Welcome to the UPF Digital Repository

Self-consistency test reveals systematic bias in programs for prediction change of stability upon mutation

Show simple item record

dc.contributor.author Usmanova, Dinara R.
dc.contributor.author Bogatyreva, Natalya S.
dc.contributor.author Ariño Bernad, Joan
dc.contributor.author Eremina, Aleksandra A.
dc.contributor.author Gorshkova, Anastasiya A.
dc.contributor.author Kanevskiy, German M.
dc.contributor.author Lonishin, Lyubov R.
dc.contributor.author Meister, Alexander V.
dc.contributor.author Yakupova, Alisa G.
dc.contributor.author Kondrashov, Fyodor A., 1979-
dc.contributor.author Ivankov, Dmitry N.
dc.date.accessioned 2019-05-24T07:43:30Z
dc.date.available 2019-05-24T07:43:30Z
dc.date.issued 2018
dc.identifier.citation Usmanova DR, Bogatyreva NS, Ariño Bernad J, Eremina AA, Gorshkova AA, Kanevskiy GM, Lonishin LR, Meister AV, Yakupova AG, Kondrashov FA, Ivankov DN. Self-consistency test reveals systematic bias in programs for prediction change of stability upon mutation. Bioinformatics. 2018; 34(21):3653-3658. DOI 10.1093/bioinformatics/bty340
dc.identifier.issn 1367-4803
dc.identifier.uri http://hdl.handle.net/10230/37290
dc.description.abstract Motivation: Computational prediction of the effect of mutations on protein stability is used by researchers in many fields. The utility of the prediction methods is affected by their accuracy and bias. Bias, a systematic shift of the predicted change of stability, has been noted as an issue for several methods, but has not been investigated systematically. Presence of the bias may lead to misleading results especially when exploring the effects of combination of different mutations. Results: Here we use a protocol to measure the bias as a function of the number of introduced mutations. It is based on a self-consistency test of the reciprocity the effect of a mutation. An advantage of the used approach is that it relies solely on crystal structures without experimentally measured stability values. We applied the protocol to four popular algorithms predicting change of protein stability upon mutation, FoldX, Eris, Rosetta and I-Mutant, and found an inherent bias. For one program, FoldX, we manage to substantially reduce the bias using additional relaxation by Modeller. Authors using algorithms for predicting effects of mutations should be aware of the bias described here. Availability and implementation: All calculations were implemented by in-house PERL scripts. Supplementary information: Supplementary data are available at Bioinformatics online.
dc.description.sponsorship This work was supported by the HHMI International Early Career Scientist Program [55007424], the MINECO [BFU2015-68723-P], Spanish Ministry of Economy and Competitiveness Centro de Excelencia Severo Ochoa 2013-2017 [grant SEV-2012-0208], Secretaria d'Universitats i Recerca del Departament d'Economia i Coneixement de la Generalitat’s AGAUR [program 2014 SGR 0974], the European Research Council under the European Union's Seventh Framework Programme [FP7/2007-2013, ERC grant agreement 335980_EinME] and Russian Scientific Foundation (RSF #14-24-00157, the part about I-Mutant calculations). The work was started at the School of Molecular and Theoretical Biology supported by the Dynasty Foundation.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Oxford University Press
dc.relation.ispartof Bioinformatics. 2018; 34(21):3653-3658
dc.rights © The Author(s) 2018. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/
dc.title Self-consistency test reveals systematic bias in programs for prediction change of stability upon mutation
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1093/bioinformatics/bty340
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/BFU2015-68723-P
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/335980
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account

Statistics

In collaboration with Compliant to Partaking