Qi Xinyu, Li Binglin, Omarini Alejandra B, Gand Martin, Zhang Xiaoli, Wang Jiao
College of Food Science and Engineering, Northwest University, 229 North Taibai Road, Xi'an, 710000, Shaanxi, China.
Institute of Earth and Environmental Sciences of La Pampa, Universidad Nacional de La Pampa, Mendoza 109, L6300DUG, Santa Rosa, La Pampa, Argentina.
J Mol Struct. 2022 Nov 15;1268:133709. doi: 10.1016/j.molstruc.2022.133709. Epub 2022 Jul 12.
The rapidly evolving Coronavirus Disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide with thousands of deaths and infected cases. For the identification of effective treatments against this disease, the main protease (M) of SARS‑CoV‑2 was found to be an attractive drug target, as it played a central role in viral replication and transcription. Here, we report the results of high-throughput molecular docking with 1,045,468 ligands' structures from 116 kinds of traditional Chinese medicine (TCM). Subsequently, 465 promising candidates were obtained, showing high binding affinities. The dynamic simulation, ADMET (absorption, distribution, metabolism, excretion and toxicity) and drug-likeness properties were further analyzed the screened docking results. Basing on these simulation results, 23 kinds of Chinese herbal extracts were employed to study their inhibitory activity for M of SARS‑CoV‑2. Plants extracts from showed acceptable inhibitory efficiencies, which were over 70%. The best candidate was , reaching 78.9%.
由严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引起的2019年冠状病毒病(COVID-19)疫情迅速演变,已在全球范围内蔓延,造成数千人死亡和感染病例。为了确定针对这种疾病的有效治疗方法,发现SARS-CoV-2的主要蛋白酶(M)是一个有吸引力的药物靶点,因为它在病毒复制和转录中起着核心作用。在此,我们报告了对116种中药的1,045,468个配体结构进行高通量分子对接的结果。随后,获得了465个有前景的候选物,显示出高结合亲和力。对筛选出的对接结果进一步分析了动态模拟、ADMET(吸收、分布、代谢、排泄和毒性)和类药性质。基于这些模拟结果,采用23种中草药提取物研究它们对SARS-CoV-2 M的抑制活性。来自[具体植物]的植物提取物显示出可接受的抑制效率,超过70%。最佳候选物是[具体植物提取物],达到78.9%。