, metric='precomputed', linkage='average')\n",
        "cluster_labels = clustering.fit_predict(rmsd_matrix)\n",
        "\n",
        "n_clusters = len(set(cluster_labels))\n",
        "cluster_sizes = Counter(cluster_labels)\n",
        "sorted_clusters = sorted(cluster_sizes.items(), key=lambda x:x[1], reverse=True)\n",
        "\n",
        "print(f\"Total {n_clusters} clusters found!\")\n",
        "\n",
        "centroids = []\n",
        "for cluster, size in sorted_clusters:\n",
        "    cluster_frames = np.where(cluster_labels == cluster)[0]\n",
        "    centroid_idx = cluster_frames[np.argmin([np.sum(rmsd_matrix[frame, cluster_frames]) for frame in cluster_frames])]\n",
        "    print(f\"Cluser {cluster} (size = {size})'s centroid structure : frame {centroid_idx}\")\n",
        "    centroids.append((cluster, size, centroid_idx))\n",
        "\n",
        "cent_traj = md.join([traj[idx] for _, _, idx in centroids])\n",
        "cent_traj.save_pdb(work+\"clustered.pdb\")\n",
        "\n",
        "view6 = nv.show_mdtraj(cent_traj, defaultRepresentation=False)\n",
        "view6._set_size('750px','500px')\n",
        "view6.add_cartoon()\n",
        "view6.add_licorice()\n",
        "view6.add_simplified_base(\"nucleic\")\n",
        "view6.add_ball_and_stick(\"ligand\")\n",
        "view6.center()\n",
        "view6.player.delay = 3000\n",
        "display(view6)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "8HF0OqTqAbhf"
      },
      "outputs": [],
      "source": [
        "#@title 4-3. Root Mean Squared Deviation\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "if 'traj' not in globals():\n",
        "    traj = md.load(work+'production.h5')\n",
        "\n",
        "#@markdown This cell shows the backbone atoms' RMSD change along the trajectory.\n",
        "\n",
        "nsres = read_non_standard_residues_list(work)\n",
        "rmsd = md.rmsd(traj, traj, 0, atom_indices=traj.topology.select('backbone'))\n",
        "\n",
        "lig_select = widgets.Dropdown(options=['whole structure']+[f\"{a['name']} and rest\" for a in nsres],\n",
        "                              value='whole structure', description='calculate RMSDs for',\n",
        "                              style={'description_width': 'initial'},\n",
        "                              layout=widgets.Layout(width='750px'),\n",
        "                              continuous_update=True)\n",
        "\n",
        "def update_RMSD_chart(change):\n",
        "    with view_chart:\n",
        "        clear_output(wait=True)\n",
        "        if change.new == 'whole structure':\n",
        "            fig = go.Figure()\n",
        "            fig.add_trace(go.Scatter(x=sorted(traj.time/1000), y=rmsd, mode='lines', name='RMSD', connectgaps=False))\n",
        "            fig.update_layout(title='whole structure backbone RMSD', xaxis_title='Time (ns)',\n",
        "                               yaxis_title='RMSD (nm)', width=750, height=500)\n",
        "        else:\n",
        "            lig_name = change.new.split( )[0]\n",
        "            lig_rmsd = md.rmsd(traj, traj, 0, atom_indices=traj.topology.select(f'resname {lig_name}'))\n",
        "            rec_rmsd = md.rmsd(traj, traj, 0, atom_indices=traj.topology.select(f'(resname != {lig_name}) and backbone'))\n",
        "            fig = make_subplots(rows=2, cols=1, subplot_titles=(\"Receptor backbone RMSD\", f\"Ligand {lig_name} all-atom RMSD\"), vertical_spacing=0.2)\n",
        "            fig.add_trace(go.Scatter(x=sorted(traj.time/1000), y=rec_rmsd, mode='lines', name='Receptor RMSD', connectgaps=False), row=1, col=1)\n",
        "            fig.add_trace(go.Scatter(x=sorted(traj.time/1000), y=lig_rmsd, mode='lines', name=f'Ligand {lig_name} RMSD', connectgaps=False), row=2, col=1)\n",
        "            fig.update_xaxes(title='Time (ns)', showticklabels=True, row=1, col=1)\n",
        "            fig.update_xaxes(title='Time (ns)', row=2, col=1)\n",
        "            fig.update_yaxes(title='RMSD (nm)', row=1, col=1)\n",
        "            fig.update_yaxes(title='RMSD (nm)', row=2, col=1)\n",
        "            fig.update_layout(width=750, height=800, showlegend=False)\n",
        "        display(fig)\n",
        "\n",
        "\n",
        "lig_select.observe(update_RMSD_chart, names='value')\n",
        "\n",
        "view_chart = widgets.Output()\n",
        "\n",
        "with view_chart:\n",
        "    fig = go.Figure()\n",
        "    fig.add_trace(go.Scatter(x=sorted(traj.time/1000), y=rmsd, mode='lines', name='RMSD', connectgaps=False))\n",
        "    fig.update_layout(title='whole structure backbone RMSD', xaxis_title='Time (ns)',\n",
        "                       yaxis_title='RMSD (nm)', width=750, height=500)\n",
        "    display(fig)\n",
        "\n",
        "display(lig_select, view_chart)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "usLGlIz-AcSS"
      },
      "outputs": [],
      "source": [
        "#@title 4-4. Radius of Gyration\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "if 'traj' not in globals():\n",
        "    traj = md.load(work+'production.h5')\n",
        "\n",
        "#@markdown This cell shows the radius of gyration of the given protein (approximate size of the globular protein) along the trajectory.\n",
        "\n",
        "rg = md.compute_rg(traj)\n",
        "\n",
        "print('Click autoscale to zoom in.')\n",
        "\n",
        "fig4 = go.Figure()\n",
        "fig4.add_trace(go.Scatter(x=traj.time/1000, y=rg, mode='lines', name='RoG'))\n",
        "fig4.update_yaxes(range=[0, rg.max()*1.1])\n",
        "fig4.update_layout(title='Radius of Gyration', xaxis_title='Time (ns)', yaxis_title='Radius of Gyration (nm)', width=750, height=500)\n",
        "fig4.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "KjAZprHVEdr5"
      },
      "outputs": [],
      "source": [
        "#@title 4-5. Free Energy Landscape\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "#@markdown Shows the free energy landscape calculated from the kernel density of given macrostate.\n",
        "\n",
        "if 'traj' not in globals():\n",
        "    traj = md.load(work+'production.h5')\n",
        "\n",
        "rmsd = md.rmsd(traj, traj, 0)\n",
        "rg = md.compute_rg(traj)\n",
        "s = read_settings(work)\n",
        "X = np.vstack([rmsd, rg]).T\n",
        "\n",
        "# Automatic bandwidth sweep with 5-fold cross-validation\n",
        "bandwidths = np.logspace(-1, 1, 20)\n",
        "grid = GridSearchCV(KernelDensity(kernel='gaussian'), {'bandwidth': bandwidths}, cv=5)\n",
        "grid.fit(X)\n",
        "\n",
        "kde = grid.best_estimator_\n",
        "xi, yi = np.mgrid[rmsd.min():rmsd.max():100j, rg.min():rg.max():100j]\n",
        "xy_sample = np.vstack([xi.ravel(), yi.ravel()]).T\n",
        "z = np.exp(kde.score_samples(xy_sample))\n",
        "zi = z.reshape(xi.shape)\n",
        "\n",
        "Fi = -np.log(zi)\n",
        "Fi -= np.max(Fi) # zero at maximum\n",
        "Fi *= (8.31446261815324*s['temperature'].value_in_unit(kelvin)/1000) # convert from kT to kJ/mol\n",
        "\n",
        "fig5 = go.Figure(data=[go.Surface(z=Fi, x=xi, y=yi, colorbar=dict(title='kJ/mol'),\n",
        "                                  hovertemplate='RMSD: %{x:.3f} nm<br>Rg: %{y:.3f} nm<br>FE: %{z:.1f} kJ/mol<extra></extra>')])\n",
        "\n",
        "fig5.update_layout(title='Relative Free Energy Landscape',\n",
        "                     scene = dict(xaxis_title='RMSD (nm)', yaxis_title='Rg (nm)', zaxis_title='Free Energy (kJ/mol)'),\n",
        "                     width=750, height=750, autosize=True)\n",
        "\n",
        "fig5.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "YgV67PHfAexa"
      },
      "outputs": [],
      "source": [
        "#@title 4-6. Residue-wise Root Mean Square Fluctuation\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "if 'traj' not in globals():\n",
        "    traj = md.load(work+'production.h5')\n",
        "\n",
        "#@markdown This cell shows the all-atom RMSF of each residues over the course of trajectory.\n",
        "\n",
        "#@markdown Residues with higher RMSFs are considered as more flexible.\n",
        "\n",
        "prot_indices = traj.topology.select(\"not water and (mass 11 to 33) and (symbol != 'Na')\")\n",
        "traj2 = traj.superpose(traj, 0, atom_indices=prot_indices)\n",
        "traj2.atom_slice(atom_indices=prot_indices, inplace=True)\n",
        "\n",
        "atom_rmsf = np.sqrt(3*np.mean(np.square(traj2.xyz - np.mean(traj2.xyz, axis=0)), axis=0))\n",
        "\n",
        "res = []\n",
        "res_rmsf = []\n",
        "for c in traj.topology.chains:\n",
        "    chain = c.chain_id\n",
        "    for i, r in enumerate(c.residues):\n",
        "        res.append(f'{\"\" if chain is None else f\"{chain}:\"}{r.name.capitalize()}{i+1}')\n",
        "        atom_idx = [atom.index for atom in r.atoms]\n",
        "        res_rmsf.append(np.mean(atom_rmsf[atom_idx]))\n",
        "\n",
        "fig6 = go.Figure()\n",
        "fig6.add_trace(go.Scatter(x=np.arange(len(res)), y=res_rmsf, mode='lines', name='RMSF', text=res))\n",
        "fig6.update_traces(hovertemplate='Residue: %{text}<br>RMSF: %{y:.3f} nm<extra></extra>')\n",
        "fig6.update_yaxes(range=[0, max(res_rmsf)*1.1])\n",
        "fig6.update_layout(title='Residue-wise heavy atom RMSF', xaxis_title='Residue index', yaxis_title='RMSF (nm)',\n",
        "                   hovermode='x unified', width=750, height=500)\n",
        "fig6.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "_tPxFFanA3mf"
      },
      "outputs": [],
      "source": [
        "#@title 4-7. Ramachandran Map\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "if 'traj' not in globals():\n",
        "    traj = md.load(work+'production.h5')\n",
        "\n",
        "#@markdown This cell shows the Ramachandran map of the given protein over the course of trajectory.\n",
        "\n",
        "#@markdown For large proteins, this may take some time.\n",
        "\n",
        "stride = int(traj.n_frames/50)\n",
        "\n",
        "if stride < 2:\n",
        "    traj2 = traj\n",
        "    stride = 1\n",
        "else:\n",
        "    traj2 = traj[::stride]\n",
        "\n",
        "s = read_settings(work)\n",
        "\n",
        "phi = md.compute_phi(traj2, periodic=s['PBC'])[1]\n",
        "psi = md.compute_psi(traj2, periodic=s['PBC'])[1]\n",
        "\n",
        "res = []\n",
        "for c in traj.topology.chains:\n",
        "    chain = c.chain_id\n",
        "    for i, r in enumerate(c.residues):\n",
        "        res.append(f'{\"\" if chain is None else f\"{chain}:\"}{r.name.capitalize()}{i+1}')\n",
        "\n",
        "fig8 = go.Figure()\n",
        "colors = np.linspace(0, traj.n_frames*s['save interval'].value_in_unit(nanosecond), traj2.n_frames)\n",
        "\n",
        "fig8.add_trace(go.Scatter(x=phi.flatten(), y=psi.flatten(), mode='markers', marker=dict(color=np.repeat(colors, phi.shape[1]), colorscale='Viridis', colorbar=dict(title='Time (ns)'), showscale=True),\n",
        "                          text=[f'Time: {(i//phi.shape[1])*stride*s[\"save interval\"]}<br>Residue: {res[i%phi.shape[1]]}<br>Phi: {phi[i//phi.shape[1], i%phi.shape[1]]:.2f}<br>Psi: {psi[i//phi.shape[1], i%phi.shape[1]]:.2f}'\n",
        "                                for i in range(phi.size)], hoverinfo='text'))\n",
        "\n",
        "fig8.update_layout(title='Time-dependent Ramachandran Map', xaxis_title='Phi (radians)', yaxis_title='Psi (radians)', xaxis_range=[-np.pi, np.pi], yaxis_range=[-np.pi, np.pi], width=750, height=500)\n",
        "fig8.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "dCZiVq5DBAn9"
      },
      "outputs": [],
      "source": [
        "#@title 4-8. Solvent Accessible Surface Area\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "if 'traj' not in globals():\n",
        "    traj = md.load(work+'production.h5')\n",
        "\n",
        "#@markdown This cell shows the change in the surface area of the given residue.\n",
        "\n",
        "#@markdown Not recommended for free Colab sessions.\n",
        "\n",
        "#@markdown Type the index (starting from 1) of the residue you want to analyze its SASA.\n",
        "\n",
        "residue_index = \"140\" #@param {type:\"string\"}\n",
        "res_idx = int(residue_index)-1\n",
        "\n",
        "assert res_idx < traj.topology.n_residues, \"Invalid residue index!\"\n",
        "\n",
        "sasa = md.shrake_rupley(traj, mode='residue')\n",
        "\n",
        "for c in traj.topology.chains:\n",
        "    chain = c.chain_id\n",
        "    for i, r in enumerate(c.residues):\n",
        "        if r.index == res_idx:\n",
        "            name = f'{\"\" if chain is None else f\"{chain}:\"}{r.name.capitalize()}{i+1}'\n",
        "            break\n",
        "\n",
        "fig9 = go.Figure()\n",
        "fig9.add_trace(go.Scatter(x=traj.time/1000, y=sasa[:,res_idx], mode='lines', name='SASA'))\n",
        "fig9.update_layout(title=f'Solvent Accessible Surface Area of the residue {name}',\n",
        "                   xaxis_title='Time (ns)', yaxis_title='SASA (nm^2)', width=750, height=500)\n",
        "fig9.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "Ab0Le5IaS8BG"
      },
      "outputs": [],
      "source": [
        "#@title 4-9. Inter-residue hydrogen bond analysis\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "traj = md.load(work+'production.h5')\n",
        "\n",
        "residue_1 = \"118\" #@param {type:\"string\"}\n",
        "residue_2 = \"\" #@param {type:\"string\"}\n",
        "\n",
        "residue_1 = int(residue_1) -1\n",
        "if residue_2 != \"\":\n",
        "    water_flag = False\n",
        "    residue_2 = int(residue_2) -1\n",
        "else:\n",
        "    water_flag = True\n",
        "\n",
        "assert residue_1 != residue_2, \"Same residue indices entered!\"\n",
        "\n",
        "s = read_settings(work)\n",
        "\n",
        "topol = traj.topology.to_openmm()\n",
        "\n",
        "donors = []\n",
        "acceptors = []\n",
        "\n",
        "for a in topol.atoms():\n",
        "    if a.element.symbol in ['N', 'O', 'F']:\n",
        "        if a.residue.index == residue_1:\n",
        "            donors.append(a.index)\n",
        "        elif a.residue.index == residue_2:\n",
        "            acceptors.append(a.index)\n",
        "        elif water_flag and a.residue.name == 'HOH':\n",
        "            acceptors.append(a.index)\n",
        "\n",
        "donor_Hs = {}\n",
        "acceptor_Hs = {}\n",
        "\n",
        "for b in topol.bonds():\n",
        "    if b[0].index in donors and b[1].element.symbol == 'H':\n",
        "        donor_Hs[b[1].index] = b[0].index\n",
        "    elif b[1].index in donors and b[0].element.symbol == 'H':\n",
        "        donor_Hs[b[0].index] = b[1].index\n",
        "    elif b[0].index in acceptors and b[1].element.symbol == 'H':\n",
        "        acceptor_Hs[b[1].index] = b[0].index\n",
        "    elif b[1].index in acceptors and b[0].element.symbol == 'H':\n",
        "        acceptor_Hs[b[0].index] = b[1].index\n",
        "\n",
        "H_bonds = []\n",
        "\n",
        "for key, value in donor_Hs.items():\n",
        "    for a in acceptors:\n",
        "        H_bonds.append([value, key, a])\n",
        "for key, value in acceptor_Hs.items():\n",
        "    for d in donors:\n",
        "        H_bonds.append([value, key, d])\n",
        "\n",
        "assert len(H_bonds) >0, \"There are no H-bond donor/acceptors in the residue!\"\n",
        "\n",
        "angles = md.compute_angles(traj, np.array(H_bonds), s['PBC'], True)\n",
        "distances = md.compute_distances(traj, np.array([[h[1], h[2]] for h in H_bonds]), s['PBC'], True)\n",
        "\n",
        "hbonds = np.sum(np.where(angles > 2*np.pi/3, 1, 0)*np.where(distances < 0.25, 1, 0), axis=1)\n",
        "\n",
        "for c in traj.topology.chains:\n",
        "    chain = c.chain_id\n",
        "    for i, r in enumerate(c.residues):\n",
        "        if r.index == residue_1:\n",
        "            name1 = f'{\"\" if chain is None else f\"{chain}:\"}{r.name.capitalize()}{i+1}'\n",
        "        elif not water_flag and r.index == residue_2:\n",
        "            name2 = f'{\"\" if chain is None else f\"{chain}:\"}{r.name.capitalize()}{i+1}'\n",
        "        else:\n",
        "            continue\n",
        "\n",
        "fig10 = go.Figure()\n",
        "fig10.add_trace(go.Scatter(x=traj.time/1000, y=hbonds, mode='lines', name='H-bond'))\n",
        "fig10.update_layout(xaxis_title='Time (ns)', yaxis_title='Number of H-bonds', width=750, height=500)\n",
        "if water_flag:\n",
        "    fig10.update_layout(title=f'Number of Hydrogen bonds between {name1} and water molecules')\n",
        "else:\n",
        "    fig10.update_layout(title=f'Number of Hydrogen Bonds between {name1} and {name2}')\n",
        "fig10.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "2c8tedqCBDbN"
      },
      "outputs": [],
      "source": [
        "#@title 4-10. Secondary Structure Analysis using DSSP\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "if 'traj' not in globals():\n",
        "    traj = md.load(work+'production.h5')\n",
        "\n",
        "#@markdown This cell shows the secondary structure of each residue over the course of trajectory.\n",
        "\n",
        "#@markdown Not recommended for free Colab sessions, since it takes up a lot of memory.\n",
        "\n",
        "dssp = md.compute_dssp(traj)\n",
        "dssp_map = {'H':0, 'E':1, 'C':2}\n",
        "dssp_num = np.array([[dssp_map.get(ss,2) for ss in frame] for frame in dssp])\n",
        "\n",
        "s = read_settings(work)\n",
        "\n",
        "fig11 = go.Figure(data=go.Heatmap(z=dssp_num.T, x=traj.time/1000, y=np.arange(traj.n_residues),\n",
        "                                 colorscale=[[0,'red'],[0.33, 'red'], [0.33, 'yellow'], [0.66, 'yellow'], [0.66, 'blue'], [1, 'blue']],\n",
        "                                 colorbar=dict(tickvals=[0,1,2],ticktext=['Helix', 'Sheet', 'Coil'])))\n",
        "fig11.update_layout(title='Time-dependent Secondary Structure (DSSP)', xaxis_title='Time (ns)', yaxis_title='Residue index', width=750, height=1000)\n",
        "fig11.data[0].hovertext = [[f'Time : {i*s[\"save interval\"]}<br>Residue: {j}<br>SS: {dssp[i][j]}' for i in range(traj.n_frames)] for j in range(traj.n_residues)]\n",
        "fig11.data[0].hoverinfo = 'text'\n",
        "fig11.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "V0qemYvRBF5e"
      },
      "outputs": [],
      "source": [
        "#@title 4-11. Dynamic Cross-Correlation Matrix\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "if 'traj' not in globals():\n",
        "    traj = md.load(work+'production.h5')\n",
        "\n",
        "#@markdown This cell shows the correlation between the movements of alpha carbons of each residue.\n",
        "#@markdown When the correlation value approaches +1 (blue), it means the pair of residues tend to move in the same direction.\n",
        "#@markdown When the value approaches -1 (red), it means the pair of residues tend to move in the opposite directions.\n",
        "#@markdown When the value approaches 0 (white), it means the pair of residues move independently from each other.\n",
        "\n",
        "ca_idx = traj.topology.select_atom_indices('alpha')\n",
        "mean_pos = np.mean(traj.xyz[:, ca_idx, :], axis=0)\n",
        "fluct = traj.xyz[:, ca_idx, :] - mean_pos\n",
        "\n",
        "dccm = np.zeros((traj.n_residues, traj.n_residues))\n",
        "\n",
        "for i in range(len(ca_idx)):\n",
        "    for j in range(len(ca_idx)):\n",
        "        numerator = np.mean(np.sum(fluct[:,i,:]*fluct[:,j,:], axis=1))\n",
        "        denominator = np.sqrt(np.mean(np.sum(fluct[:,i,:]**2, axis=1))*np.mean(np.sum(fluct[:,j,:]**2, axis=1)))\n",
        "        dccm[i,j] = numerator/denominator\n",
        "\n",
        "fig12 = go.Figure(data=go.Heatmap(z=dccm, colorscale='RdBu', zmid=0, colorbar=dict(title='Correlation')))\n",
        "fig12.update_layout(title='Dynamic Cross-Correlation Matrix', xaxis_title='Residue index', yaxis_title='Residue index', width=750, height=750)\n",
        "fig12.data[0].hovertext = [[f'Residue i: {i+1}<br>Residue j: {j+1}<br>Correlation: {dccm[i,j]:.2f}' for j in range(dccm.shape[1])] for i in range(dccm.shape[0])]\n",
        "fig12.data[0].hoverinfo = 'text'\n",
        "fig12.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EBe114g84Lq9"
      },
      "source": [
        "### 4-12. Principal Component Analysis"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "PgPSAoZ2Apnr"
      },
      "outputs": [],
      "source": [
        "#@title 2D Principal Component Analysis\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "if 'traj' not in globals():\n",
        "    traj = md.load(work+'production.h5')\n",
        "\n",
        "#@markdown This cell extracts the collective motions of atomic coordinates and demonstrates them as a pair of orthogonal eigenvectors called principal components. The percentage values in the parentheses describe the eigenvalue of each component, which show the explainability of each component in the motion of atoms over the course of trajectory.\n",
        "\n",
        "prot_indices = traj.topology.select(\"not water and (mass 11 to 33) and (symbol != 'Na')\")\n",
        "traj2 = traj.superpose(traj, 0, atom_indices=prot_indices)\n",
        "traj2.atom_slice(atom_indices=prot_indices, inplace=True)\n",
        "pca = PCA(n_components=2)\n",
        "reduced_cart = pca.fit_transform(traj2.xyz.reshape(traj2.n_frames, traj2.n_atoms*3))\n",
        "var_explained = pca.explained_variance_ratio_*100\n",
        "\n",
        "s = read_settings(work)\n",
        "\n",
        "fig13 = go.Figure()\n",
        "fig13.add_trace(go.Scatter(x=reduced_cart[:,0], y=reduced_cart[:,1], mode='markers',\n",
        "                          marker=dict(size=5, color=np.arange(len(reduced_cart))*s[\"save interval\"].value_in_unit(nanosecond), colorscale='Viridis', colorbar=dict(title='Time (ns)'), showscale=True),\n",
        "                          text=[f'Time: {i*s[\"save interval\"]}' for i in range(len(reduced_cart))], hoverinfo='text', name='PCA'))\n",
        "fig13.update_layout(title='Two Dimensional Principal Component Analysis', xaxis_title=f'PC1 ({var_explained[0]:.2f}%)', yaxis_title=f'PC2 ({var_explained[1]:.2f}%)', width=750, height=500)\n",
        "fig13.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "Kov9UUH6AsEX"
      },
      "outputs": [],
      "source": [
        "#@title 3D Principal Component Analysis\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "if 'traj' not in globals():\n",
        "    traj = md.load(work+'production.h5')\n",
        "\n",
        "#@markdown SImilar to the above cell that performed a 2D PCA, this cell performs the 3D PCA.\n",
        "prot_indices = traj.topology.select(\"not water and (mass 11 to 33) and (symbol != 'Na')\")\n",
        "traj2 = traj.superpose(traj, 0, atom_indices=prot_indices)\n",
        "traj2.atom_slice(atom_indices=prot_indices, inplace=True)\n",
        "pca = PCA(n_components=3)\n",
        "reduced_cart = pca.fit_transform(traj2.xyz.reshape(traj2.n_frames, traj2.n_atoms*3))\n",
        "var_explained = pca.explained_variance_ratio_*100\n",
        "\n",
        "s = read_settings(work)\n",
        "s['save interval'] = 10*picosecond\n",
        "\n",
        "fig14 = go.Figure()\n",
        "fig14.add_trace(go.Scatter3d(x=reduced_cart[:,0], y=reduced_cart[:,1], z=reduced_cart[:,2], mode='markers',\n",
        "                          marker=dict(size=5, color=s[\"save interval\"].value_in_unit(nanosecond)*np.arange(len(reduced_cart)), colorscale='Viridis', opacity=0.8, colorbar=dict(title='Time (ns)'), showscale=True),\n",
        "                          text=[f'Time: {i*s[\"save interval\"]}' for i in range(len(reduced_cart))], hoverinfo='text', name='PCA'))\n",
        "fig14.update_layout(title='Three Dimensional Principal Component Analysis', scene=dict(xaxis_title=f'PC1 ({var_explained[0]:.2f}%)', yaxis_title=f'PC2 ({var_explained[1]:.2f}%)', zaxis_title=f'PC3 ({var_explained[2]:.2f}%)'), width=750, height=750)\n",
        "fig14.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "f_jIQg9KAwI-"
      },
      "outputs": [],
      "source": [
        "#@title Visualization of Principal Components\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'production.h5'), \"Run the cell# 4-1 first to wrap the trajectory.\"\n",
        "\n",
        "if 'traj' not in globals():\n",
        "    traj = md.load(work+'production.h5')\n",
        "\n",
        "#@markdown This cell animates each principal component's motion in MDTraj trajectory.\n",
        "\n",
        "#@markdown Set index of the principal component to visualize.\n",
        "component_to_view = \"1\" #@param [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n",
        "#@markdown Set the scale of the motion. Set larger values for more exaggerated motions.\n",
        "scale = 3 #@param {type:\"slider\", min:1, max:10, step:1}\n",
        "\n",
        "nsres = read_non_standard_residues_list(work)\n",
        "nsres_to_view = \"\"\n",
        "for i, r in enumerate(nsres):\n",
        "    nsres_to_view += f\"(resname {r['name']})\"\n",
        "    if i < len(nsres)-1:\n",
        "        nsres_to_view += \" or \"\n",
        "\n",
        "ligand_indices = traj.topology.select(f'{nsres_to_view}')\n",
        "prot_indices = traj.topology.select(\"not water and (mass 11 to 33) and (symbol != 'Na')\")\n",
        "view_indices = np.array(sorted(set(list(ligand_indices)+list(prot_indices))))\n",
        "traj2 = traj.superpose(traj, 0, atom_indices=prot_indices)\n",
        "traj2.atom_slice(atom_indices=view_indices, inplace=True)\n",
        "coords = traj2.xyz.reshape(traj2.n_frames, -1)\n",
        "\n",
        "pca = PCA()\n",
        "pca_results = pca.fit_transform(coords)\n",
        "top_pcs = pca.components_[:10]\n",
        "\n",
        "pc_trajs = top_pcs.reshape(10, traj2.n_atoms, 3)\n",
        "sine_wave = np.sin(np.linspace(0, 2*np.pi, num=50))\n",
        "\n",
        "pc_traj = md.Trajectory(np.zeros((50, traj2.n_atoms, 3)), traj2.topology)\n",
        "\n",
        "for i in range(50):\n",
        "    pc_traj.xyz[i] = traj2.xyz[0] + scale*sine_wave[i]*pc_trajs[int(component_to_view)-1]\n",
        "\n",
        "view6 = nv.show_mdtraj(pc_traj, defaultRepresentation=False)\n",
        "view6._set_size('750px','500px')\n",
        "view6.add_cartoon()\n",
        "view6.add_simplified_base(\"nucleic\")\n",
        "view6.add_ball_and_stick(\"ligand\")\n",
        "view6.center()\n",
        "view6.player.delay = 500\n",
        "display(view6)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1EGMmauoHQmT"
      },
      "source": [
        "## 5. Intermolecular Interaction Analysis"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "colab": {
          "background_save": true
        },
        "id": "QFxU3Eqx3XlG",
        "outputId": "4f39c475-a295-4091-cada-22575c20f661"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/site-packages/mdtraj/core/trajectory.py:441: UserWarning:\n",
            "\n",
            "top= kwargs ignored since this file parser does not support it\n",
            "\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "9dbefaace74d4f1f81db71e7a5942b8e",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "NGLWidget()"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Wait up to 1 min for the NGLWidget to restart after selecting a ligand. \n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "e811e1db3bbd4348b21b60dcc1ef9e53",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Dropdown(description='Ligand : ', options=('none', 'PI4:B:1'), value='none')"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "8a216f95472f45259393eb1481785454",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Output()"
            ]
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "#@title 5-1. Visualizing protein-ligand interactions by PLIP\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert os.path.exists(work+'starting_structure.pdb'), \"starting_structure.pdb file not found!\"\n",
        "assert os.path.exists(work+'production.h5'), \"Result trajectory not found! Run cell# 4-1 first.\"\n",
        "assert os.path.exists(work+'clustered.pdb'), \"Run cell# 4-2 first.\"\n",
        "\n",
        "traj = md.load(work+'production.h5')\n",
        "\n",
        "#@markdown Each interaction type is shown in different color. <br/>\n",
        "#@markdown * H-bonds : Red\n",
        "#@markdown * Hydrophobic : grey\n",
        "#@markdown * Salt bridge : yellow\n",
        "#@markdown * Water bridge : cyan\n",
        "#@markdown * Pi-pi stacking : blue\n",
        "#@markdown * Pi-cation : purple\n",
        "#@markdown * Halogen bonds : green\n",
        "#@markdown * Metal coordination : emerald\n",
        "\n",
        "clusterPDB = PDBComplex()\n",
        "clusterPDB.load_pdb(work+'clustered.pdb')\n",
        "clusterPDB.analyze()\n",
        "\n",
        "ligands = {}\n",
        "for ligand in clusterPDB.ligands:\n",
        "    clusterPDB.characterize_complex(ligand)\n",
        "\n",
        "for key, value in sorted(clusterPDB.interaction_sets.items()):\n",
        "    ligands[key] = BindingSiteReport(value)\n",
        "\n",
        "interaction_types = ['hbond', 'hydrophobic', 'saltbridge', 'waterbridge', 'pistacking', 'pication', 'halogen', 'metal']\n",
        "color = [(1,0,0), (0.5,0.5,0.5), (1,1,0), (0,1,1), (0,0,1), (1,0,1), (0,1,0), (0.9,0.5,0.9)]\n",
        "\n",
        "view_interaction = widgets.Output()\n",
        "\n",
        "with view_interaction:\n",
        "    view = nv.NGLWidget()\n",
        "    view.add_component(nv.FileStructure(work+'clustered.pdb'), defaultRepresentation=False)\n",
        "    view._set_size('750px','500px')\n",
        "    view.add_cartoon()\n",
        "    view.add_simplified_base(\"nucleic\")\n",
        "    view.add_licorice(\"ligand\")\n",
        "    view.center()\n",
        "    display(view)\n",
        "\n",
        "def center_ligand(change): # callback function for the update\n",
        "    with view_interaction:\n",
        "        clear_output(wait=True)\n",
        "        view = nv.NGLWidget()\n",
        "        view.add_component(nv.FileStructure(work+'clustered.pdb'), defaultRepresentation=False)\n",
        "        view._set_size('750px','500px')\n",
        "        view.add_cartoon()\n",
        "        view.add_simplified_base(\"nucleic\")\n",
        "        view.add_licorice(\"ligand\")\n",
        "        if change.new == 'none':\n",
        "            view.center()\n",
        "        else:\n",
        "            intres = []\n",
        "            for i, inttype in enumerate(interaction_types):\n",
        "                intdata = getattr(ligands[change.new], inttype+'_info')\n",
        "                for interaction in intdata:\n",
        "                    intres.append(f'({interaction[0]} and {interaction[1]} and :{interaction[2]})')\n",
        "                    view.shape.add_cylinder(interaction[-2], interaction[-1], color[i], [0.05], inttype)\n",
        "            view.add_licorice(\" or \".join(intres))\n",
        "            resdata = change.new.split(':')\n",
        "            view.center(f'{resdata[2]} and :{resdata[1]} and {resdata[0]}')\n",
        "        display(view)\n",
        "\n",
        "print('Wait up to 1 min for the NGLWidget to restart after selecting a ligand. ')\n",
        "\n",
        "if len(ligands) > 0:\n",
        "    select_lig = widgets.Dropdown(options=['none']+list(ligands.keys()), value='none', description='Ligand : ', continuous_update=True)\n",
        "    select_lig.observe(center_ligand, names='value')\n",
        "    display(select_lig, view_interaction)\n",
        "else:\n",
        "    display(view_interaction)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "K0ftSkx5Kb9-"
      },
      "outputs": [],
      "source": [
        "#@title 5-2. Prepare trajectories for MM/GBSA\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "#@markdown Enter the chain ID(s) of ligand and receptor. Separate multiple chains with commas. <br/>\n",
        "#@markdown You can enter only ligand chain ID to make every other chain as receptor.\n",
        "ligand_chain = \"C\" #@param {type:\"string\"}\n",
        "receptor_chain = \"\" #@param {type:\"string\"}\n",
        "\n",
        "#@markdown To discard the starting fraction of the trajectory, set this value larger then 0.\n",
        "skip_initial_fraction = 0 #@param {type:\"slider\", min:0, max:0.9, step:0.1}\n",
        "#@markdown Only calculate every N frames.\n",
        "stride = 1  #@param {type:\"slider\", min:1, max:20, step:1}\n",
        "\n",
        "pdb = PDBFile(work+'starting_structure.pdb')\n",
        "\n",
        "lig_a = []\n",
        "rec_a = []\n",
        "com_a = []\n",
        "elements = []\n",
        "\n",
        "lig_present = False\n",
        "rec_present = False\n",
        "lig_r = []\n",
        "rec_r = []\n",
        "\n",
        "for a in pdb.topology.atoms():\n",
        "    if a.residue.chain.id in ligand_chain.split(','):\n",
        "        lig_present = True\n",
        "        lig_r.append(a.residue.index)\n",
        "        lig_a.append(a.index)\n",
        "    elif receptor_chain == \"\" or a.residue.chain.id in receptor_chain.split(','):\n",
        "        rec_present = True\n",
        "        rec_r.append(a.residue.index)\n",
        "        rec_a.append(a.index)\n",
        "    else:\n",
        "        continue\n",
        "    com_a.append(a.index)\n",
        "    elements.append(a.element.symbol)\n",
        "\n",
        "for e in set(elements):\n",
        "    assert e in ['H', 'C', 'N', 'O', 'F', 'P', 'S', 'Si', 'Cl'], f'No bondi parameter found for element {e}!'\n",
        "assert lig_present, f'No ligand molecule with the chain ID among {ligand_chain}!'\n",
        "assert rec_present, f'No receptor molecule with the chain ID among {receptor_chain}!'\n",
        "\n",
        "\n",
        "s = read_settings(work)\n",
        "ff, wm = determine_forcefield(s['forcefield'], s['watermodel'])\n",
        "\n",
        "nsres = read_non_standard_residues_list(work)\n",
        "smffs = []\n",
        "for res in nsres:\n",
        "    if res['lig']:\n",
        "        smffs.append(res['ff'])\n",
        "\n",
        "esp_flag = False\n",
        "if 'espaloma-0.3.2' in set(smffs):\n",
        "    esp_flag = True\n",
        "\n",
        "if esp_flag:\n",
        "    print('You need to install the Full package!')"
      ]
    },
    {
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      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "colab": {
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        "id": "SB6-5YsX5KYs",
        "outputId": "8b730f16-b21c-40bc-b8a4-d3edb3828135"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Running analysis on ligand system :\n"
          ]
        },
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              "  0%|          | 0/1800 [00:00<?, ?it/s]"
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            "Running analysis on receptor system :\n"
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            "Running analysis on complex system :\n"
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        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Interaction Energy    : -229.45 +/- 72.19 kJ/mol\n",
            "Polar contribution    : -212.64 +/- 68.32 kJ/mol\n",
            "Nonpolar contribution :  -16.81 +/-  6.14 kJ/mol\n",
            "GBSA Solvation Energy : +180.05 +/- 70.48 kJ/mol\n",
            "Binding Enthalpy      :  -49.40 +/- 100.89 kJ/mol\n"
          ]
        }
      ],
      "source": [
        "#@title 5-3. Running MM/GBSA\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert 'ff' in globals(), \"Please run the cell# 5-2 first.\"\n",
        "\n",
        "#@markdown Select a Generalized Born model to use.\n",
        "GB_model = \"GBn2 (igb=8)\" #@param [\"HCT (igb=1)\", \"OBC1 (igb=2)\", \"OBC2 (igb=5)\", \"GBn (igb=7)\", \"GBn2 (igb=8)\"]\n",
        "#@markdown Set the dielectric constants of solvent and solute.<br/>\n",
        "#@markdown Recommended values are 78 for the solvent and 2~5 for the solute. <br/>\n",
        "#@markdown You may increase/decrease the solute dielectric constant to tone down/up the interaction energy.\n",
        "solvent_dielectric = 78 #@param {type:\"slider\", min:1, max:80, step:1}\n",
        "solute_dielectric = 5 #@param {type:\"slider\", min:1, max:80, step:1}\n",
        "\n",
        "assert solvent_dielectric > solute_dielectric, \"Solvent dielectric constant must be larger than Solute's!\"\n",
        "\n",
        "gaff_flag = False\n",
        "smirnoff_flag = False\n",
        "esp_flag = False\n",
        "\n",
        "gaff = []\n",
        "smirnoff = []\n",
        "esp = []\n",
        "for res in nsres:\n",
        "    if res['ff'] == 'GAFF-2.11':\n",
        "        gaff_flag = True\n",
        "        with open(f'{work}{res[\"name\"]}.json', 'r') as f:\n",
        "            gaff.append(Molecule.from_json(f.read()))\n",
        "    elif res['ff'] == 'Sage-2.2.1':\n",
        "        smirnoff_flag = True\n",
        "        with open(f'{work}{res[\"name\"]}.json', 'r') as f:\n",
        "            smirnoff.append(Molecule.from_json(f.read()))\n",
        "    elif res['ff'] == 'espaloma-0.3.2':\n",
        "        esp_flag = True\n",
        "        with open(f'{work}{res[\"name\"]}.json', 'r') as f:\n",
        "            esp.append(Molecule.from_json(f.read()))\n",
        "\n",
        "if gaff_flag:\n",
        "    g = GAFFTemplateGenerator(molecules=gaff)\n",
        "    ff.registerTemplateGenerator(g.generator)\n",
        "if smirnoff_flag:\n",
        "    g = SMIRNOFFTemplateGenerator(molecules=smirnoff)\n",
        "    ff.registerTemplateGenerator(g.generator)\n",
        "if esp_flag:\n",
        "    g = EspalomaTemplateGenerator(molecules=esp)\n",
        "    ff.registerTemplateGenerator(g.generator)\n",
        "\n",
        "def create_GBSA_system(trajectory, forcefield, fftype, eps_solv, eps_solut, kappa):\n",
        "\n",
        "    top = trajectory.topology.to_openmm(trajectory)\n",
        "\n",
        "    for chain in top.chains():\n",
        "        a1 = None\n",
        "        a2 = None\n",
        "        for i, res in enumerate(chain.residues()):\n",
        "            if i == 0 and res.name == 'PRO':\n",
        "                for atom in res.atoms():\n",
        "                    if atom.name == 'H2':\n",
        "                        a2 = atom\n",
        "                    elif atom.name == 'N':\n",
        "                        a1 = atom\n",
        "                    else:\n",
        "                        continue\n",
        "            else:\n",
        "                break\n",
        "        if a1 is not None and a2 is not None:\n",
        "            top.addBond(a1, a2)\n",
        "\n",
        "    system = forcefield.createSystem(top, nonbondedMethod=NoCutoff)\n",
        "\n",
        "    charges = []\n",
        "\n",
        "    for force in system.getForces():\n",
        "        if isinstance(force, NonbondedForce):\n",
        "            force.setForceGroup(1)\n",
        "            force.addGlobalParameter(f'coul_scale', 1)\n",
        "            force.addGlobalParameter(f'lj_scale', 1)\n",
        "            for i in range(force.getNumParticles()):\n",
        "                q, s, e = force.getParticleParameters(i)\n",
        "                charges.append(q)\n",
        "                force.setParticleParameters(i, 0, s, 0)\n",
        "                force.addParticleParameterOffset(f'coul_scale', i, q, 0, 0)\n",
        "                force.addParticleParameterOffset(f'lj_scale', i, 0, 0, e)\n",
        "            for i in range(force.getNumExceptions()):\n",
        "                p1, p2, q_p, s, e = force.getExceptionParameters(i)\n",
        "                force.setExceptionParameters(i, p1, p2, 0, s, 0)\n",
        "\n",
        "        elif isinstance(force, CustomNonbondedForce):\n",
        "            force.setForceGroup(2)\n",
        "            for i in range(force.getNumExceptions()):\n",
        "                p1, p2, q_p, s, e = force.getExceptionParameters(i)\n",
        "                force.setExceptionParameters(i, p1, p2, 0, s, 0)\n",
        "        else:\n",
        "            force.setForceGroup(0)\n",
        "\n",
        "    args = {'soluteDielectric': eps_solut, 'solventDielectric': eps_solv,\n",
        "            'kappa': kappa, 'SA':'ACE'}\n",
        "\n",
        "    if fftype == \"HCT (igb=1)\":\n",
        "        gb = customgbforces.GBSAHCTForce(**args)\n",
        "        params = customgbforces.GBSAHCTForce.getStandardParameters(top)\n",
        "    elif fftype == \"OBC1 (igb=2)\":\n",
        "        gb = customgbforces.GBSAOBC1Force(**args)\n",
        "        params = customgbforces.GBSAOBC1Force.getStandardParameters(top)\n",
        "    elif fftype == \"OBC2 (igb=5)\":\n",
        "        gb = customgbforces.GBSAOBC2Force(**args)\n",
        "        params = customgbforces.GBSAOBC2Force.getStandardParameters(top)\n",
        "    elif fftype == \"GBn (igb=7)\":\n",
        "        gb = customgbforces.GBSAGBnForce(**args)\n",
        "        parmas = customgbforces.GBSAGBnForce.getStandardParameters(top)\n",
        "    elif fftype == \"GBn2 (igb=8)\":\n",
        "        gb = customgbforces.GBSAGBn2Force(**args)\n",
        "        params = customgbforces.GBSAGBn2Force.getStandardParameters(top)\n",
        "    else:\n",
        "        raise ValueError\n",
        "\n",
        "    gb.setForceGroup(3)\n",
        "    for i, p in enumerate(params):\n",
        "        if fftype in ['GBn (igb=7)', 'GBn2 (igb=8)']:\n",
        "            gb.addParticle([charges[i], p[0], p[1], p[2], p[3], p[4]])\n",
        "        else:\n",
        "            gb.addParticle([charges[i], p[0], p[1]])\n",
        "\n",
        "    gb.finalize()\n",
        "    gb.setNonbondedMethod(CustomNonbondedForce.NoCutoff)\n",
        "    system.addForce(gb)\n",
        "\n",
        "    return system\n",
        "\n",
        "\n",
        "def calculate_energies(work, name, trajectory, forcefield, fftype, eps_solv, eps_solut):\n",
        "\n",
        "    print(f'Running analysis on {name} system :')\n",
        "\n",
        "    s = read_settings(work)\n",
        "    temperature = s['temperature']/kelvin\n",
        "    ion_conc = s['ionic strength']/molar\n",
        "    kappa = 367.434915*sqrt(float(ion_conc)/78.5/(temperature))\n",
        "\n",
        "    system = create_GBSA_system(trajectory, forcefield, fftype, eps_solv, eps_solut, kappa)\n",
        "    integrator = VerletIntegrator(1*femtosecond)\n",
        "    context = Context(system, integrator)\n",
        "\n",
        "    coulombic = []\n",
        "    LJ = []\n",
        "    GBSA = []\n",
        "\n",
        "    for i in tqdm(range(trajectory.n_frames)):\n",
        "        context.setPositions(trajectory.openmm_positions(i))\n",
        "        context.setParameter('coul_scale', eps_solut**(-1/2))\n",
        "        context.setParameter('lj_scale', 0)\n",
        "        coulombic.append(context.getState(getEnergy=True, groups={1}).getPotentialEnergy().value_in_unit(kilojoules_per_mole))\n",
        "        context.setParameter('coul_scale', 0)\n",
        "        context.setParameter('lj_scale', 1/eps_solut)\n",
        "        LJ.append(context.getState(getEnergy=True, groups={1,2}).getPotentialEnergy().value_in_unit(kilojoules_per_mole))\n",
        "        GBSA.append(context.getState(getEnergy=True, groups={3}).getPotentialEnergy().value_in_unit(kilojoules_per_mole))\n",
        "\n",
        "    return np.array(coulombic), np.array(LJ), np.array(GBSA)\n",
        "\n",
        "\n",
        "def derive_G_K(dH, dH_std, dS, dS_std, temperature):\n",
        "    dG = dH - temperature*dS/1000\n",
        "    dG_std = np.sqrt(dH_std**2+(dS_std*temperature/1000)**2)\n",
        "    Kd = np.exp(dG*1000/8.31446261815324/temperature)\n",
        "    Kd_std = Kd*1000/8.31446261815324/temperature*dG_std\n",
        "    return dG, dG_std, Kd, Kd_std\n",
        "\n",
        "\n",
        "rough_traj = md.load(work+'production.h5')\n",
        "start_point = int(skip_initial_fraction*rough_traj.n_frames)\n",
        "\n",
        "lig_traj = rough_traj[start_point::stride].atom_slice(atom_indices=lig_a)\n",
        "rec_traj = rough_traj[start_point::stride].atom_slice(atom_indices=rec_a)\n",
        "com_traj = rough_traj[start_point::stride].atom_slice(atom_indices=com_a)\n",
        "\n",
        "lig_coul, lig_lj, lig_gb = calculate_energies(work, 'ligand', lig_traj, ff, GB_model, solvent_dielectric, solute_dielectric)\n",
        "rec_coul, rec_lj, rec_gb = calculate_energies(work, 'receptor', rec_traj, ff, GB_model, solvent_dielectric, solute_dielectric)\n",
        "com_coul, com_lj, com_gb = calculate_energies(work, 'complex', com_traj, ff, GB_model, solvent_dielectric, solute_dielectric)\n",
        "\n",
        "couls = com_coul - lig_coul - rec_coul\n",
        "ljs = com_lj - lig_lj - rec_lj\n",
        "gbsas = com_gb - lig_gb - rec_gb\n",
        "dHs = couls + ljs + gbsas\n",
        "dH = np.mean(dHs)\n",
        "\n",
        "fig15 = go.Figure()\n",
        "fig15.add_trace(go.Scatter(x=lig_traj.time/1000, y=dHs, mode='lines', name='delta H'))\n",
        "fig15.add_trace(go.Scatter(x=lig_traj.time/1000, y=couls, mode='lines', name='Coulombic E'))\n",
        "fig15.add_trace(go.Scatter(x=lig_traj.time/1000, y=ljs, mode='lines', name='Lennard-Jones E'))\n",
        "fig15.add_trace(go.Scatter(x=lig_traj.time/1000, y=gbsas, mode='lines', name='Solvation E'))\n",
        "fig15.update_layout(title='Binding Energy', xaxis_title='Time (ns)', yaxis_title='Energy (kJ/mol)', width=750, height=500)\n",
        "\n",
        "dE = np.mean(couls+ljs)\n",
        "dE_std = np.std(couls+ljs)\n",
        "dH_std = np.sqrt(np.var(couls+ljs)+np.var(gbsas))\n",
        "\n",
        "fig16 = go.Figure()\n",
        "x = ['ΔE', 'polar', 'nonpolar', 'GBSA', 'ΔH']\n",
        "y = [dE, np.mean(couls), np.mean(ljs), np.mean(gbsas), dH]\n",
        "colors = ['#1f77b4', '#17becf', '#17becf', '#9467bd', '#d62728']\n",
        "err = dict(type='data', array=[dE_std, np.std(couls), np.std(ljs), np.std(gbsas), dH_std])\n",
        "fig16.add_trace(go.Bar(x=x, y=y, error_y=err, marker_color=colors))\n",
        "fig16.update_layout(title=\"Energy Contributions\", xaxis_title='Type', yaxis_title='Energy (kJ/mol)', width=750, height=500)\n",
        "\n",
        "display(fig15, fig16)\n",
        "\n",
        "print(f'Interaction Energy    : {dE:>+7.2f} +/- {dE_std:>5.2f} kJ/mol')\n",
        "print(f'Polar contribution    : {np.mean(couls):>+7.2f} +/- {np.std(couls):>5.2f} kJ/mol')\n",
        "print(f'Nonpolar contribution : {np.mean(ljs):>+7.2f} +/- {np.std(ljs):>5.2f} kJ/mol')\n",
        "print(f'GBSA Solvation Energy : {np.mean(gbsas):>+7.2f} +/- {np.std(gbsas):>5.2f} kJ/mol')\n",
        "print(f'Binding Enthalpy      : {dH:>+7.2f} +/- {dH_std:>5.2f} kJ/mol')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "xiOXqrXq66DM"
      },
      "outputs": [],
      "source": [
        "#@title 5-4. Calculate Binding Free Energy from Interaction Entropy & C2 Entropy\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert 'couls' in globals(), \"Please run the cell# 5-2 first.\"\n",
        "\n",
        "#@markdown Set the bootstrap sampling size to 10^n.\n",
        "bootstrap_power = 4 #@param {type:\"slider\", min:3, max:8, step:1}\n",
        "\n",
        "def calculate_interaction_entropy(interaction_energies, temperature):\n",
        "    \"\"\"\n",
        "    Calculate the interaction entropy using the method from Duan et al.\n",
        "    https://doi.org/10.1021/jacs.6b02682\n",
        "    \"\"\"\n",
        "    R = 8.31446261815324  # Gas constant in J/mol/K\n",
        "    beta = 1 / (R * temperature)\n",
        "    avg_energy = np.mean(interaction_energies)\n",
        "    delta_e = interaction_energies - avg_energy\n",
        "    exp_beta_delta_e = np.exp(beta * delta_e *1000) # kJ/mol to J/mol\n",
        "\n",
        "    interaction_entropy = - R * np.log(np.mean(exp_beta_delta_e))\n",
        "    return interaction_entropy\n",
        "\n",
        "def calculate_c2_entropy(interaction_energies, temperature):\n",
        "    \"\"\"\n",
        "    Calculate the C2 entropy using the method from Menzer et al.\n",
        "    https://doi.org/10.1021/acs.jctc.8b00418\n",
        "    \"\"\"\n",
        "    R = 8.31446261815324  # Gas constant in J/mol/K\n",
        "    beta = 1 / (R * temperature)\n",
        "    variance = np.var(interaction_energies*1000)\n",
        "\n",
        "    c2_entropy = -0.5 * beta * variance / temperature # kJ/mol to J/mol\n",
        "    return c2_entropy\n",
        "\n",
        "\n",
        "def bootstrap_entropy_error(interaction_energies, temperature, n_bootstrap):\n",
        "\n",
        "    n_samples = len(interaction_energies)\n",
        "    interaction_entropies = []\n",
        "    c2_entropies = []\n",
        "\n",
        "    print(f'Running with n_bootstrap : {n_bootstrap}...')\n",
        "\n",
        "    for _ in tqdm(range(n_bootstrap)):\n",
        "        bootstrap_sample = np.random.choice(interaction_energies, size=n_samples, replace=True)\n",
        "\n",
        "        # Calculate entropies for this sample\n",
        "        interaction_entropy = calculate_interaction_entropy(bootstrap_sample, temperature)\n",
        "        c2_entropy = calculate_c2_entropy(bootstrap_sample, temperature)\n",
        "\n",
        "        interaction_entropies.append(interaction_entropy)\n",
        "        c2_entropies.append(c2_entropy)\n",
        "\n",
        "    # Calculate mean and standard error\n",
        "    IE = np.mean(interaction_entropies)\n",
        "    IE_std = np.std(interaction_entropies, ddof=1)\n",
        "\n",
        "    c2 = np.mean(c2_entropies)\n",
        "    c2_std = np.std(c2_entropies, ddof=1)\n",
        "\n",
        "    return IE, IE_std, c2, c2_std\n",
        "\n",
        "temperature = s['temperature']/kelvin\n",
        "\n",
        "# set from https://doi.org/10.1021/acs.jctc.1c00374\n",
        "if dE_std > 15:\n",
        "    print('Warning : Interaction Entropy is likely unreliable!')\n",
        "if dE_std > 25:\n",
        "    print('Warning : C2 Entropy is likely unreliable!')\n",
        "\n",
        "IE, IE_std, c2, c2_std = bootstrap_entropy_error(couls+ljs, temperature, 10**bootstrap_power)\n",
        "\n",
        "print(f'Interaction Entropy : {IE:>+7.2f} +/- {IE_std:>3.2f} J/mol/K')\n",
        "print(f'C2 Entropy          : {c2:>+7.2f} +/- {c2_std:>3.2f} J/mol/K')\n",
        "\n",
        "dG_IE, dG_IE_std, Kd_IE, Kd_IE_std = derive_G_K(dH, dH_std, IE, IE_std, temperature)\n",
        "dG_c2, dG_c2_std, Kd_c2, Kd_c2_std = derive_G_K(dH, dH_std, c2, c2_std, temperature)\n",
        "\n",
        "print(f'Binding Free Energy (ΔG) from IE : {dG_IE:>+7.2f} +/- {dG_IE_std:>3.2f} kJ/mol')\n",
        "print(f'Binding Free Energy (ΔG) from C2 : {dG_c2:>+7.2f} +/- {dG_c2_std:>3.2f} kJ/mol')\n",
        "print(f'Dissociation Constant (Kd) from IE: {Kd_IE:>5.2e} +/- {Kd_IE_std:>3.2e} M')\n",
        "print(f'Dissociation Constant (Kd) from C2: {Kd_c2:>5.2e} +/- {Kd_c2_std:>3.2e} M')\n",
        "\n",
        "\n",
        "fig17 = go.Figure()\n",
        "fig17.add_trace(go.Bar(name='IE', x=['ΔH', '-TΔS', 'ΔG'], y=[dH, -temperature*IE/1000, dG_IE],\n",
        "                        error_y=dict(type='data', array=[dH_std, -temperature*IE_std/1000, dG_IE_std])))\n",
        "fig17.add_trace(go.Bar(name='c2', x=['ΔH', '-TΔS', 'ΔG'], y=[dH, -temperature*c2/1000, dG_c2],\n",
        "                        error_y=dict(type='data', array=[dH_std, -temperature*c2_std/1000, dG_c2_std])))\n",
        "fig17.update_layout(title='Binding Free Energy', xaxis_title='Components', yaxis_title='Energy (kJ/mol)', barmode='group', width=750, height=500)\n",
        "display(fig17)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "cellView": "form",
        "id": "MxEOi2oC6FjX"
      },
      "outputs": [],
      "source": [
        "#@title 5-5. (Optional) Calculate Binding Entropy via Quasi-harmonic Approximation\n",
        "#@markdown **WARNING: QH method takes very long time for large systems!!**\n",
        "\n",
        "assert 'work' in globals(), \"Please run the cell# 0 to set working directory.\"\n",
        "assert 'temperature' in globals(), \"Please run the cell# 5-2 first.\"\n",
        "\n",
        "#@markdown Set the reference concentration in mol/L for a standard solution of ligand.\n",
        "reference_concentration = 1 #@param {type:\"string\"}\n",
        "bootstrap_power = 3 #@param {type:\"slider\", min:3, max:10, step:1}\n",
        "\n",
        "def estimate_rot_entropy_loss(lig_traj, temperature):\n",
        "    print(\"Estimating the ligand's rotational entropy loss upon binding...\", end='')\n",
        "\n",
        "    R = 8.31446261815324  # Gas constant in J/mol/K\n",
        "    N_A = 6.022e23  # Avogadro's number\n",
        "    h = 6.62607004e-34  # Planck's constant in J*s\n",
        "\n",
        "    inertia_tensor = md.compute_inertia_tensor(lig_traj)\n",
        "    moment, axes = np.linalg.eigh(inertia_tensor)\n",
        "    quaternions = Rotation.from_matrix(axes).as_quat()\n",
        "\n",
        "    kde_rot = KernelDensity(kernel='gaussian', bandwidth='scott').fit(quaternions)\n",
        "    S_bound = -R * kde_rot.score_samples(quaternions)\n",
        "    S_bound += 0.5*R*np.log(np.prod(moment.mean(axis=0)))\n",
        "\n",
        "    principal_axes = []\n",
        "    for i in range(lig_traj.n_frames):\n",
        "        I_A, I_B, I_C = inertia_tensor[i,:,:].diagonal()\n",
        "        principal_axes.append(I_A*I_B*I_C)\n",
        "\n",
        "    S_free = []\n",
        "    for i in range(lig_traj.n_frames):\n",
        "        S_free.append(R*(1.5*np.log(temperature)+np.log(principal_axes[i])+1.5*np.log(8*np.pi**2 * R/N_A/h**2)+1.5))\n",
        "\n",
        "    dS = S_bound - np.array(S_free)\n",
        "\n",
        "    print(\"done.\")\n",
        "\n",
        "    return np.mean(dS), np.std(dS)\n",
        "\n",
        "\n",
        "def estimate_trans_entropy_loss(lig_traj, rec_traj, temperature, reference_concentration):\n",
        "    R = 8.31446261815324  # Gas constant in J/mol/K\n",
        "    N_A = 6.022e23  # Avogadro's number\n",
        "\n",
        "    print(f'Reference concentration set to {reference_concentration} mol/L.')\n",
        "    print(\"Estimating the ligand's translational entropy loss upon binding...\", end='')\n",
        "    # Calculate free volume based on reference concentration\n",
        "    ref_v  = 1000 * 1e21/ (reference_concentration * N_A)\n",
        "\n",
        "    free_volume = np.zeros(lig_traj.n_frames)\n",
        "\n",
        "    for i in range(lig_traj.n_frames):\n",
        "        free_volume[i] = ref_v - 4/3*np.pi*(md.compute_rg(lig_traj)[i]**3)\n",
        "\n",
        "    lig_com = md.compute_center_of_mass(lig_traj)\n",
        "    rec_com = md.compute_center_of_mass(rec_traj)\n",
        "    bound_volume = 4/3 * np.pi\n",
        "    for i in range(3):\n",
        "        bound_volume *= np.var((lig_com-rec_com)[:,i])\n",
        "\n",
        "    dS_trans = R * np.log(np.full(lig_traj.n_frames, bound_volume) / free_volume)\n",
        "\n",
        "    print(\"done.\")\n",
        "\n",
        "    return np.mean(dS_trans), np.std(dS_trans)\n",
        "\n",
        "\n",
        "def autocorrelation_time(trajectory):\n",
        "    n_frames, n_atoms, _ = trajectory.shape\n",
        "    mean_positions = np.mean(trajectory, axis=0)\n",
        "\n",
        "    displacements = trajectory - mean_positions\n",
        "    sd = np.sum(displacements**2, axis=(1, 2))\n",
        "\n",
        "    msd = np.mean(sd)\n",
        "\n",
        "    y = sd - msd\n",
        "    acorr = np.correlate(y, y, mode='full')[n_frames-1:]\n",
        "    acorr /= acorr[0]\n",
        "    return np.sum(acorr)\n",
        "\n",
        "def extract_independent_frames(coordinates):\n",
        "    \"\"\"\n",
        "    Extract independent frames based on dynamic autocorrelation times.\n",
        "    \"\"\"\n",
        "    n_frames, n_atoms, n_dims = coordinates.shape\n",
        "    independent_indices = []\n",
        "    last_index = 0\n",
        "\n",
        "    while last_index < n_frames:\n",
        "        independent_indices.append(last_index)\n",
        "        remaining_data = coordinates[last_index:,:,:]\n",
        "        if remaining_data.shape[0] > 1:  # Ensure we have enough data to calculate autocorrelation\n",
        "            try:\n",
        "                lag = int(np.ceil(autocorrelation_time(remaining_data)))\n",
        "            except:\n",
        "                break\n",
        "\n",
        "        last_index += lag\n",
        "\n",
        "    return coordinates[independent_indices]\n",
        "\n",
        "def bootstrap_sample(data, n_samples):\n",
        "    indices = np.random.choice(data.shape[0], size=n_samples, replace=True)\n",
        "    return data[indices,:,:]\n",
        "\n",
        "def quasi_harmonic(name, coordinates, n_bootstrap):\n",
        "    R = 8.31446261815324  # Gas constant in J/mol/K\n",
        "\n",
        "    print(f\"Calculating {name}'s vibrational entropy by quasi-harmonic approach...\")\n",
        "    independent_coords = extract_independent_frames(coordinates)\n",
        "    print(f\"Total {independent_coords.shape[0]} independent frames extracted.\")\n",
        "    bootstrapped_coords = bootstrap_sample(independent_coords, n_bootstrap)\n",
        "    reshaped_coords = bootstrapped_coords.reshape(bootstrapped_coords.shape[0], -1)\n",
        "    print(f'Calculating covariance matrix from bootstrapped samples...', end='')\n",
        "    cov_estimator = EmpiricalCovariance()\n",
        "    cov_estimator.fit(reshaped_coords)\n",
        "    cov_matrix = cov_estimator.covariance_\n",
        "\n",
        "    S_corr = 0.5 * np.log(np.linalg.det(2 * np.pi * np.e * cov_matrix))\n",
        "\n",
        "    print('done.')\n",
        "\n",
        "    return R * S_corr\n",
        "\n",
        "\n",
        "n_bootstrap = 10**bootstrap_power\n",
        "print(f'n_bootstrap set to {n_bootstrap}.')\n",
        "\n",
        "dS_rot, dS_rot_std = estimate_rot_entropy_loss(lig_traj, temperature)\n",
        "dS_trans, dS_trans_std = estimate_trans_entropy_loss(lig_traj, rec_traj, temperature, float(reference_concentration))\n",
        "\n",
        "qh_lig_S = quasi_harmonic('ligand', lig_traj.xyz, n_bootstrap)\n",
        "qh_rec_S = quasi_harmonic('receptor', rec_traj.xyz, n_bootstrap)\n",
        "qh_com_S = quasi_harmonic('complex', com_traj.xyz, n_bootstrap)\n",
        "\n",
        "qh_dS_vib = com_S - lig_S - rec_S\n",
        "\n",
        "qh = dS_vib + dS_rot + dS_trans\n",
        "qh_std = np.sqrt(dS_rot_std**2 + dS_trans_std**2)\n",
        "\n",
        "print(f'Estimated Binding Entropy : {qh:.2f} +/- {qh_std:.2f} J/mol/K')\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B8BgKwrGEKsT"
      },
      "source": [
        "## Tools used"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TkzwxKqOBLZb"
      },
      "source": [
        "* REDUCE\n",
        "> J. M. Word, S. C. Lovell, J. S. Richardson, and D. C. Richardson. (1999) \"Asparagine and glutamine: using hydrogen atom contacts in the choice of side-chain amide orientation\" J. Mol. Biol. 285(4): 1735-1747. DOI:[10.1006/jmbi.1998.2401](https://doi.org/10.1006/jmbi.1998.2401)\n",
        "\n",
        "*  RDKit\n",
        "> RDKit: Open-source cheminformatics. https://www.rdkit.org\n",
        "\n",
        "* OpenBabel\n",
        "> N. M. O'Boyle, M. Banck, C. A. James, C. Morley, T. Vandermeersch, and G. R. Hutchison (2011) \"Open Babel: An open chemical toolbox\" J. Cheminf. 3:33. DOI:[10.1186/1758-2946-3-33](https://doi.org/10.1186/1758-2946-3-33)\n",
        "\n",
        "* PDB2PQR\n",
        "> T. J. Dolinsky, J. E. Nielsen, J. A. McCammon, and N. A. Baker. (2004) \"PDB2PQR: an automated pipeline for the setup, execution, and analysis of Poisson-Boltzmann electrostatics calculations.\" Nucleic Acids Res. 32: W665-667. DOI:[10.1093/nar/gkh381](https://doi.org/10.1093/nar/gkh381)\n",
        "\n",
        "* PropKa\n",
        "> H. Li, A. D. Robertson, and J. H. Jensen. (2005) \"Very Fast Empirical Prediction and Rationalization of Protein pKa Values.\" Proteins, 61: 704-721. DOI:[10.1002/prot.20660](https://doi.org/10.1002/prot.20660)\n",
        "\n",
        "*  OpenMM\n",
        "> P. Eastman, J. Swails, J. D. Chodera, R. T. McGibbon, Y. Zhao, K. A. Beauchamp, L.-P. Wang, A. C. Simmonett, M. P. Harrigan, C. D. Stern, R. P. Wiewiora, B. R. Brooks, and V. S. Pande. (2017) \"OpenMM 7: Rapid development of high performance algorithms for molecular dynamics.” PLOS Comp. Biol. 13(7): e1005659. DOI:[10.1371/journal.pcbi.1005659](https://doi.org/10.1371/journal.pcbi.1005659)\n",
        "\n",
        "*  NGLViewer\n",
        "> H. Nguyen, D. A. Case, and A. S. Rose. (2018) \"NGLview - Interactive molecular graphics for Jupyter notebooks\" Bioinformatics 34(7): 1241-1242. DOI:[10.1093/bioinformatics/btx789](https://doi.org/10.1093/bioinformatics/btx789)\n",
        "\n",
        "* MDTraj\n",
        "> R. T. McGibbon, K. A. Beauchamp, M. P. Harrigan, C. Klein, J. M. Swails, C. X. Hernández, C. R. Schwantes, L-P. Wang, T. J. Lane, and V. S. Pande (2011) \"MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectories\" Biophys. J. 109(8): 1528-1532. DOI:[10.1016/j.bpj.2015.08.015](https://doi.org/10.1016/j.bpj.2015.08.015)\n",
        "\n",
        "* NumPy\n",
        "> C. R. Harris, K. J. Millman, S. J. van der Walt et al. (2020) \"Array programming with NumPy\" Nature 585, 357-362. DOI:[10.1038/s41586-020-2649-2](https://doi.org/10.1038/s41586-020-2649-2)\n",
        "\n",
        "* Scikit-learn\n",
        "> F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, David Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay (2011) \"Scikit-learn: Machine Learning in Python\" JMLR 12(85): 2825-2830. (https://jmlr.csail.mit.edu/papers/v12/pedregosa11a.html)\n",
        "\n",
        "* Plotly\n",
        "> Plotly Technologies Inc. (https://plot.ly)\n",
        "\n",
        "* ipywidgets\n",
        "> Jupyter widgets community (https://github.com/jupyter-widgets/ipywidgets)\n",
        "\n",
        "* PLIP\n",
        "> S. Salentin, S. Schreiber, V. J. Haupt, M. F. Adasme, and M. Schroeder (2015) \"PLIP: fully automated protein-ligand interaction profiler\" Nucleic Acids Research 43(W1): W443-W447. DOI:[10.1093/nar/gkv315](https://doi.org/10.1093/nar/gkv315)"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
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        "7Xf2GSRAqxDg",
        "ktFrmmAnqyp1",
        "1EGMmauoHQmT",
        "B8BgKwrGEKsT"
      ],
      "gpuType": "T4",
      "machine_shape": "hm",
      "provenance": [],
      "authorship_tag": "ABX9TyOy3xwToyQXqdBvA9Q9WKba",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
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