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.