Journal article
Kinact: A computational approach for predicting activating missense mutations in protein kinases
CHM Rodrigues, DB Ascher, DEV Pires
Nucleic Acids Research | OXFORD UNIV PRESS | Published : 2018
DOI: 10.1093/nar/gky375
Open access
Abstract
Protein phosphorylation is tightly regulated due to its vital role in many cellular processes. While gain of function mutations leading to constitutive activation of protein kinases are known to be driver events of many cancers, the identification of these mutations has proven challenging. Here we present Kinact, a novel machine learning approach for predicting kinase activating missense mutations using information from sequence and structure. By adapting our graph-based signatures, Kinact represents both structural and sequence information, which are used as evidence to train predictive models. We show the combination of structural and sequence features significantly improved the overall ac..
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Awarded by Medical Research Council
Funding Acknowledgements
Australian Government Research Training Program Scholarship [to C.H.M.R]; 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]; Instituto Rene Rachou (IRR/FIOCRUZ Minas), Brazil and Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) [to D.E.V.P.]; Department of Biochemistry and Molecular Biology, University of Melbourne [to D.B.A.]. Funding for open access charge: Instituto Rene Rachou (IRR/FIOCRUZ Minas).