PyInteraph: a framework for the analysis of interaction networks in structural ensembles of proteins

Matteo Tiberti, Gaetano Invernizzi, Matteo Lambrughi, Yuval Inbar, Gideon Schreiber, Elena Papaleo

54 Citations (Scopus)

Abstract

In the last years, a growing interest has been gathering around the ability of Molecular Dynamics (MD) to provide insight into the paths of long-range structural communication in biomolecules. The knowledge of the mechanisms related to structural communication helps in the rationalization in atomistic details of the effects induced by mutations, ligand binding, and the intrinsic dynamics of proteins. We here present PyInteraph, a tool for the analysis of structural ensembles inspired by graph theory. PyInteraph is a software suite designed to analyze MD and structural ensembles with attention to binary interactions between residues, such as hydrogen bonds, salt bridges, and hydrophobic interactions. PyInteraph also allows the different classes of intra- and intermolecular interactions to be represented, combined or alone, in the form of interaction graphs, along with performing network analysis on the resulting interaction graphs. The program also integrates the network description with a knowledge-based force field to estimate the interaction energies between side chains in the protein. It can be used alone or together with the recently developed xPyder PyMOL plugin through an xPyder-compatible format. The software capabilities and associated protocols are here illustrated by biologically relevant cases of study. The program is available free of charge as Open Source software via the GPL v3 license at http://linux.btbs.unimib.it/pyinteraph/ .
Original languageEnglish
JournalJournal of Chemical Information and Modeling
Volume54
Issue number5
Pages (from-to)1537-1551
Number of pages15
ISSN1549-9596
DOIs
Publication statusPublished - 28 Apr 2014

Fingerprint

Dive into the research topics of 'PyInteraph: a framework for the analysis of interaction networks in structural ensembles of proteins'. Together they form a unique fingerprint.

Cite this