药代动力学
化学
毒性
损耗
图形
计算机科学
药理学
理论计算机科学
医学
有机化学
牙科
作者
Douglas E. V. Pires,Tom L. Blundell,David B. Ascher
标识
DOI:10.1021/acs.jmedchem.5b00104
摘要
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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