Department of Computer Science, Tokyo Institute of Technology, Yokohama, 226-8501, Japan.
Academy for Convergence of Materials and Informatics, Tokyo Institute of Technology, Tokyo, 152-8550, Japan.
J Chem Inf Model. 2022 Jan 24;62(2):350-358. doi: 10.1021/acs.jcim.1c01087. Epub 2022 Jan 11.
In addition to vaccines, antiviral drugs are essential for suppressing COVID-19. Although several inhibitor candidates were reported for SARS-CoV-2 main protease, most are highly polar peptidomimetics with poor oral bioavailability and cell membrane permeability. Here, we conducted structure-based virtual screening and in vitro assays to obtain hit compounds belonging to a new chemical space, excluding peptidyl secondary amides. In total, 180 compounds were subjected to the primary assay at 20 μM, and nine compounds with inhibition rates of >5% were obtained. The IC of six compounds was determined in dose-response experiments, with the values on the order of 10 M. Although nitro groups were enriched in the substructure of the hit compounds, they did not significantly contribute to the binding interaction in the predicted docking poses. Physicochemical properties prediction showed good oral absorption. These new scaffolds are promising candidates for future optimization.
除疫苗外，抗病毒药物对于抑制 COVID-19 也至关重要。尽管有报道称针对 SARS-CoV-2 主蛋白酶有几种抑制剂候选物，但大多数都是高度极性的拟肽，口服生物利用度和细胞膜通透性较差。在这里，我们进行了基于结构的虚拟筛选和体外检测，以获得属于新化学空间的命中化合物，排除了肽基二级酰胺。总共对 180 种化合物在 20 μM 下进行了初步检测，得到了 9 种抑制率超过 5%的化合物。在剂量反应实验中测定了 6 种化合物的 IC 值，其值在 10 M 左右。尽管硝基在命中化合物的子结构中富集，但它们在预测的对接构象中对结合相互作用没有显著贡献。物理化学性质预测显示具有良好的口服吸收性。这些新骨架是未来优化的有希望的候选物。
