4.7 Article

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

期刊

JOURNAL OF MEDICINAL CHEMISTRY
卷 58, 期 9, 页码 4066-4072

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jmedchem.5b00104

关键词

-

资金

  1. Medical Research Council (MRC)
  2. Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG)
  3. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)
  4. Centro de Pesquisas Rene Rachou (CPqRR/FIOCRUZ Minas), Brazil
  5. NHMRC CJ Martin Fellowship [APP1072476]
  6. University of Cambridge
  7. Wellcome Trust
  8. Biotechnology and Biological Sciences Research Council [1103577] Funding Source: researchfish
  9. Medical Research Council [MR/M026302/1, MR/N501864/1] Funding Source: researchfish
  10. MRC [MR/M026302/1, MR/N501864/1] Funding Source: UKRI

向作者/读者索取更多资源

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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据