Ikram Saima, Ahmad Jamshaid, Rehman Irshad-Ur, Durdagi Serdar
Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey; Center of Biotechnology & Microbiology, University of Peshawar, Pakistan.
Center of Biotechnology & Microbiology, University of Peshawar, Pakistan.
J Mol Graph Model. 2020 Dec;101:107727. doi: 10.1016/j.jmgm.2020.107727. Epub 2020 Sep 1.
HCV NS3, a non-structural hepatitis C viral protein is used as one of the potential targets for inhibition by direct-acting antivirals. It is known that the success rate for HCV genotype-1 treatment remained very high, however, treatment of genotype-3a (GT-3a), is still quite challenging. In the current study, the HCV GT-3a full-length NS3 gene was amplified and sequenced. The complete nucleotide sequence was translated into the amino acid sequence and homology models of HCV-NS3 GT-3a were generated by HCV-NS3 genotype-1b as a template. The objective of the study was to screen novel therapeutic hits from large databases. For this aim, various small molecule databases including, BindingDB (∼45.000 compounds), NCI (∼265.000 compounds), and Specs-SC (∼212.000 compounds) were used. Firstly, all of the compounds were screened using binary-QSAR models from the MetaCore/MetaDrug server, and compounds were filtered based on therapeutic activity predictions by the anti-viral QSAR model. Filtered molecules were used in 26 different toxicity QSAR models and active non-toxic compounds were identified. These selected molecules were then used in docking and molecular dynamics (MD) simulations studies at the binding cavities of the NS3 protease domain of the GT-3a. Results were compared with known inhibitors and novel molecules are proposed against HCV-NS3 GT-3a. These molecules have high ligand efficiencies as compared to the reference molecules suggesting a better alternate to the existing suite of inhibitors. Thus, this study will be a step ahead in the development of new potential compounds as antiviral drugs for the GT-3a target.
丙型肝炎病毒非结构蛋白3(HCV NS3)是一种丙型肝炎病毒非结构蛋白,被用作直接作用抗病毒药物抑制的潜在靶点之一。已知丙型肝炎病毒1型治疗的成功率仍然很高,然而,丙型肝炎病毒3a基因型(GT-3a)的治疗仍然颇具挑战性。在本研究中,扩增并测序了丙型肝炎病毒GT-3a全长NS3基因。将完整的核苷酸序列翻译成氨基酸序列,并以丙型肝炎病毒NS3 1b基因型为模板生成丙型肝炎病毒NS3 GT-3a的同源模型。该研究的目的是从大型数据库中筛选新的治疗性命中物。为此,使用了各种小分子数据库,包括BindingDB(约45000种化合物)、美国国立癌症研究所数据库(NCI,约265000种化合物)和Specs-SC(约212000种化合物)。首先,使用来自MetaCore/MetaDrug服务器的二元定量构效关系(QSAR)模型对所有化合物进行筛选,并根据抗病毒QSAR模型的治疗活性预测对化合物进行过滤。将过滤后的分子用于26种不同的毒性QSAR模型,鉴定出活性无毒化合物。然后将这些选定的分子用于GT-3a的NS3蛋白酶结构域结合腔的对接和分子动力学(MD)模拟研究。将结果与已知抑制剂进行比较,并提出针对丙型肝炎病毒NS3 GT-3a的新分子。与参考分子相比,这些分子具有高配体效率,表明是现有抑制剂组的更好替代品。因此,本研究将在开发针对GT-3a靶点的新型潜在抗病毒药物方面向前迈出一步。