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InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale

We propose InSite, a computational method that integrates high-throughput protein and sequence data to infer the specific binding regions of interacting protein pairs. We compared our predictions with binding sites in Protein Data Bank and found significantly more binding events occur at sites we pr...

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Autores principales: Wang, Haidong, Segal, Eran, Ben-Hur, Asa, Li, Qian-Ru, Vidal, Marc, Koller, Daphne
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2375030/
https://www.ncbi.nlm.nih.gov/pubmed/17868464
http://dx.doi.org/10.1186/gb-2007-8-9-r192
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author Wang, Haidong
Segal, Eran
Ben-Hur, Asa
Li, Qian-Ru
Vidal, Marc
Koller, Daphne
author_facet Wang, Haidong
Segal, Eran
Ben-Hur, Asa
Li, Qian-Ru
Vidal, Marc
Koller, Daphne
author_sort Wang, Haidong
collection PubMed
description We propose InSite, a computational method that integrates high-throughput protein and sequence data to infer the specific binding regions of interacting protein pairs. We compared our predictions with binding sites in Protein Data Bank and found significantly more binding events occur at sites we predicted. Several regions containing disease-causing mutations or cancer polymorphisms in human are predicted to be binding for protein pairs related to the disease, which suggests novel mechanistic hypotheses for several diseases.
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spelling pubmed-23750302008-05-12 InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale Wang, Haidong Segal, Eran Ben-Hur, Asa Li, Qian-Ru Vidal, Marc Koller, Daphne Genome Biol Method We propose InSite, a computational method that integrates high-throughput protein and sequence data to infer the specific binding regions of interacting protein pairs. We compared our predictions with binding sites in Protein Data Bank and found significantly more binding events occur at sites we predicted. Several regions containing disease-causing mutations or cancer polymorphisms in human are predicted to be binding for protein pairs related to the disease, which suggests novel mechanistic hypotheses for several diseases. BioMed Central 2007 2007-09-14 /pmc/articles/PMC2375030/ /pubmed/17868464 http://dx.doi.org/10.1186/gb-2007-8-9-r192 Text en Copyright © 2007 Wang 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 Method
Wang, Haidong
Segal, Eran
Ben-Hur, Asa
Li, Qian-Ru
Vidal, Marc
Koller, Daphne
InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale
title InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale
title_full InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale
title_fullStr InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale
title_full_unstemmed InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale
title_short InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale
title_sort insite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2375030/
https://www.ncbi.nlm.nih.gov/pubmed/17868464
http://dx.doi.org/10.1186/gb-2007-8-9-r192
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