Repository containing various scripts to predict the binding affinity of protein-protein complexes from structure
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PRODIGY / Binding Affinity Prediction

Collection of scripts to predict binding affinity values for protein-protein complexes from atomic structures.

The online version of PRODIGY predictor can be found here:

Details of the binding affinity predictor implemented in PRODIGY can be found here:

Quick & Dirty Installation

git clone
cd biopython
sudo python install # Alternatively, install locally but fix $PYTHONPATH

tar -xzvf freesasa-1.0.tar.gz
cd freesasa-1.0
./configure && make && make install

git clone

# Edit the to setup the paths to the freesasa binary and radii files

# Have fun!


python <pdb file> [--selection <chain1><chain2>]

Type --help to get a list of all the possible options of the script.

Installation & 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.

To install and use the scripts, just clone the git repository or download the tarball zip archive. Make sure freesasa and Biopython are accessible to the Python scripts through the appropriate environment variables ($PYTHONPATH).


These utilities are open-source and licensed under the Apache License 2.0. For more information read the LICENSE file.

Citing us

If our predictive model or any scripts are useful to you, consider citing them 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) (link)

Anna Vangone and Alexandre M.J.J. Bonvin: Contacts-based prediction of binding affinity in protein-protein complexes. eLife, e07454 (2015) (link)

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). (link)