A quantitative analysis of kinase inhibitor selectivity

被引：1995

作者：

Karaman, Mazen W. ^{[1
]}

Herrgard, Sanna ^{[1
]}

Treiber, Daniel K. ^{[1
]}

Gallant, Paul ^{[1
]}

Atteridge, Corey E. ^{[1
]}

Campbell, Brian T. ^{[1
]}

Chan, Katrina W. ^{[1
]}

Ciceri, Pietro ^{[1
]}

Davis, Mindy I. ^{[1
]}

Edeen, Philip T. ^{[1
]}

Faraoni, Raffaella ^{[1
]}

Floyd, Mark ^{[1
]}

Hunt, Jeremy P. ^{[1
]}

Lockhart, Daniel J. ^{[1
]}

Milanov, Zdravko V. ^{[1
]}

Morrison, Michael J. ^{[1
]}

Pallares, Gabriel ^{[1
]}

Patel, Hitesh K. ^{[1
]}

Pritchard, Stephanie ^{[1
]}

Wodicka, Lisa M. ^{[1
]}

Zarrinkar, Patrick P. ^{[1
]}

机构：

[1] Ambit Biosci, San Diego, CA 92121 USA

来源：

NATURE BIOTECHNOLOGY | 2008年 / 26卷 / 01期

关键词：

D O I：

10.1038/nbt1358

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

Kinase inhibitors are a new class of therapeutics with a propensity to inhibit multiple targets(1,2). The biological consequences of multi-kinase activity are poorly defined, and an important step toward understanding the relationship between selectivity, efficacy and safety is the exploration of how inhibitors interact with the human kinome(2-4). We present interaction maps for 38 kinase inhibitors across a panel of 317 kinases representing >50% of the predicted human protein kinome. The data constitute the most comprehensive study of kinase inhibitor selectivity to date and reveal a wide diversity of interaction patterns. To enable a global analysis of the results, we introduce the concept of a selectivity score as a general tool to quantify and differentiate the observed interaction patterns. We further investigate the impact of panel size and find that small assay panels do not provide a robust measure of selectivity.

引用

页码：127 / 132

页数：6

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