Only a Subset of Normal Modes is Sufficient to Identify Linear Correlations in Proteins

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dc.authoridYildirim, Ahmet/0000-0003-1495-0288
dc.authoridTekpinar, Mustafa/0000-0002-0207-0446
dc.contributor.authorTekpinar, Mustafa
dc.contributor.authorYildirim, Ahmet
dc.date.accessioned2024-12-24T19:27:50Z
dc.date.available2024-12-24T19:27:50Z
dc.date.issued2018
dc.departmentSiirt Üniversitesi
dc.description.abstractIdentification of correlated residues in proteins is very important for many areas of protein research such as drug design, protein domain classification, signal transmission, allostery and mutational studies. Pairwise residue correlations in proteins can be obtained from experimental and theoretical ensembles. Since it is difficult to obtain proteins in various conformational states experimentally, theoretical methods such as all-atom molecular dynamics simulations and normal-mode analysis are commonly used methods to obtain protein ensembles and, therefore, pairwise residue correlations. The extent of agreement for the correlations obtained with all-atom molecular dynamics and elastic network model based normal-mode analysis is an important issue to investigate due to orders of magnitude computational advantage in terms of wall time for normal-mode based calculation. We performed multiple microsecond long equilibrium classical molecular dynamics simulations for six proteins. We calculated normalized dynamical cross-correlations and linear mutual information as pairwise residue correlations from the trajectories of these simulations. Then, we calculated the same pairwise residue correlations with two elastic network model based normal-mode analysis methods and compared our results with the former. The results show that elastic network model based normal-mode analysis can provide a fast and accurate estimation of linear correlations within proteins. Finally, we observed that only a subset of modes is sufficient to obtain linear correlations in proteins. This conclusion has crucial implications for understanding correlations within very large protein assemblies such as viral capsids.
dc.identifier.doi10.1021/acs.jcim.8b00486
dc.identifier.endpage1961
dc.identifier.issn1549-9596
dc.identifier.issn1549-960X
dc.identifier.issue9
dc.identifier.pmid30148964
dc.identifier.scopus2-s2.0-85053243181
dc.identifier.scopusqualityQ1
dc.identifier.startpage1947
dc.identifier.urihttps://doi.org/10.1021/acs.jcim.8b00486
dc.identifier.urihttps://hdl.handle.net/20.500.12604/6816
dc.identifier.volume58
dc.identifier.wosWOS:000445847700021
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherAmer Chemical Soc
dc.relation.ispartofJournal of Chemical Information and Modeling
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.titleOnly a Subset of Normal Modes is Sufficient to Identify Linear Correlations in Proteins
dc.typeArticle

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