Abstract

A computational approach to in silico drug discovery was carried out to identify small drug-like compounds able to show structural and functional mimicry of the high affinity ligand X77, potent non-covalent inhibitor of SARS-COV-2 main protease (M^Pro). In doing so, the X77-mimetic candidates were predicted based on the crystal X77-M^Pro structure by a public web-oriented virtual screening platform Pharmit. Models of these candidates bound to SARS-COV-2 M^Pro were generated by molecular docking, quantum chemical calculations and molecular dynamics simulations. At the final point, analysis of the interaction modes of the identified compounds with M^Pro and prediction of their binding affinity were carried out. Calculation revealed 5 top-ranking compounds that exhibited a high affinity to the active site of SARS-CoV-2 M^Pro. Insights into the ligand − M^Pro models indicate that all identified compounds may effectively block the binding pocket of SARS-CoV-2 M^Pro, in line with the low values ​​of binding free energy and dissociation constant. Mechanism of binding of these compounds to M^Pro is mainly provided by van der Waals interactions with the functionally important residues of the enzyme, such as His-41, Met-49, Cys-145, Met-165, and Gln-189 that play a role of the binding hot spots assisting the predicted molecules to effectively interact with the M^Pro active site. The data obtained show that the identified X77-mimetic candidates may serve as good scaffolds for the design of novel antiviral agents able to target the active site of SARS-CoV-2 M^Pro.

Communicated by Ramaswamy H. Sarma

摘要

进行了计算机药物发现的计算方法，以鉴定能够显示出高亲和力配体 X77（SARS-COV-2 主要蛋白酶 (M ^Pro ) 的有效非共价抑制剂）的结构和功能模拟的小类药物化合物。在此过程中，公共面向网络的虚拟筛选平台 Pharmit基于水晶 X77-M ^Pro结构预测了 X77 模拟候选物。这些候选药物与 SARS-COV-2 M ^Pro结合的模型是通过分子对接、量子化学计算和分子动力学模拟生成的。最后，分析鉴定化合物与 M ^Pro的相互作用模式并预测了它们的结合亲和力。计算显示 5 种顶级化合物对 SARS-CoV-2 M ^Pro的活性位点表现出高亲和力。对配体 - M ^Pro模型的洞察表明，所有已鉴定的化合物都可以有效地阻断 SARS-CoV-2 M ^Pro的结合口袋，这与结合自由能和解离常数的低值一致。这些化合物与 M ^Pro的结合机制主要是通过范德华力与酶的功能上重要的残基相互作用提供的，例如发挥作用的 His-41、Met-49、Cys-145、Met-165 和 Gln-189结合热点的作用有助于预测分子与 M ^Pro有效相互作用活动站点。获得的数据表明，确定的 X77 模拟候选物可以作为设计能够靶向 SARS-CoV-2 M ^Pro活性位点的新型抗病毒药物的良好支架。

由 Ramaswamy H. Sarma 交流