Sims Peter A, Wong Chung F, McCammon J Andrew
Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093-0365, USA.
J Med Chem. 2003 Jul 17;46(15):3314-25. doi: 10.1021/jm0205043.
The cyclin-dependent protein kinases are important targets in drug discovery because of their role in cell cycle regulation. In this computational study, we have applied a continuum solvent model to study the interactions between cyclin-dependent kinase 2 (CDK2) and analogues of the clinically tested anticancer agent flavopiridol. The continuum solvent model uses Coulomb's law to account for direct electrostatic interactions, solves the Poisson equation to obtain the electrostatic contributions to solvation energy, and calculates scaled solvent-accessible surface area to account for hydrophobic interactions. The computed free energy of binding gauges the strength of protein-ligand interactions. Our model was first validated through a study on the binding of a number of flavopiridol derivatives to CDK2, and its ability to identify potent inhibitors was observed. The model was then used to aid in the design of novel CDK2 inhibitors with the aid of a computational sensitivity analysis. Some of these hypothetical structures could be significantly more potent than the lead compound flavopiridol. We applied two approaches to gain insights into designing selective inhibitors. One relied on the comparative analysis of the binding pocket for several hundred protein kinases to identify the parts of a lead compound whose modifications might lead to selective compounds. The other was based on building and using homology models for energy calculations. The homology models appear to be able to classify ligand potency into groups but cannot yet give reliable quantitative results.
细胞周期蛋白依赖性蛋白激酶因其在细胞周期调控中的作用而成为药物研发的重要靶点。在这项计算研究中,我们应用连续介质溶剂模型来研究细胞周期蛋白依赖性激酶2(CDK2)与临床测试的抗癌药物黄酮哌啶醇类似物之间的相互作用。连续介质溶剂模型利用库仑定律来解释直接静电相互作用,求解泊松方程以获得静电对溶剂化能的贡献,并计算缩放的溶剂可及表面积以解释疏水相互作用。计算得到的结合自由能衡量了蛋白质 - 配体相互作用的强度。我们的模型首先通过对多种黄酮哌啶醇衍生物与CDK2结合的研究进行了验证,并观察到其识别强效抑制剂的能力。然后,借助计算敏感性分析,该模型被用于辅助设计新型CDK2抑制剂。其中一些假设结构可能比先导化合物黄酮哌啶醇的活性显著更高。我们应用了两种方法来深入了解选择性抑制剂的设计。一种方法依赖于对数百种蛋白激酶结合口袋的比较分析,以确定先导化合物中哪些部分的修饰可能导致选择性化合物。另一种方法基于构建和使用同源模型进行能量计算。同源模型似乎能够将配体活性分类,但尚未能给出可靠的定量结果。