pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures
Douglas E. V. PiresDepartment
of Biochemistry, University of Cambridge, 80 Tennis Court Road, Sanger Building, Cambridge, Cambridgshire CB2 1GA, U.KTom L. BlundellDepartment
of Biochemistry, University of Cambridge, 80 Tennis Court Road, Sanger Building, Cambridge, Cambridgshire CB2 1GA, U.KDavid B. AscherDepartment
of Biochemistry, University of Cambridge, 80 Tennis Court Road, Sanger Building, Cambridge, Cambridgshire CB2 1GA, U.K
2015en
Ochiq kirishGibrid
Litsenziya: cc-by
ABI
Annotatsiya
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.
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