Bursulaya Badry D, Totrov Maxim, Abagyan Ruben, Brooks Charles L
Department of Molecular Biology (TPC6), The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA.
J Comput Aided Mol Des. 2003 Nov;17(11):755-63. doi: 10.1023/b:jcam.0000017496.76572.6f.
We have performed a comparative assessment of several programs for flexible molecular docking: DOCK 4.0, FlexX 1.8, AutoDock 3.0, GOLD 1.2 and ICM 2.8. This was accomplished using two different studies: docking experiments on a data set of 37 protein-ligand complexes and screening a library containing 10,037 entries against 11 different proteins. The docking accuracy of the methods was judged based on the corresponding rank-one solutions. We have found that the fraction of molecules docked with acceptable accuracy is 0.47, 0.31, 0.35, 0.52 and 0.93 for, respectively, AutoDock, DOCK, FlexX, GOLD and ICM. Thus ICM provided the highest accuracy in ligand docking against these receptors. The results from the other programs are found to be less accurate and of approximately the same quality. A speed comparison demonstrated that FlexX was the fastest and AutoDock was the slowest among the tested docking programs. The database screening was performed using DOCK, FlexX and ICM. ICM was able to identify the original ligands within the top 1% of the total library in 17 cases. The corresponding number for DOCK and FlexX was 7 and 8, respectively. We have estimated that in virtual database screening, 50% of the potentially active compounds will be found among approximately 1.5% of the top scoring solutions found with ICM and among approximately 9% of the top scoring solutions produced by DOCK and FlexX.
DOCK 4.0、FlexX 1.8、AutoDock 3.0、GOLD 1.2和ICM 2.8。这是通过两项不同的研究完成的:对一组包含37个蛋白质-配体复合物的数据集进行对接实验,以及针对11种不同蛋白质筛选一个包含10037个条目的文库。根据相应的排名第一的解决方案来判断这些方法的对接准确性。我们发现,对于AutoDock、DOCK、FlexX、GOLD和ICM,以可接受的准确性对接的分子比例分别为0.47、0.31、0.35、0.52和0.93。因此,ICM在针对这些受体的配体对接中提供了最高的准确性。发现其他程序的结果准确性较低且质量大致相同。速度比较表明,在测试的对接程序中,FlexX最快,AutoDock最慢。使用DOCK、FlexX和ICM进行数据库筛选。ICM能够在17例中在文库总数的前1%内识别出原始配体。DOCK和FlexX的相应数字分别为7和8。我们估计,在虚拟数据库筛选中,约50%的潜在活性化合物将在ICM找到的约1.5%的最高得分解决方案中以及DOCK和FlexX产生的约9%的最高得分解决方案中被发现。