Computational evaluation of protein-small molecule binding.
Computational evaluation of protein-small molecule binding.
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DOI：
10.1016/j.sbi.2008.11.009
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发表时间：
2009-02
影响因子：
6.8
通讯作者：
MacKerell, Alexander D., Jr.
中科院分区：
文献类型：
--
作者：
Guvench, Olgun;MacKerell, Alexander D., Jr.
确定蛋白质-小分子结合亲和力是当今合理药物发现的关键组成部分。为了避免与实验性蛋白质-小分子结合测定相关的时间、劳动力和材料成本，已经开发了多种基于结构的计算方法用于确定蛋白质-小分子结合亲和力。这些方法可以分为两类：准确但缓慢（类1）和快速但近似（类2）。类1的方法，明确考虑到蛋白质的灵活性，并包括一个原子级的溶剂化的描述，能够定量再现实验蛋白质-小分子的绝对结合自由能。然而，1类计算要求使得针对蛋白质筛选数千至数百万个小分子（如合理药物设计所需）在可预见的未来是不可行的。另一方面，第2类方法足够快以进行这种抑制剂筛选，但它们对蛋白质柔性和溶剂化的描述有限，这反过来限制了它们通过计算结合亲和力选择和排序小分子的能力。本文综述了1类和2类方法的概述，2类方法的研究途径，旨在使他们更接近1类的准确性，以及中间方法，结合1类和2类方法的特点。
Determining protein – small molecule binding affinity is a key component of present-day rational drug discovery. To circumvent the time, labor, and materials costs associated with experimental protein – small molecule binding assays, a variety of structure-based computational methods have been developed for determining protein – small molecule binding affinities. These methods can be placed in one of two classes: accurate but slow (Class 1), and fast but approximate (Class 2). Class 1 methods, which explicitly take into account protein flexibility and include an atomic-level description of solvation, are capable of quantitatively reproducing experimental protein – small molecule absolute binding free energies. However, Class 1 computational requirements make screening thousands to millions of small molecules against a protein, as required for rational drug design, infeasible for the foreseeable future. Class 2 methods, on the other hand, are sufficiently fast to perform such inhibitor screening, yet they suffer from limited descriptions of protein flexibility and solvation, which in turn limit their ability to select and rank-order small molecules by computed binding affinities. This review presents an overview of Class 1 and Class 2 methods, avenues of research in Class 2 methods aimed at bringing them closer to Class 1 accuracy, and intermediate approaches that incorporate features of both Class 1 and Class 2 methods.
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