Publication:
The gaussian network model: precise prediction of residue fluctuations and application to binding problems

dc.contributor.departmentDepartment of Chemical and Biological Engineering
dc.contributor.kuauthorErman, Burak
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.date.accessioned2024-11-09T23:36:39Z
dc.date.issued2006
dc.description.abstractThe single- parameter G matrix of force constants proposed by the Gaussian Network Model ( GNM) is iteratively modified to yield native state fluctuations that agree exactly with experimentally observed values. The resulting optimized Gamma matrix contains residue-specific force constants that may be used for an accurate analysis of ligand binding to single or multiple sites on proteins. Bovine Pancreatic Trypsin Inhibitor ( BPTI) is used as an example. The calculated off- diagonal elements of the G matrix, i.e., the optimized spring constants, obey a Lorentzian distribution. The mean value of the spring constants is similar to-0.1, a value much weaker than -1 of the GNM. Few of the spring constants are positive, indicating repulsion between residues. Residue pairs with large number of neighbors have spring constants around the mean, -0.1. Large negative spring constants are between highly correlated pairs of residues. The fluctuations of the distance between anticorrelated pairs of residues are subject to smaller spring constants. The importance of the number of neighbors of residue pairs in determining the elements of the G matrix is pointed out. Allosteric effects of binding on a single or multiple residues of BPTI are illustrated and discussed. Comparison of the predictions of the present model with those of the standard GNM shows that the two models agree at lower modes, i.e., those relating to global motions, but they disagree at higher modes. In the higher modes, the present model points to the important contributions from specific residues whereas the standard GNM fails to do so.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.issue10
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume91
dc.identifier.doi10.1529/biophysj.106.090803
dc.identifier.issn0006-3495
dc.identifier.quartileQ2
dc.identifier.scopus2-s2.0-33751225684
dc.identifier.urihttps://doi.org/10.1529/biophysj.106.090803
dc.identifier.urihttps://hdl.handle.net/20.500.14288/12673
dc.identifier.wos241702500005
dc.keywordsVibrational-energy transfer
dc.keywordsSingle-parameter
dc.keywordsProtein molecule
dc.keywordsMotions
dc.keywordsFlexibility
dc.keywordsStability
dc.keywordsDynamics
dc.keywordsState
dc.language.isoeng
dc.publisherCell Press
dc.relation.ispartofBiophysical Journal
dc.subjectBiophysics
dc.titleThe gaussian network model: precise prediction of residue fluctuations and application to binding problems
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorErman, Burak
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Chemical and Biological Engineering
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relation.isParentOrgUnitOfPublication.latestForDiscovery8e756b23-2d4a-4ce8-b1b3-62c794a8c164

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