Maiorov Vladimir, Sheridan Robert P
Molecular Systems, Merck Research Laboratories, Merck and Co., Inc., RY50SW-100, P.O. Box 2000, Rahway, New Jersey 07065, USA.
J Chem Inf Model. 2005 Jul-Aug;45(4):1017-23. doi: 10.1021/ci050089y.
Flexible ligand docking is a routine part of a modern structure-based lead discovery process. As of today, there are quite a number of commercial docking programs that can be used to screen large databases (hundreds of thousands to millions of compounds). However, limiting factors such as the number of commercial software licenses needed to perform docking simultaneously on multiple processors ("software cost") and the relatively long time required per molecule to get good results ("quality-to-speed") should be taken into account when planning a large docking run. How can we optimize the efficiency of selecting lead candidates by docking, in respect to the quality of the results, search speed, and software cost? We present a combination of two methods, our "fast-free-approximate" in-house docking program and the "slow-costly-accurate" ICM-Dock, as an example of one solution to the problem. Our proposed protocol is illustrated by a series of virtual screening experiments aimed at identifying active compounds in the MDL Drug Data Report database. In more than half of the 20 cases examined, at least several actives per protein target were identified in approximately 24 hours per target.
灵活配体对接是现代基于结构的先导化合物发现过程中的常规部分。截至目前，有相当多的商业对接程序可用于筛选大型数据库（数十万到数百万种化合物）。然而，在规划大型对接运行时，需要考虑一些限制因素，例如在多个处理器上同时进行对接所需的商业软件许可证数量（“软件成本”）以及每个分子获得良好结果所需的相对较长时间（“质量与速度”）。就结果质量、搜索速度和软件成本而言，我们如何通过对接来优化选择先导候选物的效率？我们提出了两种方法的组合，即我们的“快速免费近似”内部对接程序和“慢速昂贵精确”的ICM-Dock，作为该问题的一种解决方案示例。我们通过一系列虚拟筛选实验来说明我们提出的方案，这些实验旨在在MDL药物数据报告数据库中识别活性化合物。在所研究的20个案例中，超过一半的案例中，每个蛋白质靶点在大约24小时内至少鉴定出了几种活性化合物。
