SMILES-based QSAR virtual screening to identify potential therapeutics for COVID-19 by targeting 3CLpro and RdRp viral proteins

IF 4.3 2区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY BMC Chemistry Pub Date : 2024-10-03 DOI:10.1186/s13065-024-01302-3
Faezeh Bazzi-Allahri, Fereshteh Shiri, Shahin Ahmadi, Alla P. Toropova, Andrey A. Toropov
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Abstract

The COVID-19 pandemic has prompted the medical systems of many countries to develop effective treatments to combat the high rate of infection and death caused by the disease. Within the array of proteins found in SARS-CoV-2, the 3 chymotrypsin-like protease (3CLpro) holds significance as it plays a crucial role in cleaving polyprotein peptides into distinct functional nonstructural proteins. Meanwhile, RNA-dependent RNA polymerase (RdRp) takes center stage as the key enzyme tasked with replicating the viral genomic RNA within host cells. These proteins, 3CLpro and RdRp, are deemed optimal subjects for QSAR modeling due to their pivotal functions in the viral lifecycle. In this study, SMILES-based QSAR classification models were developed for a dataset of 2377 compounds that were defined as either active or inactive against 3CLpro and RdRp. Pharmacophore (PH4) and QSAR modeling were used for the virtual screening on 60.2 million compounds including ZINC, ChEMBL, Molport, and MCULE databases to identify new potent inhibitors against 3CLpro and RdRp. Then, a filter was established based on typical molecular characteristics to identify drug-like molecules. The molecular docking was also performed to evaluate the binding affinity of 156 AND 51 potential inhibitors to 3CLpro and RdRp, respectively. Among the 15 hits identified based on molecular docking scores, M3, N2, and N4 were identified as promising inhibitors due to their good synthetic accessibility scores (3.07, 3.11, and 3.29 out of 10 for M3, N2, and N4 respectively). These compounds contain amine functional groups, which are known for their crucial role in the binding interactions between drugs and their targets. Consequently, these hits have been chosen for further biological assay studies to validate their activity. They may represent novel 3CLpro and RdRp inhibitors possessing drug-like properties suitable for COVID-19 therapy.

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基于 SMILES 的 QSAR 虚拟筛选,通过靶向 3CLpro 和 RdRp 病毒蛋白确定 COVID-19 的潜在疗法。
COVID-19 大流行促使许多国家的医疗系统开发有效的治疗方法,以应对该疾病造成的高感染率和高死亡率。在 SARS-CoV-2 中发现的一系列蛋白质中,3糜蛋白酶样蛋白酶(3CLpro)具有重要意义,因为它在将多肽蛋白裂解为不同功能的非结构蛋白方面发挥着关键作用。与此同时,RNA 依赖性 RNA 聚合酶(RdRp)作为在宿主细胞内复制病毒基因组 RNA 的关键酶占据了中心位置。由于 3CLpro 和 RdRp 这两种蛋白在病毒生命周期中的关键功能,它们被认为是 QSAR 建模的最佳对象。本研究针对 2377 种化合物的数据集开发了基于 SMILES 的 QSAR 分类模型,这些化合物被定义为对 3CLpro 和 RdRp 有活性或无活性。该研究利用Pharmacophore (PH4)和QSAR模型对包括ZINC、ChEMBL、Molport和MCULE数据库在内的6020万个化合物进行了虚拟筛选,以鉴定出针对3CLpro和RdRp的新的强效抑制剂。然后,根据典型的分子特征建立过滤器,以识别类药物分子。同时还进行了分子对接,分别评估了156个和51个潜在抑制剂与3CLpro和RdRp的结合亲和力。在根据分子对接得分确定的 15 个命中物中,M3、N2 和 N4 因其良好的合成亲和性得分(M3、N2 和 N4 分别为 3.07、3.11 和 3.29,满分为 10 分)而被确定为有希望的抑制剂。这些化合物含有胺官能团,众所周知,胺官能团在药物与其靶点的结合相互作用中起着至关重要的作用。因此,这些化合物被选中进行进一步的生物检测研究,以验证其活性。它们可能是新型 3CLpro 和 RdRp 抑制剂,具有类似药物的特性,适合用于 COVID-19 治疗。
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来源期刊
BMC Chemistry
BMC Chemistry Chemistry-General Chemistry
CiteScore
5.30
自引率
2.20%
发文量
92
审稿时长
27 weeks
期刊介绍: BMC Chemistry, formerly known as Chemistry Central Journal, is now part of the BMC series journals family. Chemistry Central Journal has served the chemistry community as a trusted open access resource for more than 10 years – and we are delighted to announce the next step on its journey. In January 2019 the journal has been renamed BMC Chemistry and now strengthens the BMC series footprint in the physical sciences by publishing quality articles and by pushing the boundaries of open chemistry.
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