Arafet Kemel, Serrano-Aparicio Natalia, Lodola Alessio, Mulholland Adrian J, González Florenci V, Świderek Katarzyna, Moliner Vicent
Departament de Química Física i Analítica, Universitat Jaume I 12071 Castelló Spain
Dipartimento di Scienze degli Alimenti e del Farmaco, Università degli Studi di Parma Italy.
Chem Sci. 2020 Nov 27;12(4):1433-1444. doi: 10.1039/d0sc06195f.
The SARS-CoV-2 main protease (M) is essential for replication of the virus responsible for the COVID-19 pandemic, and one of the main targets for drug design. Here, we simulate the inhibition process of SARS-CoV-2 M with a known Michael acceptor (peptidyl) inhibitor, . The free energy landscape for the mechanism of the formation of the covalent enzyme-inhibitor product is computed with QM/MM molecular dynamics methods. The simulations show a two-step mechanism, and give structures and calculated barriers in good agreement with experiment. Using these results and information from our previous investigation on the proteolysis reaction of SARS-CoV-2 M, we design two new, synthetically accessible -analogues as potential inhibitors, in which the recognition and warhead motifs are modified. QM/MM modelling of the mechanism of inhibition of M by these novel compounds indicates that both may be promising candidates as drug leads against COVID-19, one as an irreversible inhibitor and one as a potential reversible inhibitor.
严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)主要蛋白酶(M)对于引发新冠疫情的病毒复制至关重要,也是药物设计的主要靶点之一。在此,我们用一种已知的迈克尔受体(肽基)抑制剂模拟SARS-CoV-2 M的抑制过程。采用量子力学/分子力学(QM/MM)分子动力学方法计算了共价酶-抑制剂产物形成机制的自由能景观。模拟显示了两步机制,并给出了与实验结果高度吻合的结构和计算能垒。利用这些结果以及我们之前对SARS-CoV-2 M蛋白水解反应的研究信息,我们设计了两种新的、可通过合成获得的类似物作为潜在抑制剂,其中识别基序和弹头基序均有修饰。对这些新型化合物抑制M机制的QM/MM建模表明,两者都有望成为抗新冠药物的先导化合物,一种作为不可逆抑制剂,另一种作为潜在的可逆抑制剂。