Liman Wissal, Oubahmane Mehdi, Lahcen Nouhaila Ait, Hdoufane Ismail, Cherqaoui Driss, Daoud Rachid, El Allali Achraf
Bioinformatics Laboratory, College of Computing, University Mohammed VI Polytechnic, Ben Guerir, Morocco.
Department of Chemistry, Faculty of Sciences Semlalia, BP 2390, Marrakech, Morocco.
Sci Rep. 2024 Dec 30;14(1):31655. doi: 10.1038/s41598-024-80082-1.
Hepatitis C virus (HCV) presents a significant global health issue due to its widespread prevalence and the absence of a reliable vaccine for prevention. While significant progress has been achieved in therapeutic interventions since the disease was first identified, its resurgence underscores the need for innovative strategies to combat it. The nonstructural protein NS5A is crucial in the life cycle of the HCV, serving as a significant factor in both viral replication and assembly processes. This significance is highlighted by its inclusion in all existing approved HCV combination therapies. In this study, a quantitative structure-activity relationship (QSAR) was conducted to design new compounds with enhanced inhibitory activity against HCV. In this context, a set of 82 phenylthiazole derivatives was employed to construct a QSAR model using the Monte Carlo optimization technique. This model offers valuable insights into the specific structural characteristics that either enhance or reduce the inhibitory activity. These findings were used to design novel NS5A inhibitors. Moreover, molecular docking was used to predict the binding affinity of the newly designed inhibitors within the NS5A protein, followed by molecular dynamics simulations to investigate the dynamic interactions over time. Additionally, molecular mechanics generalized born surface area calculations were carried out to estimate the binding free energies of the inhibitor candidates, providing additional insights into their binding affinities and stabilities. Finally, the absorption, distribution, metabolism, excretion, and toxicity analysis were performed to assess the pharmacokinetic and toxicity profiles of the inhibitor candidates. This comprehensive approach provides a detailed understanding of the potential efficacy, stability, and safety of the screened drug candidates, offering valuable insights for their further development as potent therapeutic agents against HCV.
丙型肝炎病毒（HCV）因其广泛流行且缺乏可靠的预防疫苗，成为一个重大的全球健康问题。自该疾病首次被发现以来，尽管在治疗干预方面已取得显著进展，但其再次出现凸显了对抗该病毒的创新策略的必要性。非结构蛋白NS5A在HCV的生命周期中至关重要，是病毒复制和组装过程中的一个重要因素。所有现有的获批HCV联合疗法中都包含该蛋白，这突出了其重要性。在本研究中，开展了定量构效关系（QSAR）研究，以设计对HCV具有增强抑制活性的新化合物。在此背景下，使用一组82种苯基噻唑衍生物，采用蒙特卡罗优化技术构建了一个QSAR模型。该模型为增强或降低抑制活性的特定结构特征提供了有价值的见解。这些发现被用于设计新型NS5A抑制剂。此外，分子对接用于预测新设计的抑制剂在NS5A蛋白内的结合亲和力，随后进行分子动力学模拟以研究随时间的动态相互作用。另外，进行了分子力学广义Born表面面积计算，以估计候选抑制剂的结合自由能，从而进一步深入了解它们的结合亲和力和稳定性。最后，进行了吸收、分布、代谢、排泄和毒性分析，以评估候选抑制剂的药代动力学和毒性特征。这种综合方法提供了对筛选出的候选药物潜在疗效、稳定性和安全性的详细理解，为其作为抗HCV有效治疗剂的进一步开发提供了有价值的见解。
