Publication:
Prediction of protein-protein interactions: unifying evolution and structure at protein interfaces

dc.contributor.coauthorN/A
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.departmentDepartment of Chemical and Biological Engineering
dc.contributor.kuauthorGürsoy, Attila
dc.contributor.kuauthorKeskin, Özlem
dc.contributor.kuauthorTunçbağ, Nurcan
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.date.accessioned2024-11-09T23:21:12Z
dc.date.issued2011
dc.description.abstractThe vast majority of the chores in the living cell involve protein-protein interactions. Providing details of protein interactions at the residue level and incorporating them into protein interaction networks are crucial toward the elucidation of a dynamic picture of cells. Despite the rapid increase in the number of structurally known protein complexes, we are still far away from a complete network. Given experimental limitations, computational modeling of protein interactions is a prerequisite to proceed on the way to complete structural networks. In this work, we focus on the question 'how do proteins interact?' rather than 'which proteins interact?' and we review structure-based protein-protein interaction prediction approaches. As a sample approach for modeling protein interactions, PRISM is detailed which combines structural similarity and evolutionary conservation in protein interfaces to infer structures of complexes in the protein interaction network. This will ultimately help us to understand the role of protein interfaces in predicting bound conformations.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.issue3
dc.description.openaccessNO
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipTUBITAK [109T343, 109E207]
dc.description.sponsorshipTurkish Academy of Sciences This project has been supported by TUBITAK (research grants: 109T343 and 109E207) and the Turkish Academy of Sciences. NT is supported by a TUBITAK fellowship. We thank Vicki Taylor for editing the manuscript.
dc.description.volume8
dc.identifier.doi10.1088/1478-3975/8/3/035006
dc.identifier.eissn1478-3975
dc.identifier.issn1478-3967
dc.identifier.scopus2-s2.0-79956188706
dc.identifier.urihttps://doi.org/10.1088/1478-3975/8/3/035006
dc.identifier.urihttps://hdl.handle.net/20.500.14288/10852
dc.identifier.wos290560100007
dc.keywordsHot-spot residues
dc.keywordsMacromolecular assemblies
dc.keywordsSaccharomyces-cerevisiae
dc.keywordsStatistical-analysis
dc.keywordsInteraction database
dc.keywordsInteraction networks
dc.keywordsRecognition sites
dc.keywordsCrystalline state
dc.keywordsMolecular docking
dc.keywordsMass-spectrometry
dc.language.isoeng
dc.publisherIop Publishing Ltd
dc.relation.ispartofPhysical Biology
dc.subjectBiochemistry
dc.subjectMolecular biology
dc.subjectBiophysics
dc.titlePrediction of protein-protein interactions: unifying evolution and structure at protein interfaces
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorTunçbağ, Nurcan
local.contributor.kuauthorGürsoy, Attila
local.contributor.kuauthorKeskin, Özlem
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Chemical and Biological Engineering
local.publication.orgunit2Department of Computer Engineering
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