PAIN(S) relievers for medicinal chemists: how computational methods can assist in hit evaluation

被引：10

作者：

Stork, Conrad ^{[1
]}

Kirchmair, Johannes ^{[1
]}

机构：

[1] Univ Hamburg, Fac Math Informat & Nat Sci, Ctr Bioinformat, Dept Comp Sci, D-20146 Hamburg, Germany

来源：

FUTURE MEDICINAL CHEMISTRY | 2018年 / 10卷 / 13期

关键词：

aggregators; frequent hitters; in silico prediction; in vitro screening; machine learning; molecular similarity; PAINS; promiscuous compounds; rule-based approaches; statistical methods; ASSAY INTERFERENCE COMPOUNDS; ECSTASY; AGONY;

D O I：

10.4155/fmc-2018-0116

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

[No abstract available]

引用

页码：1533 / 1535

页数：3

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