Schrödinger Inc, Quatro House, Frimley Road, Camberley, Surrey GU16 7ER, UK.
ChemMedChem. 2010 Apr 6;5(4):618-27. doi: 10.1002/cmdc.200900501.
Kinases remain an important drug target class within the pharmaceutical industry; however, the rational design of kinase inhibitors is plagued by the complexity of gaining selectivity for a small number of proteins within a family of more than 500 related enzymes. Herein we show how a computational method for identifying the location and thermodynamic properties of water molecules within a protein binding site can yield insight into previously inexplicable selectivity and structure-activity relationships. Four kinase systems (Src family, Abl/c-Kit, Syk/ZAP-70, and CDK2/4) were investigated, and differences in predicted water molecule locations and energetics were able to explain the experimentally observed binding selectivity profiles. The successful predictions across the range of kinases studied here suggest that this methodology could be generally applicable for predicting selectivity profiles in related targets.
激酶仍然是制药行业中一个重要的药物靶点类别；然而，激酶抑制剂的合理设计受到了获得家族中少数几种蛋白质选择性的复杂性的困扰，该家族有超过 500 种相关酶。本文展示了一种识别蛋白质结合位点内水分子位置和热力学性质的计算方法如何能够深入了解以前无法解释的选择性和结构-活性关系。研究了四个激酶系统（Src 家族、Abl/c-Kit、Syk/ZAP-70 和 CDK2/4），预测水分子位置和能量的差异能够解释实验观察到的结合选择性谱。在此研究范围内对激酶的成功预测表明，该方法可能普遍适用于预测相关靶标中的选择性谱。
