prodigy
Predict the binding affinity of protein-protein complexes from structural data
Science Score: 67.0%
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Repository
Predict the binding affinity of protein-protein complexes from structural data
Basic Info
- Host: GitHub
- Owner: haddocking
- License: apache-2.0
- Language: Python
- Default Branch: main
- Homepage: https://wenmr.science.uu.nl/prodigy/
- Size: 5.49 MB
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- Stars: 145
- Watchers: 13
- Forks: 31
- Open Issues: 0
- Releases: 17
Topics
Metadata Files
README.md
PRODIGY / Binding Affinity Prediction
PRODIGY is also available as a web service @ wenmr.science.uu.nl/prodigy
Installation
text
pip install prodigy-prot
If you want to develop PRODIGY, check DEVELOPMENT for more details.
Usage
You can run prodigy either on a single structure:
bash
prodigy <structure_file>
Or in a directory containing multiple molecules:
bash
prodigy <directory_with_molecules>
Or using a multi-model input PDB file (an ensemble)
bash
prodigy <multi_model.pdb>
If you are running several structures, try using the
-npargument to run in multiple processors
To get a list of all the possible options.
```bash $ prodigy -h usage: prodigy [-h] [--distance-cutoff DISTANCECUTOFF] [--acc-threshold ACC_THRESHOLD] [--temperature TEMPERATURE] [--contact_list] [--pymol_selection] [-q] [-np NUMBEROFPROCESSORS] [--selection A B [A,B C ...]] inputpath
Binding affinity predictor based on Intermolecular Contacts (ICs).
positional arguments: input_path Path to either: - Structure in PDB or mmCIF format - Directory containing structure files
options: -h, --help show this help message and exit --distance-cutoff DISTANCECUTOFF Distance cutoff to calculate ICs --acc-threshold ACCTHRESHOLD Accessibility threshold for BSA analysis --temperature TEMPERATURE Temperature (C) for Kd prediction --contactlist Output a list of contacts --pymolselection Output a script to highlight the interface (pymol) -q, --quiet Outputs only the predicted affinity value -np, --number-of-processors NUMBEROFPROCESSORS Number of processors to use (default: 1)
Selection Options:
By default, all intermolecular contacts are taken into consideration, a molecule being defined as an isolated group of amino acids sharing a common chain identifier. In specific cases, for example antibody-antigen complexes, some chains should be considered as a single molecule.
Use the --selection option to provide collections of chains that should be considered for the calculation. Separate by a space the chains that are to be considered different molecules. Use commas to include multiple chains as part of a single group:
--selection A B => Contacts calculated (only) between chains A and B. --selection A,B C => Contacts calculated (only) between chains A and C; and B and C. --selection A B C => Contacts calculated (only) between chains A and B; B and C; and A and C. ```
Example single structure
Download the PDB 3BZD and run PRODIGY on it.
bash
$ curl -o 3bzd.pdb https://files.rcsb.org/download/3BZD.pdb
$ prodigy 3bzd.pdb
[+] Reading structure file: /Users/rvhonorato/dbg/3bzd.pdb
[+] Parsed structure file 3bzd (2 chains, 343 residues)
[+] No. of intermolecular contacts: 51
[+] No. of charged-charged contacts: 4
[+] No. of charged-polar contacts: 7
[+] No. of charged-apolar contacts: 6
[+] No. of polar-polar contacts: 7
[+] No. of apolar-polar contacts: 15
[+] No. of apolar-apolar contacts: 12
[+] Percentage of apolar NIS residues: 29.48
[+] Percentage of charged NIS residues: 29.48
[++] Predicted binding affinity (kcal.mol-1): -9.4
[++] Predicted dissociation constant (M) at 25.0˚C: 1.3e-07
Details of the binding affinity predictor implemented in PRODIGY can be found at 10.7554/elife.07454
Example multiple structures
Create a directory that will hold your input molecules
bash
mkdir input
Download some molecules (or copy them into this directory):
text
curl -o input/3bzd.pdb https://files.rcsb.org/download/3BZD.pdb
curl -o input/2oob.pdb https://files.rcsb.org/download/2OOB.pdb
curl -o input/1ppe.pdb https://files.rcsb.org/download/1PPE.pdb
Run prodigy with the quiet option, so it is easier to parse the output later
and run it with 2 processors via the np option.
bash
$ prodigy -q -np 2 input/
3bzd -9.373
2oob -6.230
1ppe -14.727
Citing us
If our tool is useful to you, please cite PRODIGY in your publications:
Xue L, Rodrigues J, Kastritis P, Bonvin A.M.J.J, Vangone A.: PRODIGY: a web server for predicting the binding affinity of protein-protein complexes. Bioinformatics (2016) (10.1093/bioinformatics/btw514)
Anna Vangone and Alexandre M.J.J. Bonvin: Contacts-based prediction of binding affinity in protein-protein complexes. eLife, e07454 (2015) (10.7554/eLife.07454)
Panagiotis L. Kastritis , João P.G.L.M. Rodrigues, Gert E. Folkers, Rolf Boelens, Alexandre M.J.J. Bonvin: Proteins Feel More Than They See: Fine-Tuning of Binding Affinity by Properties of the Non-Interacting Surface. Journal of Molecular Biology, 14, 2632–2652 (2014). (10.1016/j.jmb.2014.04.017)
Contact
For questions about PRODIGY usage, please reach out the team at ask.bioexcel.eu
Information about dependencies
The scripts rely on Biopython to validate the PDB structures and calculate interatomic distances. freesasa, with the parameter set used in NACCESS (Chothia, 1976), is also required for calculating the buried surface area.
DISCLAIMER: given the different software to calculate solvent accessiblity, predicted values might differ (very slightly) from those published in the reference implementations. The correlation of the actual atomic accessibilities is over 0.99, so we expect these differences to be very minor.
Owner
- Name: HADDOCK
- Login: haddocking
- Kind: organization
- Location: Utrecht, The Netherlands
- Website: http://bonvinlab.org
- Repositories: 55
- Profile: https://github.com/haddocking
Computational Structural Biology Group @ Utrecht University
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: Prodigy
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Anna
family-names: Vangone
affiliation: Utrecht University
- given-names: Alexandre
name-particle: MJJ
family-names: Bonvin
affiliation: Utrecht University
- given-names: Joerg
family-names: Schaarschmidt
affiliation: Utrecht University
- given-names: Rodrigo
family-names: Vargas Honorato
affiliation: Utrecht University
- given-names: Brian
family-names: Jimenez
affiliation: Utrecht University
- given-names: Joao
family-names: Rodrigues
affiliation: Utrecht University
identifiers:
- type: doi
value: 10.1093/bioinformatics/btw514
description: DOI of the web service version
- type: doi
value: 10.7554/eLife.07454
- type: doi
value: 10.1016/j.jmb.2014.04.017
repository-code: 'https://github.com/haddocking/prodigy'
url: 'https://wenmr.science.uu.nl/prodigy'
abstract: >-
A tool to predict binding affinity values for
protein-protein complexes from atomic structures.
keywords:
- binding affinity
- computational biology
- protein-protein
license: Apache-2.0
GitHub Events
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Last Year
- Create event: 10
- Release event: 2
- Issues event: 6
- Watch event: 30
- Delete event: 7
- Issue comment event: 7
- Push event: 31
- Pull request review comment event: 1
- Pull request review event: 3
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- Fork event: 6
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 7
- Total pull requests: 16
- Average time to close issues: 2 months
- Average time to close pull requests: 10 minutes
- Total issue authors: 6
- Total pull request authors: 2
- Average comments per issue: 1.29
- Average comments per pull request: 0.06
- Merged pull requests: 14
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 4
- Pull requests: 10
- Average time to close issues: 3 months
- Average time to close pull requests: 11 minutes
- Issue authors: 3
- Pull request authors: 1
- Average comments per issue: 1.0
- Average comments per pull request: 0.0
- Merged pull requests: 8
- Bot issues: 0
- Bot pull requests: 0
Top Authors
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Pull Request Authors
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- amjjbonvin (1)
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Dependencies
- actions/checkout v3 composite
- actions/setup-python v4 composite
- codacy/codacy-coverage-reporter-action v1 composite
- codecov/codecov-action v3 composite
- snok/install-poetry v1 composite
- coverage 7.1.0 develop
- biopython 1.80
- freesasa 2.1.0
- numpy 1.21.1
- biopython 1.80
- freesasa 2.1.0
- python ^3.7