EVcouplings

Protein and RNA structure, function and fitness predicted from evolutionary sequence covariation

Webservers and resources

Evolutionary couplings can be used to predict many interesting aspects about protein and RNA molecules from sequence alone. Here is what we have worked on so far:

EVfold webserver

EVfold server

Compute evolutionary couplings from sequence alignments and predict 3D structure for your protein of interest.

evfold.org

Model database

Models

Precomputed evolutionary couplings and 3D models for thousands of experimentally unsolved proteins.

EVfold models

EVcomplex webserver

EVcomplex server

Predict interacting residues in protein complexes from sequence covariation for your complex of interest.

evcomplex.org

EVmutation database

EVmutation

Context-dependent mutation landscapes predicted for thousands of human proteins.

evmutation.org

Disorder database

Protein plasticity

Coevolutionary prediction of conformations of disordered regions in the human proteome.

Disorder predictions

RNA supplement

RNA structure

3D structure of RNA molecules and protein-RNA interactions predicted from nucleotide sequence covariation.

RNA predictions


Software and source code

We provide access to our evolutionary couplings methods as open source software. For details about each tool, please refer to the individual repositories.

EVcouplings

Application and Python package providing the complete EVcouplings workflow from alignment to structure.

Request alpha version

plmc

Software to infer undirected pairwise graphical models from multiple sequence alignments.

GitHub repository

EVmutation

Python module to predict mutation effects from undirected graphical models of sequences.

GitHub repository

EVzoom

Tool to interactively visualize the parameters of undirected graphical models of protein families.

GitHub repository