Department of Chemistry and Biochemistry and Center for Nanoscience, University of Missouri-Saint Louis, One University Boulevard, St. Louis, Missouri 63121, USA.
Curr Pharm Des. 2013;19(26):4739-54. doi: 10.2174/1381612811319260006.
This article reviews some of our experiences on applying computational techniques to aid the design of drugs targeting protein kinases and phosphatases. It is not a comprehensive review. Rather, it focuses on several less explored approaches or ideas that we have experiences on. It reviews some recent improvements on the Poisson-Boltzmann/Surface Area model for calculating binding affinity and discusses ways to perform calculations that are more tolerant to statistical and systematic errors. Several new ways to incorporate protein flexibility in molecular docking and estimating binding affinity are also discussed. Its discussions also go beyond binding affinity to considering drug-binding kinetics, not only on investigating protein-ligand interactions in isolation, but also on accounting for upstream and downstream influences that can occur in cells, through kinetic modeling of cell signaling. This review also describes a quick molecular simulation method for understanding drug-binding kinetics at the molecular level, with the hope of generating guiding principles for designing drugs with the desired kinetic properties. Sources of drug-binding selectivity that appear obvious but often overlooked are also discussed.
本文回顾了我们在应用计算技术辅助设计针对蛋白激酶和磷酸酶的药物方面的一些经验。这不是一篇全面的综述。相反,它侧重于我们有经验的几种探索较少的方法或思路。本文回顾了泊松-玻尔兹曼/表面积模型在计算结合亲和力方面的一些最新改进,并讨论了如何进行更能容忍统计和系统误差的计算。还讨论了几种在分子对接和估计结合亲和力中纳入蛋白质柔性的新方法。其讨论也超越了结合亲和力,考虑了药物结合动力学,不仅在孤立地研究蛋白质-配体相互作用时如此,而且还考虑了通过细胞信号转导的动力学建模,在细胞中可能发生的上游和下游影响。本文还描述了一种快速的分子模拟方法,用于在分子水平上理解药物结合动力学,希望为设计具有所需动力学特性的药物提供指导原则。本文还讨论了一些明显但经常被忽视的药物结合选择性的来源。