prodigy

Predict the binding affinity of protein-protein complexes from structural data

https://github.com/haddocking/prodigy

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binding-affinity bioinformatics python3 utrecht-university
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Predict the binding affinity of protein-protein complexes from structural data

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binding-affinity bioinformatics python3 utrecht-university
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README.md

PRODIGY / Binding Affinity Prediction

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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 -np argument 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

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

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Dependencies

.github/workflows/ci.yml actions
  • 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
poetry.lock pypi
  • coverage 7.1.0 develop
  • biopython 1.80
  • freesasa 2.1.0
  • numpy 1.21.1
pyproject.toml pypi
  • biopython 1.80
  • freesasa 2.1.0
  • python ^3.7