Alexandre Bonvin bio photo

Computational Structural Biology group focusing on dissecting, understanding and predicting biomolecular interactions at the molecular level.

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This page provide you links to software and software manuals of the computational structural biology group.


Software package for integrative modelling of biomolecular complexes

HADDOCKING GitHub repository

The GitHub repository for HADDOCK and its associated tools

  • Binding_affinity: PRODIGY: A collection of Python scripts to predict the binding affinity in protein-protein complexes.

  • DisVis: A Python package and command-line tool to quantify and visualize the accessible interaction space of distance-restrained biomolecular complexes.

  • Fraction of common contact clustering: Clustering of biomolecular complexes based on the fraction of common contacts

  • HADDOCK-tools: A collection of useful scripts related to HADDOCK

  • PDB-tools: A collection of Python scripts for the manipulation (renumbering, changing chain and segIDs…) of PDB files. For documentation refer to And now also available as web portal!

  • PowerFit: PowerFit is a Python package and simple command-line program to automatically fit high-resolution atomic structures in cryo-EM densities.

  • Samplex: Samplex is an automatic and unbiased method to distinguish perturbed and unperturbed regions in a protein existing in two distinct states (folded/partially unfolded, bound/unbound). Samplex takes as input a set of data and the corresponding three-dimensional structure and returns the confidence for each residue to be in a perturbed or unperturbed state.

3D-DART DNA modelling

3D-DART provides a convenient means of generating custom structural models of DNA. Our server is no longer in operation because of security issues, but you can run it yourself from a docker container. Visit for this our GitHub repo below.

Bioinformatics interface predictors

  • WHISCY WHISCY is a program to predict protein-protein interfaces. It is primarily based on conservation, but it also takes into account structural information.

  • CPORT CPORT is an algorithm for the prediction of protein-protein interface residues. It combines six interface prediction methods into a consensus predictor

Deep learning protein interactions

  • DeepRank DeepRank is a general, configurable deep learning framework for data mining protein-protein interactions (PPIs) using 3D convolutional neural networks (CNNs).

  • DeepRank-GNN DeepRank-GNN is a general, configurable deep learning framework for data mining protein-protein interactions (PPIs) using graph convolutional neural networks (CNNs).

Benchmarks and datasets