Evaluation of docking performance: Comparative data on docking algorithms
Evaluation of docking performance: Comparative data on docking algorithms
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DOI：
10.1021/jm0302997
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发表时间：
2004-01-29
影响因子：
7.3
通讯作者：
Sokol, GS
中科院分区：
文献类型：
--
作者：
Kontoyianni, M;McClellan, LM;Sokol, GS
将分子对接到各自的三维大分子靶标中是一种广泛使用的铅优化方法。然而，最著名的对接算法往往无法将配体定位在接近实验结合模式的方向上。最近有报道称，在一项虚拟筛选实验中，共识评分可以提高命中率。这种方法专注于排名靠前的姿势，潜在的假设是停靠的化合物的方向/构象是最准确的。为了消除评分函数偏差，并评估对接算法提供类似于晶体模式的解决方案的能力，我们调查了最已知的对接程序，并评估了所有结果姿势。我们介绍了一项广泛的计算研究的结果，其中五个对接程序(Flexx，DOCK，GOLD，LigandFit，Glide)针对14个蛋白质家族(69个靶标)进行了研究。我们的发现表明，一些算法的性能始终好于其他算法，并且可以找到活动站点的性质和最佳停靠算法之间的对应关系。
Docking molecules into their respective 3D macromolecular targets is a widely used method for lead optimization. However, the best known docking algorithms often fail to position the ligand in an orientation close to the experimental binding mode. It was reported recently that consensus scoring enhances the hit rates in a virtual screening experiment. This methodology focused on the top-ranked pose, with the underlying assumption that the orientation/conformation of the docked compound is the most accurate. In an effort to eliminate the scoring function bias, and assess the ability of the docking algorithms to provide solutions similar to the crystallographic modes, we investigated the most known docking programs and evaluated all of the resultant poses. We present the results of an extensive computational study in which five docking programs (FlexX, DOCK, GOLD, LigandFit, Glide) were investigated against 14 protein families (69 targets). Our findings show that some algorithms perform consistently better than others, and a correspondence between the nature of the active site and the best docking algorithm can be found.