Workflow Type: Jupyter
Stable

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.


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).

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

Version History

Version 3 (latest) Created 15th Sep 2022 at 11:59 by Genís Bayarri

Update to BioBB 3.8.*. taken from Git commit 2a351bf


Frozen Version-3 0e1ae08

Version 2 Created 29th Jun 2021 at 08:40 by Robin Long

Updated to BioBB 3.6.0. Taken from Git commit 461262dae


Frozen Version-2 461262d

Version 1 (earliest) Created 14th Sep 2020 at 11:01 by Robin Long

Initial Commit. Taken from Git commit c6cb736


Frozen master eff4a17
help Creators and Submitter
Citation
Bayarri, G., Hospital, A., & Lowe, D. (2022). Jupyter GMX Notebook Automatic Ligand Parameterization tutorial. WorkflowHub. https://doi.org/10.48546/WORKFLOWHUB.WORKFLOW.54.3
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Views: 1863

Created: 14th Sep 2020 at 11:01

Last updated: 17th Mar 2022 at 14:07

Last used: 6th Oct 2022 at 13:55

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