使用对接和FPL模拟快速预测新型冠状病毒主要蛋白酶的潜在抑制剂
Rapid prediction of possible inhibitors for SARS-CoV-2 main protease using docking and FPL simulations.
作者信息
Pham Minh Quan, Vu Khanh B, Han Pham T Ngoc, Thuy Huong Le Thi, Tran Linh Hoang, Tung Nguyen Thanh, Vu Van V, Nguyen Trung Hai, Ngo Son Tung
机构信息
Graduate University of Science and Technology, Vietnam Academy of Science and Technology Hanoi Vietnam.
Institute of Natural Products Chemistry, Vietnam Academy of Science and Technology Hanoi Vietnam.
出版信息
RSC Adv. 2020 Aug 28;10(53):31991-31996. doi: 10.1039/d0ra06212j. eCollection 2020 Aug 26.
Originating for the first time in Wuhan, China, the outbreak of SARS-CoV-2 has caused a serious global health issue. An effective treatment for SARS-CoV-2 is still unavailable. Therefore, in this study, we have tried to predict a list of potential inhibitors for SARS-CoV-2 main protease (Mpro) using a combination of molecular docking and fast pulling of ligand (FPL) simulations. The approaches were initially validated over a set of eleven available inhibitors. Both Autodock Vina and FPL calculations produced consistent results with the experiments with correlation coefficients of = 0.72 ± 0.14 and = -0.76 ± 0.10, respectively. The combined approaches were then utilized to predict possible inhibitors that were selected from a ZINC15 sub-database for SARS-CoV-2 Mpro. Twenty compounds were suggested to be able to bind well to SARS-CoV-2 Mpro. Among them, five top-leads are , , , , and . The obtained results could probably lead to enhance the COVID-19 therapy.
严重急性呼吸综合征冠状病毒2（SARS-CoV-2）首次在中国武汉爆发，已引发严重的全球健康问题。目前仍没有针对SARS-CoV-2的有效治疗方法。因此，在本研究中，我们尝试结合分子对接和配体快速拉动（FPL）模拟来预测一系列SARS-CoV-2主要蛋白酶（Mpro）的潜在抑制剂。这些方法首先在一组11种可用抑制剂上进行了验证。自动对接Vina和FPL计算与实验结果一致，相关系数分别为 = 0.72 ± 0.14和 = -0.76 ± 0.10。然后，利用这些组合方法从SARS-CoV-2 Mpro的ZINC15子数据库中预测可能的抑制剂。有20种化合物被认为能够与SARS-CoV-2 Mpro良好结合。其中，五个顶级先导物分别是 、 、 、 和 。所得结果可能有助于加强对2019冠状病毒病的治疗。
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