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Gsatools: Analysis of Allosteric Communication and Functional Local Motions using a Structural Alphabet
- 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).
- Subjects :
- Statistics and Probability
Theoretical computer science
Computer science
Protein Conformation
Structural alphabet
Mutant
Allosteric regulation
GSATools
Biophysics
Computational biology
01 natural sciences
Biochemistry
Set (abstract data type)
Functional motions in proteins
03 medical and health sciences
Molecular dynamics
Motion
0302 clinical medicine
Protein structure
Allosteric Regulation
0103 physical sciences
Molecular Biology
Conformational ensembles
030304 developmental biology
Complement (set theory)
0303 health sciences
010304 chemical physics
String (computer science)
Applications Notes
Structural Bioinformatics
Computer Science Applications
Computational Mathematics
Identification (information)
Range (mathematics)
Computational Theory and Mathematics
030217 neurology & neurosurgery
Software
Subjects
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