Journal article

mmCSM-PPI: predicting the effects of multiple point mutations on protein-protein interactions

Carlos HM Rodrigues, Douglas E Pires, David B Ascher



Protein-protein interactions play a crucial role in all cellular functions and biological processes and mutations leading to their disruption are enriched in many diseases. While a number of computational methods to assess the effects of variants on protein-protein binding affinity have been proposed, they are in general limited to the analysis of single point mutations and have been shown to perform poorly on independent test sets. Here, we present mmCSM-PPI, a scalable and effective machine learning model for accurately assessing changes in protein-protein binding affinity caused by single and multiple missense mutations. We expanded our well-established graph-based signatures in order to ..

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Awarded by Newton Fund RCUK-CONFAP - Medical Research Council

Awarded by Jack Brockhoff Foundation

Awarded by National Health and Medical Research Council (NHMRC) of Australia

Funding Acknowledgements

Melbourne Research Scholarship (to C.H.M.R.); Newton Fund RCUK-CONFAP Grant awarded by the Medical Research Council [MR/M026302/1 to D.B.A. and D.E.V.P.]; Jack Brockhoff Foundation [JBF 4186, 2016]; Investigator Grant from the National Health and Medical Research Council (NHMRC) of Australia [GNT1174405]; Victorian Government's Operational Infrastructure Support Program (in part). Funding for open access charge: MRC.