Karaman Mazen W, Herrgard Sanna, Treiber Daniel K, Gallant Paul, Atteridge Corey E, Campbell Brian T, Chan Katrina W, Ciceri Pietro, Davis Mindy I, Edeen Philip T, Faraoni Raffaella, Floyd Mark, Hunt Jeremy P, Lockhart Daniel J, Milanov Zdravko V, Morrison Michael J, Pallares Gabriel, Patel Hitesh K, Pritchard Stephanie, Wodicka Lisa M, Zarrinkar Patrick P
Ambit Biosciences, 4215 Sorrento Valley Blvd., San Diego, California 92121, USA.
Nat Biotechnol. 2008 Jan;26(1):127-32. doi: 10.1038/nbt1358.
Kinase inhibitors are a new class of therapeutics with a propensity to inhibit multiple targets. 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. 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.
激酶抑制剂是一类新型治疗药物,倾向于抑制多个靶点。多激酶活性的生物学后果尚不清楚,而理解选择性、疗效和安全性之间关系的重要一步是探索抑制剂如何与人类激酶组相互作用。我们展示了38种激酶抑制剂与一组317种激酶的相互作用图谱,这些激酶占预测人类蛋白激酶组的50%以上。这些数据构成了迄今为止对激酶抑制剂选择性最全面的研究,并揭示了广泛多样的相互作用模式。为了对结果进行全局分析,我们引入了选择性评分的概念,作为量化和区分观察到的相互作用模式的通用工具。我们进一步研究了检测组大小的影响,发现小检测组不能提供可靠的选择性测量。