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Multisite λ Dynamics

  1. Hardware requirements
    Linux system with NVIDIA GPU
    !! root or superuser privileges are NOT required !!

  2. Software requirements
    CHARMM program
    miniconda
    PyMOL
    MMTSB
    LOMAP -- Optional

  3. References literature

  4. Github Resources

Compiling CHARMM

** You can follow the steps from the pyCHARMM workshop as well, below is just a part of the things that are on the pyCHARMM workshop page **

  1. Install miniconda and create a new environment
    conda create --name charmm
    conda activate charmm
  • install mamba within the conda environment to make the next steps fast
    conda install conda-forge::mamba
  • Please see more info on pyCHARMM workshop's page regarding cuda and GCC
    • check the version of NVIDIA drivers
      nvidia-smi
    • install cuda version that is compatible with your NVIDIA drivers
      mamba install -y -c "nvidia/label/cuda-x.y.y" cuda
    • use GCC version that is recommended for your cuda version
      mamba install -y -c conda-forge gcc==X.X gxx==X.X gfortran==X.X
  • a few more packages through conda
    mamba install -y -c conda-forge make cmake binutils fftw openmpi openmm sysroot_linux-64==2.17 readline==8.2 rdkit openbabel pymol-open-source pymbar
  1. Compile CHARMM
  • active your conda environment
    conda activate charmm
  • untar CHARMM
    tar -xvf charmm.tgz
    cd charmm
    mkdir build_charmm
    cd build_charmm
    ../configure -u --with-blade --without-mkl
    I'm using 8 cores (see next command) to compile/build charmm, you can use more cores eg. 10 or 20 or less eg 1 or 4.
    make -j 8 all
    DONE