Protein Ligand Complex MD Setup tutorial using BioExcel Building Blocks (biobb)

Forked from the original biobb_wf_protein-complex

Based on the official GROMACS tutorial.

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This tutorial aims to illustrate the process of setting up a simulation system containing a protein in complex with a ligand, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the T4 lysozyme L99A/M102Q protein (PDB code 3HTB), in complex with the 2-propylphenol small molecule (3-letter Code JZ4).

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Settings

Biobb modules used

• biobb_io: Tools to fetch biomolecular data from public databases.
• biobb_model: Tools to model macromolecular structures.
• biobb_chemistry: Tools to manipulate chemical data.
• biobb_gromacs: Tools to setup and run Molecular Dynamics simulations.
• biobb_analysis: Tools to analyse Molecular Dynamics trajectories.
• biobb_structure_utils: Tools to modify or extract information from a PDB structure file.

Auxiliary libraries used

• jupyter: Free software, open standards, and web services for interactive computing across all programming languages.
• nglview: Jupyter/IPython widget to interactively view molecular structures and trajectories in notebooks.
• plotly: Python interactive graphing library integrated in Jupyter notebooks.
• simpletraj: Lightweight coordinate-only trajectory reader based on code from GROMACS, MDAnalysis and VMD.

Conda Installation and Launch

See: bioexcel/biobb_gromacs#23

1. Install python packages

git clone https://github.com/hariseldon99/biobb_wf_protein-complex_md_setup.git
cd biobb_wf_protein-complex_md_setup
conda env create -f conda_env/environment.yml
conda activate biobb_wf_protein-complex_md_setup

2. Install or load CUDA, i.e., CUDATOOLKIT
3. Download and compile GROMACS from source with CUDA enabled: TODO
4. Install development version of MDAnalysis: TODO
5. Run

jupyter-notebook biobb_wf_protein-complex_md_setup/notebooks/biobb_wf_protein-complex_md_setup.ipynb

Tutorial

Click here to view tutorial

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Version

2024.1+0.0.1

Copyright & Licensing

This software has been developed in the MMB group at the BSC & IRB for the European BioExcel, funded by the European Commission (EU H2020 823830, EU H2020 675728).

• (c) 2015-2024 Barcelona Supercomputing Center
• (c) 2015-2024 Institute for Research in Biomedicine

Licensed under the Apache License 2.0, see the file LICENSE for details.

Forked by Analabha Roy, Department of Physics, The University of Burdwan

TODO

Conda environment created properly, but downloading gromacs source and running the following in the build directory:

cmake .. -DCMAKE_INSTALL_PREFIX=$CONDA_PREFIX -DGMX_GPU=CUDA -DGMX_HWLOC=ON -DGMX_SIMD=AVX_512
make -j $NPROCS
make check
make install

yields error for cmake:

CMake Error: The following variables are used in this project, but they are set to NOTFOUND.
Please set them or make sure they are set and tested correctly in the CMake files:
CUDA_cufft_LIBRARY (ADVANCED)
    linked by target "testutils" in directory /tmp/gromacs-2024.4/src/testutils
    linked by target "libgromacs" in directory /tmp/gromacs-2024.4/src/gromacs

-- Generating done (0.8s)
CMake Generate step failed.  Build files cannot be regenerated correctly.

Solution: NVidia HPC toolkit is not supported for GROMACS. Need standard cuda toolkit. Run in cluster where this should work.

Also, need to figure out what environment variables to set for gromacs to work properly. The gromacs package in conda-forge sets the following files

• @ $CONDA_PREFIX/etc/conda/activate.d
• @ $CONDA_PREFIX/etc/conda/deactivate.d

The files should probably should be changed to include the AVX_512 option

Background: https://guillaume-martin.github.io/saving-environment-variables-in-conda.html