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用于核酸结合候选药物的发现漏斗。

A Discovery Funnel for Nucleic Acid Binding Drug Candidates.

作者信息

Holt Patrick A, Buscaglia Robert, Trent John O, Chaires Jonathan B

机构信息

James Graham Brown Cancer Center, University of Louisville, 505 S. Hancock St., Louisville, KY 40202, USA.

出版信息

Drug Dev Res. 2011 Mar 1;72(2):178-186. doi: 10.1002/ddr.20414.

Abstract

Computational approaches are becoming increasingly popular for the discovery of drug candidates against a target of interest. Proteins have historically been the primary targets of many virtual screening efforts. While in silico screens targeting proteins has proven successful, other classes of targets, in particular DNA, remain largely unexplored using virtual screening methods. With the realization of the functional importance of many non-cannonical DNA structures such as G-quadruplexes, increased efforts are underway to discover new small molecules that can bind selectively to DNA structures. Here, we describe efforts to build an integrated in silico and in vitro platform for discovering compounds that may bind to a chosen DNA target. Millions of compounds are initially screened in silico for selective binding to a particular structure and ranked to identify several hundred best hits. An important element of our strategy is the inclusion of an array of possible competing structures in the in silico screen. The best hundred or so hits are validated experimentally for binding to the actual target structure by a high-throughput 96-well thermal denaturation assay to yield the top ten candidates. Finally, these most promising candidates are thoroughly characterized for binding to their DNA target by rigorous biophysical methods, including isothermal titration calorimetry, differential scanning calorimetry, spectroscopy and competition dialysis.This platform was validated using quadruplex DNA as a target and a newly discovered quadruplex binding compound with possible anti-cancer activity was discovered. Some considerations when embarking on virtual screening and in silico experiments are also discussed.

摘要

计算方法在发现针对感兴趣靶点的候选药物方面正变得越来越流行。蛋白质一直是许多虚拟筛选工作的主要靶点。虽然针对蛋白质的计算机模拟筛选已被证明是成功的,但其他类型的靶点,特别是DNA,在很大程度上仍未使用虚拟筛选方法进行探索。随着人们认识到许多非经典DNA结构(如G-四链体)的功能重要性,正在加大努力发现能够选择性结合DNA结构的新小分子。在此,我们描述了构建一个集成的计算机模拟和体外平台以发现可能结合选定DNA靶点的化合物的工作。最初在计算机模拟中对数百万种化合物进行筛选,以寻找与特定结构的选择性结合,并进行排名以确定数百个最佳命中物。我们策略的一个重要元素是在计算机模拟筛选中纳入一系列可能的竞争结构。通过高通量96孔热变性测定法对约一百个最佳命中物进行实验验证,以确定它们与实际靶点结构的结合情况,从而得到前十名候选物。最后,通过严格的生物物理方法,包括等温滴定量热法、差示扫描量热法、光谱学和竞争透析法,对这些最有前景的候选物与它们的DNA靶点的结合进行全面表征。该平台以四链体DNA为靶点进行了验证,并发现了一种新的具有可能抗癌活性的四链体结合化合物。文中还讨论了开展虚拟筛选和计算机模拟实验时的一些注意事项。

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