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dc.contributor.authorMoal, Iain H.
dc.contributor.authorDapkūnas, Justas
dc.contributor.authorFernández-Recio, Juan
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2016-05-09T15:47:58Z
dc.date.available2016-05-09T15:47:58Z
dc.date.issued2015-04
dc.identifier.citationMoal, Iain H.; Dapkūnas, Justas; Fernández-Recio, Juan. Inferring the microscopic surface energy of protein-protein interfaces from mutation data. "Proteins", Abril 2015, vol. 83, núm. 4, p. 640-650.
dc.identifier.issn0887-3585
dc.identifier.urihttp://hdl.handle.net/2117/86791
dc.description.abstractMutations at protein-protein recognition sites alter binding strength by altering the chemical nature of the interacting surfaces. We present a simple surface energy model, parameterised with empirical DDG values, yielding mean energies of -48 cal.mol−1.°A−2 for interactions between hydrophobic surfaces, -51 to -80 cal.mol−1.°A −2 for surfaces of complementary charge, and 66 to 83 cal.mol−1.°A−2 for electrostatically repelling surfaces, relative to the aqueous phase. This places the mean energy of hydrophobic surface burial at -24 cal.mol−1.°A−2. Despite neglecting configurational entropy and intramolecular changes, the model correlates with empirical binding free energies of a functionally diverse set of rigid-body interactions (r=0.66). When used to rerank docking poses, it can place near-native solutions in the top 10 for 37% of the complexes evaluated, and 82% in the top 100. The method shows that hydrophobic burial is the driving force for protein association, accounting for 50-95% of the cohesive energy. The model is available opensource from http://life.bsc.es/pid/web/surface_energy/ and via the CCharpPPI web server http://life.bsc.es/pid/ccharppi/.
dc.description.sponsorshipThis research was in part supported by postdoctoral fellowship funded by European Union Structural Funds project ”Postdoctoral Fellowship Implementation in Lithuania”. The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Unions Seventh Framework Programme (FP7/2007-2013) under REA grant agreement PIEF-GA- 2012-327899, and the SpanishMinistry of Science and Innovation project [BIO2013- 48213-R]. The authors declare no conflict of interests.
dc.format.extent11 p.
dc.language.isoeng
dc.publisherWiley
dc.subjectÀrees temàtiques de la UPC::Enginyeria electrònica
dc.subject.lcshProtein-protein interactions
dc.subject.otherProtein–protein interactions
dc.subject.otherBinding affinity
dc.subject.otherInteraction energy
dc.subject.otherMutation
dc.subject.otherDocking
dc.subject.otherHydrophobic effect
dc.subject.otherEmpirical modeling
dc.titleInferring the microscopic surface energy of protein-protein interfaces from mutation data
dc.typeArticle
dc.subject.lemacProteïnes
dc.identifier.doi10.1002/prot.24761
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://onlinelibrary.wiley.com/doi/abs/10.1002/prot.24761
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/327899/EU/Exploring the evolution of protein-protein interactions and their networks using biophysical models/EEPPIBM
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO//BIO2013-48213-R/ES/DESARROLLO DE NUEVAS METODOLOGIAS DE DOCKING ENTRE PROTEINAS PARA LOS RETOS DE INTERACTOMICA Y MEDICINA PERSONALIZADA/
local.citation.publicationNameProteins
local.citation.volume83
local.citation.number4
local.citation.startingPage640
local.citation.endingPage650


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