Department of Chemistry and Institute for Nanotechnology & Advanced Materials, Bar-Ilan University, Ramat-Gan 52900, Israel.
J Chem Inf Model. 2021 Jun 28;61(6):2957-2966. doi: 10.1021/acs.jcim.1c00263. Epub 2021 May 28.
The coronavirus SARS-CoV-2 main protease, M, is conserved among coronaviruses with no human homolog and has therefore attracted significant attention as an enzyme drug target for COVID-19. The number of studies targeting M for in silico screening has grown rapidly, and it would be of great interest to know in advance how well docking methods can reproduce the correct ligand binding modes and rank these correctly. Clearly, current attempts at designing drugs targeting M with the aid of computational docking would benefit from a priori knowledge of the ability of docking programs to predict correct binding modes and score these correctly. In the current work, we tested the ability of several leading docking programs, namely, Glide, DOCK, AutoDock, AutoDock Vina, FRED, and EnzyDock, to correctly identify and score the binding mode of M ligands in 193 crystal structures. None of the codes were able to correctly identify the crystal structure binding mode (lowest energy pose with root-mean-square deviation < 2 Å) in more than 26% of the cases for noncovalently bound ligands (Glide: top performer), whereas for covalently bound ligands the top score was 45% (EnzyDock). These results suggest that one should perform in silico campaigns of M with care and that more comprehensive strategies including ligand free energy perturbation might be necessary in conjunction with virtual screening and docking.
冠状病毒 SARS-CoV-2 的主要蛋白酶 M 在冠状病毒中是保守的，没有人类同源物，因此作为 COVID-19 的酶药物靶点引起了极大的关注。针对 M 进行计算机筛选的研究数量迅速增加，如果事先知道对接方法能在多大程度上重现正确的配体结合模式并正确对其进行排序，这将非常有趣。显然，目前借助计算对接设计针对 M 的药物的尝试将受益于对接程序预测正确结合模式和正确评分的能力的先验知识。在当前的工作中，我们测试了几种领先的对接程序，即 Glide、DOCK、AutoDock、AutoDock Vina、FRED 和 EnzyDock，以正确识别和评分 193 个晶体结构中 M 配体的结合模式。在非共价结合配体的情况下（Glide：表现最好），没有一个代码能够正确识别超过 26%的晶体结构结合模式（最低能量构象，均方根偏差 < 2 Å），而对于共价结合配体，最高得分为 45%（EnzyDock）。这些结果表明，人们应该谨慎地进行 M 的计算机筛选，并且可能需要更全面的策略，包括配体自由能扰动，结合虚拟筛选和对接。
