Jupyter Notebook Protein-ligand Docking tutorial (Cluster90)
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This tutorial aims to illustrate the process of protein-ligand docking, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the Mitogen-activated protein kinase 14 (p38-α) protein (PDB code 3HEC), a well-known Protein Kinase enzyme, in complex with the FDA-approved Imatinib, (PDB Ligand code STI, DrugBank Ligand Code DB00619), a small molecule kinase inhibitor used to treat certain types of cancer.
Workflow engine is a jupyter notebook. It can be run in binder, following the link given, or locally. Auxiliar libraries used are: nb_conda_kernels, nglview, ipywidgets, plotly, and simpletraj. Environment can be setup using the included environment.yml file.
Parameters
Inputs
Parameters needed to configure the workflow:
- pdb_code: PDB code of the experimental complex structure (if exists).
- ligand_code: Ligand PDB code (3-letter code) for the small molecule (e.g. STI).
Outputs
Output files generated (named according to the input parameters given above):
- output_structure: generated protein-ligand complex
Version History
Version 6 (latest) Created 4th Mar 2024 at 14:30 by Genís Bayarri
Update to BioBB 4.1.*
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Version-65cabf1c
Version 5 Created 26th Jul 2023 at 10:27 by Genís Bayarri
Fixed importlib_metadata bug
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Version-5
15c1452
Version 4 Created 14th Apr 2023 at 09:09 by Genís Bayarri
Update to BioBB 4.0.*
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Version-4
b38bf86
Version 3 Created 15th Sep 2022 at 12:15 by Genís Bayarri
Update to BioBB 3.8.*. taken from Git commit 9b31005
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Version-3
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Version 2 Created 29th Jun 2021 at 10:06 by Genís Bayarri
Updated to BioBB 3.6.0. Taken from Git commit 1dbc7fe
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Version-2
891cdfe
Version 1 (earliest) Created 28th Jun 2021 at 11:30 by Genís Bayarri
Initial commit. Taken from Git commit 04b4cee
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Views: 5513 Downloads: 1296
Created: 28th Jun 2021 at 11:30
Last updated: 14th Apr 2023 at 09:09
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https://orcid.org/0000-0003-0513-0288
BioExcel is the leading European Centre of Excellence for Computational Biomolecular Research. Established in 2015, the centre has grown into a major research and innovation hub for scientific computing. BioExcel develops some of the most popular applications for modelling and simulations of biomolecular systems. A broad range of additional pre-/post-processing tools are integrated with the core applications within user-friendly workflows and container solutions.
The software stack comes with ...
Teams: BioBB Building Blocks, BioExcel Best Practice Guides
Web page: https://bioexcel.eu/
The BioExcel Building Blocks (biobb) software library is a collection of Python wrappers on top of popular biomolecular simulation tools. This library offers a layer of interoperability between the wrapped tools, which make them compatible and prepared to be directly interconnected to build complex biomolecular workflows. The building blocks can be used in many different workflow systems, including Galaxy, CWL, Jupyter Notebook and PyCOMPSs – notably their ...
Space: BioExcel
Public web page: https://mmb.irbbarcelona.org/biobb/
Interactive Jupyter Notebooks in combination with Conda environments can be used to generate FAIR (Findable, Accessible, Interoperable and Reusable/Reproducible) biomolecular simulation workflows. The interactive programming code accompanied by documentation, and the possibility to inspect intermediate results with versatile graphical charts and data visualization is very helpful, especially in iterative processes, where parameters might be adjusted to a particular system of interest. This work ...
Selection of BioExcel Building Blocks (BioBB) Workflows intended for tutorials and training.
