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Rapid prediction of possible inhibitors for SARS-CoV-2 main protease using docking and FPL simulations

机译：使用对接和FPL模拟的SARS-COV-2主要蛋白酶可能抑制剂的快速预测

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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 R _(Dock) = 0.72 ± 0.14 and R _(W) = ?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 periandrin V , penimocycline , cis-p-Coumaroylcorosolic acid , glycyrrhizin , and uralsaponin B . The obtained results could probably lead to enhance the COVID-19 therapy.
机译：在中国武汉首次起初，SARS-COV-2爆发造成了严重的全球卫生问题。对SARS-COV-2的有效治疗仍然无法使用。因此，在本研究中，我们尝试使用分子对接和快速拉动配体（FPL）模拟的组合来预测SARS-COV-2主要蛋白酶（MPRO）的潜在抑制剂列表。最初通过一组11可用抑制剂验证该方法。 Autodock Vina和FPL计算分别为R _（码头）= 0.72±0.14和R _（W）=Δ0.76±0.10的相关系数的实验产生了一致的结果。然后利用组合的方法来预测从锌15副库中选择的抑制剂，用于SARS-COV-2 MPRO。建议二十种化合物能够与SARS-COV-2 MPRO结合。其中，五个顶序是紫花苷V，Phimocycline，CIS-P-COUMAROYLCOROSIC酸，甘草蛋白和乌拉瓦彭林B。获得的结果可能导致增强Covid-19治疗。

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