Python CNS/XPLOR MD Automatic Ligand Parameterization tutorial using Biobb
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1yr ago
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Version 2
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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.
Code Snippets
5 6 7 8 | from biobb_common.configuration import settings from biobb_common.tools import file_utils as fu from biobb_chemistry.babelm.babel_minimize import babel_minimize from biobb_chemistry.acpype.acpype_params_cns import acpype_params_cns |
12 13 14 15 16 17 18 19 20 21 | conf = settings.ConfReader(config, system) global_log, _ = fu.get_logs(path=conf.get_working_dir_path(), light_format=True) global_prop = conf.get_prop_dic(global_log=global_log) global_paths = conf.get_paths_dic() global_log.info("step2_babel_minimize: Energetically minimize hydrogen atoms") babel_minimize(**global_paths["step2_babel_minimize"], properties=global_prop["step2_babel_minimize"]) global_log.info("step3_acpype_params_cns: Generating ligand parameters") acpype_params_cns(**global_paths["step3_acpype_params_cns"], properties=global_prop["step3_acpype_params_cns"]) |
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Created: 1yr ago
Updated: 1yr ago
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public
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https://workflowhub.eu/workflows/293
Name:
python-cns-xplor-md-automatic-ligand-parameterizat
Version:
Version 2
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Public Domain
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