mCSM–NA: predicting the effects of mutations on protein–nucleic acids interactions

Abstract

Over the past two decades, several computational methods have been proposed to predict how missense mutations can affect protein structure and function, either by altering protein stability or interactions with its partners, shedding light into potential molecular mechanisms giving rise to different phenotypes. Effectively and efficiently predicting consequences of mutations on protein–nucleic acid interactions, however, remained until recently a great and unmet challenge. Here we report an updated webserver for mCSM–NA, the only scalable method we are aware of capable of quantitatively predicting the effects of mutations in protein coding regions on nucleic acid binding affinities. We have significantly enhanced the original method by including a pharmacophore modelling and information of nucleic acid properties into our graph-based signatures, considering the reverse mutation and by using a refined, more reliable data set, based on a new release of the ProNIT database, which has significantly improved the reliability and applicability of the methodology. Our new predictive model was capable of achieving a correlation coefficient of up to 0.70 on cross-validation and 0.68 on blind-tests, outperforming its previous version. The server is freely available via a user-friendly web interface at: http://structure.bioc.cam.ac.uk/mcsm_na.Jack Brockhoff Foundation [JBF 4186, 2016 to D.B.A.]; Newton Fund RCUK-CONFAP Grant awarded by The Medical Research Council (MRC) and Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG) [MR/M026302/1 to D.B.A. and D.E.V.P.]; National Health and Medical Research Council of Australia [APP1072476 to D.B.A.]; Victorian Life Sciences Computation Initiative (VLSCI), an initiative of the Victorian Government, Australia, on its Facility hosted at the University of Melbourne [UOM0017]; Centro de Pesquisas Rene Rachou (CPqRR/FIOCRUZ Minas), Brazil [to D.E.V.P.]; Department of Biochemistry and Molecular Biology, University of Melbourne [to D.B.A.]. Funding for open access charge: MRC