Back to Search Start Over

Gsatools: Analysis of Allosteric Communication and Functional Local Motions using a Structural Alphabet

Authors :
Jens Kleinjung
Arianna Fornili
Franca Fraternali
Alessandro Pandini
Source :
Bioinformatics
Publisher :
Biophysical Society. Published by Elsevier Inc.

Abstract

BackgroundBiomolecular motions play a key role in several biological functions: enzymatic activity, protein-protein interactions, ligand binding and allosteric regulation. Computational approaches, such as Molecular Dynamics (MD), are now routinely used to reproduce the intrinsic dynamics of proteins, but effective tools are still required to gain functional insight from the simulated data.Methods and ResultsWe previously suggested a method aimed at recovering the role of local conformational changes in functional motions. To this purpose we developed a Structural Alphabet (SA): a set of 25 canonical states of 4-residue protein fragments (Cα atoms only) describing the most probable local conformations in high-resolution protein structures [1]. The SA provides a mean for the coarse-grained annotation and processing of local conformations in a string format, which lends itself to a range of efficient sequence analysis algorithms. The SA has been successfully used in analysing local changes and allosteric signal transmission [2].Here we present GSATools [3], a set of SA-related tools interfacing with GROMACS for the analysis of conformational ensembles. GSATools is designed for the investigation of the conformational dynamics of local structures, the functional correlations between local and global motions, and the mechanisms of allosteric communication.ConclusionsGSATools is a free, easy-to-use and fully documented software for the analysis of conformational ensembles of proteins. The GSATools complement the GROMACS toolkit with a powerful set of analyses to detect, annotate and interpret local motions of functional relevance.1. Pandini A., Fornili A. & Kleinjung J. BMC Bioinformatics 11, 97 (2010).2. Pandini A., Fornili A., Fraternali F. & Kleinjung J., FASEB J., 26, 868 (2012).3. Pandini A., Fornili A., Fraternali F. & Kleinjung J., Bioinformatics, 29, 2053 (2013).

Details

Language :
English
ISSN :
00063495
Issue :
2
Database :
OpenAIRE
Journal :
Biophysical Journal
Accession number :
edsair.doi.dedup.....af50f2ab36ee5f519e2238fa70d53cec
Full Text :
https://doi.org/10.1016/j.bpj.2013.11.3586