Journal article

pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures

Douglas EV Pires, Tom L Blundell, David B Ascher

JOURNAL OF MEDICINAL CHEMISTRY | AMER CHEMICAL SOC | Published : 2015

Abstract

Drug development has a high attrition rate, with poor pharmacokinetic and safety properties a significant hurdle. Computational approaches may help minimize these risks. We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. pkCSM performs as well or better than current methods. A freely accessible web server (http://structure.bioc.cam.ac.uk/pkcsm), which retains no information submitted to it, provides an integrated platform to rapidly evaluate pharmacokinetic and toxicity properties.

Grants

Awarded by NHMRC CJ Martin Fellowship


Awarded by MRC


Awarded by Biotechnology and Biological Sciences Research Council


Awarded by Medical Research Council


Funding Acknowledgements

Newton Fund RCUK-CONFAP grant awarded by The Medical Research Council (MRC) and Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG) [to D.E.V.P., T.L.B,. and D.B.A.]; Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), and Centro de Pesquisas Rene Rachou (CPqRR/FIOCRUZ Minas), Brazil [to D.E.V.P.]; NHMRC CJ Martin Fellowship [APP1072476 to D.B.A.]; University of Cambridge and The Wellcome Trust for facilities and support [to T.L.B.]. Funding for open access charge: The Wellcome Trust.