Hakmi Mohammed, Bouricha El Mehdi, Kandoussi Ilham, Harti Jaouad El, Ibrahimi Azeddine
Medical Biotechnology Laboratory (MedBiotech), Rabat Medical and Pharmacy School, Mohammed Vth University in Rabat, Morocco.
Therapeutic Chemistry Laboratory, Medical Biotechnology Laboratory (MedBiotech), Rabat Medical and Pharmacy School, Mohammed Vth University in Rabat, Morocco.
Bioinformation. 2020 Apr 30;16(4):301-306. doi: 10.6026/97320630016301. eCollection 2020.
The new SARS-CoV-2 coronavirus is the causative agent of the COVID-19 pandemic outbreak that affected more than 190 countries worldwide with more than 292,000 confirmed cases and over 12,700 deaths. There is at the moment no vaccine or effective treatment for this disease which constitutes a serious global health problem. It is of interest to use a structure based virtual screening approach for the identification of potential inhibitors of the main protease of SARS-CoV-2 (M) from antiviral drugs used to treat other viral disease such as human immunodeficiency virus (HIV) and hepatitis C virus (HCV) infections. The crystallographic structure with PDB ID: 6LU7 of M in complex with the inhibitor N3 was used as a model in the virtual screening of 33 protease inhibitors collected from the ChEMBL chemical database. Molecular docking analysis was performed using the standard AutoDock vina protocol followed by ranking and selection of compounds based on their binding affinity. We report 10 candidates with optimal binding features to the active site of the protease for further consideration as potential drugs to treat patients infected with the emerging COVID-19 disease.
新型严重急性呼吸综合征冠状病毒2(SARS-CoV-2)是导致新冠疫情爆发的病原体,该疫情已影响全球190多个国家,确诊病例超过29.2万例,死亡人数超过1.27万例。目前,针对这种疾病尚无疫苗或有效治疗方法,这构成了一个严重的全球健康问题。利用基于结构的虚拟筛选方法,从用于治疗其他病毒疾病(如人类免疫缺陷病毒(HIV)和丙型肝炎病毒(HCV)感染)的抗病毒药物中,识别SARS-CoV-2主要蛋白酶(M)的潜在抑制剂,这一点很有意义。在从ChEMBL化学数据库收集的33种蛋白酶抑制剂的虚拟筛选中,将与抑制剂N3复合的M的晶体结构(PDB ID:6LU7)用作模型。使用标准的AutoDock vina协议进行分子对接分析,然后根据化合物的结合亲和力对其进行排序和选择。我们报告了10种与蛋白酶活性位点具有最佳结合特征的候选物,可进一步考虑作为治疗感染新型新冠疾病患者的潜在药物。