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A web server for analysis, comparison and prediction of protein ligand binding sites

BACKGROUND: One of the major challenges in the field of system biology is to understand the interaction between a wide range of proteins and ligands. In the past, methods have been developed for predicting binding sites in a protein for a limited number of ligands. RESULTS: In order to address this...

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Autores principales: Singh, Harinder, Srivastava, Hemant Kumar, Raghava, Gajendra P. S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4807588/
https://www.ncbi.nlm.nih.gov/pubmed/27016210
http://dx.doi.org/10.1186/s13062-016-0118-5
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author Singh, Harinder
Srivastava, Hemant Kumar
Raghava, Gajendra P. S.
author_facet Singh, Harinder
Srivastava, Hemant Kumar
Raghava, Gajendra P. S.
author_sort Singh, Harinder
collection PubMed
description BACKGROUND: One of the major challenges in the field of system biology is to understand the interaction between a wide range of proteins and ligands. In the past, methods have been developed for predicting binding sites in a protein for a limited number of ligands. RESULTS: In order to address this problem, we developed a web server named ‘LPIcom’ to facilitate users in understanding protein-ligand interaction. Analysis, comparison and prediction modules are available in the “LPIcom’ server to predict protein-ligand interacting residues for 824 ligands. Each ligand must have at least 30 protein binding sites in PDB. Analysis module of the server can identify residues preferred in interaction and binding motif for a given ligand; for example residues glycine, lysine and arginine are preferred in ATP binding sites. Comparison module of the server allows comparing protein-binding sites of multiple ligands to understand the similarity between ligands based on their binding site. This module indicates that ATP, ADP and GTP ligands are in the same cluster and thus their binding sites or interacting residues exhibit a high level of similarity. Propensity-based prediction module has been developed for predicting ligand-interacting residues in a protein for more than 800 ligands. In addition, a number of web-based tools have been integrated to facilitate users in creating web logo and two-sample between ligand interacting and non-interacting residues. CONCLUSIONS: In summary, this manuscript presents a web-server for analysis of ligand interacting residue. This server is available for public use from URL http://crdd.osdd.net/raghava/lpicom. REVIEWERS: This article was reviewed by Prof Michael Gromiha, Prof Vladimir Poroikov and Prof Zlatko Trajanoski. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13062-016-0118-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-48075882016-03-25 A web server for analysis, comparison and prediction of protein ligand binding sites Singh, Harinder Srivastava, Hemant Kumar Raghava, Gajendra P. S. Biol Direct Research BACKGROUND: One of the major challenges in the field of system biology is to understand the interaction between a wide range of proteins and ligands. In the past, methods have been developed for predicting binding sites in a protein for a limited number of ligands. RESULTS: In order to address this problem, we developed a web server named ‘LPIcom’ to facilitate users in understanding protein-ligand interaction. Analysis, comparison and prediction modules are available in the “LPIcom’ server to predict protein-ligand interacting residues for 824 ligands. Each ligand must have at least 30 protein binding sites in PDB. Analysis module of the server can identify residues preferred in interaction and binding motif for a given ligand; for example residues glycine, lysine and arginine are preferred in ATP binding sites. Comparison module of the server allows comparing protein-binding sites of multiple ligands to understand the similarity between ligands based on their binding site. This module indicates that ATP, ADP and GTP ligands are in the same cluster and thus their binding sites or interacting residues exhibit a high level of similarity. Propensity-based prediction module has been developed for predicting ligand-interacting residues in a protein for more than 800 ligands. In addition, a number of web-based tools have been integrated to facilitate users in creating web logo and two-sample between ligand interacting and non-interacting residues. CONCLUSIONS: In summary, this manuscript presents a web-server for analysis of ligand interacting residue. This server is available for public use from URL http://crdd.osdd.net/raghava/lpicom. REVIEWERS: This article was reviewed by Prof Michael Gromiha, Prof Vladimir Poroikov and Prof Zlatko Trajanoski. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13062-016-0118-5) contains supplementary material, which is available to authorized users. BioMed Central 2016-03-25 /pmc/articles/PMC4807588/ /pubmed/27016210 http://dx.doi.org/10.1186/s13062-016-0118-5 Text en © Singh et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Singh, Harinder
Srivastava, Hemant Kumar
Raghava, Gajendra P. S.
A web server for analysis, comparison and prediction of protein ligand binding sites
title A web server for analysis, comparison and prediction of protein ligand binding sites
title_full A web server for analysis, comparison and prediction of protein ligand binding sites
title_fullStr A web server for analysis, comparison and prediction of protein ligand binding sites
title_full_unstemmed A web server for analysis, comparison and prediction of protein ligand binding sites
title_short A web server for analysis, comparison and prediction of protein ligand binding sites
title_sort web server for analysis, comparison and prediction of protein ligand binding sites
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4807588/
https://www.ncbi.nlm.nih.gov/pubmed/27016210
http://dx.doi.org/10.1186/s13062-016-0118-5
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