Identification of potential antivirals against 3CLpro enzyme for the treatment of SARS-CoV-2: A multi-step virtual screening study

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak is posing a serious public health threat worldwide in the form of COVD-19. Herein, we have performed two-dimensional quantitative structure–activity relationship (2D-QSAR) and three-dimensional pharmacophore modelling analysis employing inhibitors of 3-chymotrypsin-like protease (3CLpro), the leading protease that is crucial for the replication of SARS-CoV-2. The investigation aims to identify the important structural features responsible for the enzyme inhibition and the search for novel 3CLpro enzyme inhibitors as effective therapeutics for treating SARS-CoV-2. Furthermore, we carried out molecular docking studies using the most and least active compounds in the dataset, aiming to validate the contributions of various features as appeared in the QSAR models. Later, the stringently validated 2D-QSAR model was used to estimate the 3CLpro inhibitory activity of compounds from five chemical databases. Compounds with the significant predicted activity were then subjected to pharmacophore-based virtual screening to screen the top-rated compounds, which were then further subjected to molecular docking analysis, absorption, distribution, metabolism, excretion – toxicity (ADMET) profiling, and molecular dynamics (MD) simulation. The multi-step virtual screening analyses suggested that compounds CASAntiV-865453-58-3, CASAntiV-865453-40-3, and CASAntiV-2043031-84-9 could be used as effective therapeutic agents for the treatment of SARS-CoV-2.

严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）疫情以新型冠状病毒肺炎（COVID-19）的形式对全球公共卫生构成严重威胁。本研究针对3-胰凝乳蛋白酶样蛋白酶（3CLpro）——这一对SARS-CoV-2复制至关重要的核心蛋白酶——的抑制剂，开展了二维定量构效关系（2D-QSAR）与三维药效团建模分析。本研究旨在明确与该酶抑制活性相关的关键结构特征，并挖掘新型3CLpro抑制剂以作为治疗SARS-CoV-2感染的有效治疗药物。此外，本研究选取数据集中活性最高与最低的化合物进行分子对接实验，以验证定量构效关系模型中各结构特征的贡献度。随后，本研究利用经过严格验证的2D-QSAR模型，对五个化学数据库中的化合物的3CLpro抑制活性进行预测。将预测活性显著的化合物进行基于药效团的虚拟筛选，得到候选优质化合物后，进一步对其开展分子对接分析、吸收-分布-代谢-排泄-毒性（ADMET）成药性评价以及分子动力学（MD）模拟。经多轮虚拟筛选分析表明，化合物CASAntiV-865453-58-3、CASAntiV-865453-40-3以及CASAntiV-2043031-84-9可作为治疗SARS-CoV-2感染的有效候选治疗药物。