volume 16 issue 02 pages 1840005

The visualCMAT: A web-server to select and interpret correlated mutations/co-evolving residues in protein families

Publication typeJournal Article
Publication date2017-12-29
scimago Q4
wos Q4
SJR0.234
CiteScore2.0
Impact factor0.7
ISSN02197200, 17576334
Biochemistry
Computer Science Applications
Molecular Biology
Abstract

The visualCMAT web-server was designed to assist experimental research in the fields of protein/enzyme biochemistry, protein engineering, and drug discovery by providing an intuitive and easy-to-use interface to the analysis of correlated mutations/co-evolving residues. Sequence and structural information describing homologous proteins are used to predict correlated substitutions by the Mutual information-based CMAT approach, classify them into spatially close co-evolving pairs, which either form a direct physical contact or interact with the same ligand (e.g. a substrate or a crystallographic water molecule), and long-range correlations, annotate and rank binding sites on the protein surface by the presence of statistically significant co-evolving positions. The results of the visualCMAT are organized for a convenient visual analysis and can be downloaded to a local computer as a content-rich all-in-one PyMol session file with multiple layers of annotation corresponding to bioinformatic, statistical and structural analyses of the predicted co-evolution, or further studied online using the built-in interactive analysis tools. The online interactivity is implemented in HTML5 and therefore neither plugins nor Java are required. The visualCMAT web-server is integrated with the Mustguseal web-server capable of constructing large structure-guided sequence alignments of protein families and superfamilies using all available information about their structures and sequences in public databases. The visualCMAT web-server can be used to understand the relationship between structure and function in proteins, implemented at selecting hotspots and compensatory mutations for rational design and directed evolution experiments to produce novel enzymes with improved properties, and employed at studying the mechanism of selective ligand’s binding and allosteric communication between topologically independent sites in protein structures. The web-server is freely available at https://biokinet.belozersky.msu.ru/visualcmat and there are no login requirements.

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Suplatov D. et al. The visualCMAT: A web-server to select and interpret correlated mutations/co-evolving residues in protein families // Journal of Bioinformatics and Computational Biology. 2017. Vol. 16. No. 02. p. 1840005.
GOST all authors (up to 50) Copy
Suplatov D., Sharapova Y., Timonina D., Kopylov K., Švedas V. The visualCMAT: A web-server to select and interpret correlated mutations/co-evolving residues in protein families // Journal of Bioinformatics and Computational Biology. 2017. Vol. 16. No. 02. p. 1840005.
RIS |
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RIS Copy
TY - JOUR
DO - 10.1142/S021972001840005X
UR - https://doi.org/10.1142/S021972001840005X
TI - The visualCMAT: A web-server to select and interpret correlated mutations/co-evolving residues in protein families
T2 - Journal of Bioinformatics and Computational Biology
AU - Suplatov, Dmitry
AU - Sharapova, Yana
AU - Timonina, Daria
AU - Kopylov, Kirill
AU - Švedas, Vytas
PY - 2017
DA - 2017/12/29
PB - World Scientific
SP - 1840005
IS - 02
VL - 16
PMID - 29361894
SN - 0219-7200
SN - 1757-6334
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2017_Suplatov,
author = {Dmitry Suplatov and Yana Sharapova and Daria Timonina and Kirill Kopylov and Vytas Švedas},
title = {The visualCMAT: A web-server to select and interpret correlated mutations/co-evolving residues in protein families},
journal = {Journal of Bioinformatics and Computational Biology},
year = {2017},
volume = {16},
publisher = {World Scientific},
month = {dec},
url = {https://doi.org/10.1142/S021972001840005X},
number = {02},
pages = {1840005},
doi = {10.1142/S021972001840005X}
}
MLA
Cite this
MLA Copy
Suplatov, Dmitry, et al. “The visualCMAT: A web-server to select and interpret correlated mutations/co-evolving residues in protein families.” Journal of Bioinformatics and Computational Biology, vol. 16, no. 02, Dec. 2017, p. 1840005. https://doi.org/10.1142/S021972001840005X.