The EVcouplings Python framework for coevolutionary sequence analysis - Hopf, Thomas A; Green, Anna G; Schubert, Benjamin; Mersmann, Sophia; Schärfe, Charlotta P I; Ingraham, John B; Toth-Petroczy, Agnes; Brock, Kelly; Riesselman, Adam J; Palmedo, Perry; Kang, Chan; Sheridan, Robert; et al. (Bioinformatics (Oxford, England), 2019)
Coevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis. The framework enables generation of sequence alignments, calculation and evaluation of evolutionary couplings (ECs), and de novo prediction of structure and mutation effects. The combination of an easy to use, flexible command line interface and an underlying modular Python package makes the full power of coevolutionary analyses available to entry-level and advanced users. https://github.com/debbiemarkslab/evcouplings.