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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Main Author: Brian Y Chen
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-08-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC4148194?pdf=render
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author Brian Y Chen
author_facet Brian Y Chen
author_sort Brian Y Chen
collection DOAJ
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 doaj.art-e901063f0ad043b8abf35a29843cd0d52022-12-22T01:35:59ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582014-08-01108e100379210.1371/journal.pcbi.1003792VASP-E: specificity annotation with a volumetric analysis of electrostatic isopotentials.Brian Y ChenAlgorithms 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.http://europepmc.org/articles/PMC4148194?pdf=render
spellingShingle Brian Y Chen
VASP-E: specificity annotation with a volumetric analysis of electrostatic isopotentials.
PLoS Computational Biology
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
url http://europepmc.org/articles/PMC4148194?pdf=render
work_keys_str_mv AT brianychen vaspespecificityannotationwithavolumetricanalysisofelectrostaticisopotentials