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An automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies

BACKGROUND: Recent progress in sequencing and 3 D structure determination techniques stimulated development of approaches aimed at more precise annotation of proteins, that is, prediction of exact specificity to a ligand or, more broadly, to a binding partner of any kind. RESULTS: We present a metho...

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Autores principales: Mazin, Pavel V, Gelfand, Mikhail S, Mironov, Andrey A, Rakhmaninova, Aleksandra B, Rubinov, Anatoly R, Russell, Robert B, Kalinina, Olga V
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2914642/
https://www.ncbi.nlm.nih.gov/pubmed/20633297
http://dx.doi.org/10.1186/1748-7188-5-29
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author Mazin, Pavel V
Gelfand, Mikhail S
Mironov, Andrey A
Rakhmaninova, Aleksandra B
Rubinov, Anatoly R
Russell, Robert B
Kalinina, Olga V
author_facet Mazin, Pavel V
Gelfand, Mikhail S
Mironov, Andrey A
Rakhmaninova, Aleksandra B
Rubinov, Anatoly R
Russell, Robert B
Kalinina, Olga V
author_sort Mazin, Pavel V
collection PubMed
description BACKGROUND: Recent progress in sequencing and 3 D structure determination techniques stimulated development of approaches aimed at more precise annotation of proteins, that is, prediction of exact specificity to a ligand or, more broadly, to a binding partner of any kind. RESULTS: We present a method, SDPclust, for identification of protein functional subfamilies coupled with prediction of specificity-determining positions (SDPs). SDPclust predicts specificity in a phylogeny-independent stochastic manner, which allows for the correct identification of the specificity for proteins that are separated on a phylogenetic tree, but still bind the same ligand. SDPclust is implemented as a Web-server http://bioinf.fbb.msu.ru/SDPfoxWeb/ and a stand-alone Java application available from the website. CONCLUSIONS: SDPclust performs a simultaneous identification of specificity determinants and specificity groups in a statistically robust and phylogeny-independent manner.
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spelling pubmed-29146422010-08-12 An automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies Mazin, Pavel V Gelfand, Mikhail S Mironov, Andrey A Rakhmaninova, Aleksandra B Rubinov, Anatoly R Russell, Robert B Kalinina, Olga V Algorithms Mol Biol Research BACKGROUND: Recent progress in sequencing and 3 D structure determination techniques stimulated development of approaches aimed at more precise annotation of proteins, that is, prediction of exact specificity to a ligand or, more broadly, to a binding partner of any kind. RESULTS: We present a method, SDPclust, for identification of protein functional subfamilies coupled with prediction of specificity-determining positions (SDPs). SDPclust predicts specificity in a phylogeny-independent stochastic manner, which allows for the correct identification of the specificity for proteins that are separated on a phylogenetic tree, but still bind the same ligand. SDPclust is implemented as a Web-server http://bioinf.fbb.msu.ru/SDPfoxWeb/ and a stand-alone Java application available from the website. CONCLUSIONS: SDPclust performs a simultaneous identification of specificity determinants and specificity groups in a statistically robust and phylogeny-independent manner. BioMed Central 2010-07-15 /pmc/articles/PMC2914642/ /pubmed/20633297 http://dx.doi.org/10.1186/1748-7188-5-29 Text en Copyright ©2010 Mazin et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Mazin, Pavel V
Gelfand, Mikhail S
Mironov, Andrey A
Rakhmaninova, Aleksandra B
Rubinov, Anatoly R
Russell, Robert B
Kalinina, Olga V
An automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies
title An automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies
title_full An automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies
title_fullStr An automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies
title_full_unstemmed An automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies
title_short An automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies
title_sort automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2914642/
https://www.ncbi.nlm.nih.gov/pubmed/20633297
http://dx.doi.org/10.1186/1748-7188-5-29
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