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VASP-E: Specificity Annotation with a Volumetric Analysis of Electrostatic Isopotentials

Algorithms for comparing protein structure are frequently used for function annotation. By searching for subtle similarities among very different proteins, these algorithms can identify remote homologs with similar biological functions. In contrast, few comparison algorithms focus on specificity ann...

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Detalles Bibliográficos
Autor principal: Chen, Brian Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4148194/
https://www.ncbi.nlm.nih.gov/pubmed/25166865
http://dx.doi.org/10.1371/journal.pcbi.1003792
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author Chen, Brian Y.
author_facet Chen, Brian Y.
author_sort Chen, Brian Y.
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description Algorithms for comparing protein structure are frequently used for function annotation. By searching for subtle similarities among very different proteins, these algorithms can identify remote homologs with similar biological functions. In contrast, few comparison algorithms focus on specificity annotation, where the identification of subtle differences among very similar proteins can assist in finding small structural variations that create differences in binding specificity. Few specificity annotation methods consider electrostatic fields, which play a critical role in molecular recognition. To fill this gap, this paper describes VASP-E (Volumetric Analysis of Surface Properties with Electrostatics), a novel volumetric comparison tool based on the electrostatic comparison of protein-ligand and protein-protein binding sites. VASP-E exploits the central observation that three dimensional solids can be used to fully represent and compare both electrostatic isopotentials and molecular surfaces. With this integrated representation, VASP-E is able to dissect the electrostatic environments of protein-ligand and protein-protein binding interfaces, identifying individual amino acids that have an electrostatic influence on binding specificity. VASP-E was used to examine a nonredundant subset of the serine and cysteine proteases as well as the barnase-barstar and Rap1a-raf complexes. Based on amino acids established by various experimental studies to have an electrostatic influence on binding specificity, VASP-E identified electrostatically influential amino acids with 100% precision and 83.3% recall. We also show that VASP-E can accurately classify closely related ligand binding cavities into groups with different binding preferences. These results suggest that VASP-E should prove a useful tool for the characterization of specific binding and the engineering of binding preferences in proteins.
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spelling pubmed-41481942014-08-29 VASP-E: Specificity Annotation with a Volumetric Analysis of Electrostatic Isopotentials Chen, Brian Y. PLoS Comput Biol Research Article Algorithms for comparing protein structure are frequently used for function annotation. By searching for subtle similarities among very different proteins, these algorithms can identify remote homologs with similar biological functions. In contrast, few comparison algorithms focus on specificity annotation, where the identification of subtle differences among very similar proteins can assist in finding small structural variations that create differences in binding specificity. Few specificity annotation methods consider electrostatic fields, which play a critical role in molecular recognition. To fill this gap, this paper describes VASP-E (Volumetric Analysis of Surface Properties with Electrostatics), a novel volumetric comparison tool based on the electrostatic comparison of protein-ligand and protein-protein binding sites. VASP-E exploits the central observation that three dimensional solids can be used to fully represent and compare both electrostatic isopotentials and molecular surfaces. With this integrated representation, VASP-E is able to dissect the electrostatic environments of protein-ligand and protein-protein binding interfaces, identifying individual amino acids that have an electrostatic influence on binding specificity. VASP-E was used to examine a nonredundant subset of the serine and cysteine proteases as well as the barnase-barstar and Rap1a-raf complexes. Based on amino acids established by various experimental studies to have an electrostatic influence on binding specificity, VASP-E identified electrostatically influential amino acids with 100% precision and 83.3% recall. We also show that VASP-E can accurately classify closely related ligand binding cavities into groups with different binding preferences. These results suggest that VASP-E should prove a useful tool for the characterization of specific binding and the engineering of binding preferences in proteins. Public Library of Science 2014-08-28 /pmc/articles/PMC4148194/ /pubmed/25166865 http://dx.doi.org/10.1371/journal.pcbi.1003792 Text en © 2014 Brian Y http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Chen, Brian Y.
VASP-E: Specificity Annotation with a Volumetric Analysis of Electrostatic Isopotentials
title VASP-E: Specificity Annotation with a Volumetric Analysis of Electrostatic Isopotentials
title_full VASP-E: Specificity Annotation with a Volumetric Analysis of Electrostatic Isopotentials
title_fullStr VASP-E: Specificity Annotation with a Volumetric Analysis of Electrostatic Isopotentials
title_full_unstemmed VASP-E: Specificity Annotation with a Volumetric Analysis of Electrostatic Isopotentials
title_short VASP-E: Specificity Annotation with a Volumetric Analysis of Electrostatic Isopotentials
title_sort vasp-e: specificity annotation with a volumetric analysis of electrostatic isopotentials
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4148194/
https://www.ncbi.nlm.nih.gov/pubmed/25166865
http://dx.doi.org/10.1371/journal.pcbi.1003792
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