新冠病毒SARS-CoV-2主蛋白酶3CLpro抑制剂的多步虚拟筛选

目的 通过构建多步虚拟筛选模型和方法，寻找有效筛选新冠状病毒SARS-CoV-2主蛋白酶3CLpro抑制剂的方法，为抗击COVID-19提供去潜在的候选药物。方法 利用Discovery Studio Client 2016和AutoDock Vina 1.5.6软件对ZINC 数据库共5811个化合物进行基于结构的虚拟筛选，然后基于配体的药效团模型，选取最佳模型后进行基于配体的虚拟筛选，最后基于构效关系筛选出与抗病毒有关的药物。结果 经过3步筛选最终得到11个具有高亲和力、高拟合值和适当药理作用的化合物。结论 通过3种不同方法的多步筛选可以快速寻找出具有高活性的候选化合物，表明构建的虚拟筛选的方法和模型有效，为今后抗COVID-19药物研究提供了潜在的研究工具。

Multi-step virtual screening for searching the 3Clpro inhibitor of the main protease of the new coronavirus SRAS-CoV-2

Objective To construct a multi-step virtual screening model and method to find an effective method for screening the 3Clpro inhibitor of the main protease of the new coronavirus SARS-CoV-2, so as to provide potential candidate drugs for COVID-19 drug research.Methods Discovery Studio Client 2016 and Autodock vina 1.5.6 software were used to conduct structural-based virtual screening of 5811 compounds from the ZINC database, and the ligand-based pharmacophore model was constructed. After selecting the best model, the ligand-based virtual screening was performed. Finally, the antiviral drugs were screened based on pharmacological effects.Results After three steps of screening, 11 compounds with high affinity, high fitting value and appropriate pharmacological effects were finally obtained.Conclusion After three different screening, the candidate compounds with high activity can be quickly found, indicating that the virtual screening method and model are effective, which will greatly reduce the range of drug screening against COVID-19 and provide potential research tools for future COVID-19 drug discovery.