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首页> 外文期刊>Journal of Medicinal Chemistry >pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures
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pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures

机译:pkCSM:使用基于图的签名预测小分子药代动力学和毒性

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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.
机译:药物开发的损耗率很高,药物动力学和安全性较差是一大障碍。计算方法可能有助于最小化这些风险。我们已经开发了一种新颖的方法(pkCSM),该方法使用基于图形的签名来开发用于药物开发的ADMET中心属性的预测模型。pkCSM的性能与现有方法相同或更好。可免费访问的Web服务器(http://structure.bioc.cam.ac.uk/pkcsm)不保留提交给它的信息,它提供了一个集成的平台来快速评估药代动力学和毒性。

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