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Automatic Ligand parameterization tutorial using BioExcel Building Blocks (biobb)


This tutorial aims to illustrate the process of ligand parameterization for a small molecule, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the Sulfasalazine protein (3-letter code SAS), used to treat rheumatoid arthritis, ulcerative colitis, and Crohn’s disease.

OpenBabel and ACPype packages are used to add hydrogens, energetically minimize the structure, and generate parameters for the GROMACS package. With Generalized Amber Force Field (GAFF) forcefield and AM1-BCC charges.


Settings

Biobb modules used

  • biobb_io: Tools to fetch data to be consumed by the rest of the Biobb building blocks.
  • biobb_chemistry: Tools to manipulate chemical data.

Auxiliar libraries used

  • nb_conda_kernels: Enables a Jupyter Notebook or JupyterLab application in one conda environment to access kernels for Python, R, and other languages found in other environments.
  • nglview: Jupyter/IPython widget to interactively view molecular structures and trajectories in notebooks.
  • ipywidgets: Interactive HTML widgets for Jupyter notebooks and the IPython kernel.

Conda Installation and Launch

git clone https://github.com/bioexcel/biobb_wf_ligand_parameterization.git
cd biobb_wf_ligand_parameterization
conda env create -f conda_env/environment.yml
conda activate biobb_ligand_parameterization_tutorial
jupyter-nbextension enable --py --user widgetsnbextension
jupyter-nbextension enable --py --user nglview
jupyter-notebook biobb_wf_ligand_parameterization/notebooks/biobb_ligand_parameterization_tutorial.ipynb

Tutorial

Click here to view tutorial in Read the Docs


Version

2020.4