Department of Biochemistry, Government College University, Faisalabad, Pakistan.
Department of Pharmacy, The Women University, Multan, Pakistan.
Curr Med Chem. 2024;31(15):2052-2072. doi: 10.2174/0109298673234823230921090431.
Hepatitis C virus (HCV) is a globally prevalent and hazardous disorder that is responsible for inducing several persistent and potentially fatal liver diseases. Current treatment strategies offer limited efficacy, often accompanied by severe and debilitating adverse effects. Consequently, there is an urgent and compelling need to develop novel therapeutic interventions that can provide maximum efficacy in combating HCV while minimizing the burden of adverse effects on patients. One promising target against HCV is the NS3-4A serine protease, a complex composed of two HCV-encoded proteins. This non-covalent heterodimer is crucial in the viral life cycle and has become a primary focus for therapeutic interventions. Although peginterferon, combined with ribavirin, is commonly employed for HCV treatment, its efficacy is hampered by significant adverse effects that can profoundly impact patients' quality of life. In recent years, the development of direct-acting antiviral agents (DAAs) has emerged as a breakthrough in HCV therapy. These agents exhibit remarkable potency against the virus and have demonstrated fewer adverse effects when combined with other DAAs. However, it is important to note that there is a potential for developing resistance to DAAs due to alterations in the amino acid position of the NS3-4A protease. This emphasizes the need for ongoing research to identify strategies that can minimize the emergence of resistance and ensure long-term effectiveness. While the combination of DAAs holds promise for HCV treatment, it is crucial to consider the possibility of drug-drug interactions. These interactions may occur when different DAAs are used concurrently, potentially compromising their therapeutic efficacy. Therefore, carefully evaluating and monitoring potential drug interactions are vital to optimize treatment outcomes. In the pursuit of novel therapeutic interventions for HCV, the field of computational biology and bioinformatics has emerged as a valuable tool. These advanced technologies and methodologies enable the development and design of new drugs and therapeutic agents that exhibit maximum efficacy, reduced risk of resistance, and minimal adverse effects. By leveraging computational approaches, researchers can efficiently screen and optimize potential candidates, accelerating the discovery and development of highly effective treatments for HCV, treatments.
丙型肝炎病毒(HCV)是一种全球流行且危险的疾病,可导致多种持续存在且可能致命的肝脏疾病。目前的治疗策略疗效有限,常常伴有严重和使人衰弱的不良反应。因此,迫切需要开发新的治疗干预措施,以在最大程度地发挥抗 HCV 疗效的同时,减轻不良反应对患者的负担。针对 HCV 的一个有前途的靶标是 NS3-4A 丝氨酸蛋白酶,它是由两种 HCV 编码的蛋白质组成的复杂结构。这种非共价异源二聚体在病毒生命周期中至关重要,已成为治疗干预的主要焦点。尽管聚乙二醇干扰素联合利巴韦林常用于 HCV 治疗,但由于其不良反应显著,会对患者的生活质量产生深远影响,因此疗效受到限制。近年来,直接作用抗病毒药物(DAA)的开发已成为 HCV 治疗的突破。这些药物对病毒具有显著的效力,并且与其他 DAA 联合使用时不良反应较少。然而,值得注意的是,由于 NS3-4A 蛋白酶的氨基酸位置发生改变,可能会产生对 DAA 的耐药性。这强调了需要不断研究以确定可以最小化耐药性出现并确保长期有效性的策略。虽然 DAA 的联合使用为 HCV 治疗带来了希望,但必须考虑药物相互作用的可能性。当同时使用不同的 DAA 时,可能会发生这些相互作用,从而可能会降低其治疗效果。因此,仔细评估和监测潜在的药物相互作用对于优化治疗结果至关重要。在寻求 HCV 的新治疗干预措施时,计算生物学和生物信息学领域已成为一种有价值的工具。这些先进的技术和方法可用于开发和设计具有最大疗效、降低耐药风险和最小不良反应的新型药物和治疗剂。通过利用计算方法,研究人员可以高效筛选和优化潜在的候选药物,从而加速发现和开发高效的 HCV 治疗方法。