Suleman Muhammad, Arbab Hira, Yassine Hadi M, Sayaf Abrar Mohammad, Ilahi Usama, Alissa Mohammed, Alghamdi Abdullah, Alghamdi Suad A, Crovella Sergio, Shaito Abdullah A
Laboratory of Animal Research Center (LARC), Qatar University, Doha P.O. Box 2713, Qatar.
Center for Biotechnology and Microbiology, University of Swat, Swat 19200, Pakistan.
Pharmaceuticals (Basel). 2025 Jul 31;18(8):1144. doi: 10.3390/ph18081144.
Hepatocellular carcinoma (HCC) is one of the most common and fatal malignancies worldwide, characterized by remarkable molecular heterogeneity and poor clinical outcomes. Despite advancements in diagnosis and treatment, the prognosis for HCC remains dismal, largely due to late-stage diagnosis and limited therapeutic efficacy. Therefore, there is a critical need to identify novel therapeutic targets and explore alternative strategies, such as drug repurposing, to improve patient outcomes. In this study, we employed network pharmacology, molecular docking, and molecular dynamics (MD) simulations to explore the potential therapeutic targets of Nirmatrelvir in HCC. Nirmatrelvir targets were predicted through SwissTarget (101 targets), SuperPred (1111 targets), and Way2Drug (38 targets). Concurrently, HCC-associated genes (5726) were retrieved from DisGeNet. Cross-referencing the two datasets identified 29 overlapping proteins. A protein-protein interaction (PPI) network constructed from the overlapping proteins was analyzed using CytoHubba, identifying 10 hub genes, with HDAC1, HDAC3, and STAT3 achieving the highest degree scores. Molecular docking revealed a strong binding affinity of Nirmatrelvir to HDAC1 (docking score = -7.319 kcal/mol), HDAC3 (-6.026 kcal/mol), and STAT3 (-6.304 kcal/mol). Moreover, Nirmatrelvir displayed stable dynamic behavior in repeated 200 ns simulation analyses. Binding free energy calculations using MM/GBSA showed values of -23.692 kcal/mol for the HDAC1-Nirmatrelvir complex, -33.360 kcal/mol for HDAC3, and -21.167 kcal/mol for STAT3. MM/PBSA analysis yielded -17.987 kcal/mol for HDAC1, -27.767 kcal/mol for HDAC3, and -16.986 kcal/mol for STAT3. The findings demonstrate Nirmatrelvir's strong binding affinity towards HDAC3, underscoring its potential for future drug development. Collectively, the data provide computational evidence for repurposing Nirmatrelvir as a multi-target inhibitor in HCC therapy, warranting in vitro and in vivo studies to confirm its clinical efficacy and safety and elucidate its mechanisms of action in HCC.
肝细胞癌(HCC)是全球最常见且致命的恶性肿瘤之一,其特点是具有显著的分子异质性和较差的临床预后。尽管在诊断和治疗方面取得了进展,但HCC的预后仍然不容乐观,这主要归因于晚期诊断和有限的治疗效果。因此,迫切需要确定新的治疗靶点并探索替代策略,如药物重新利用,以改善患者的预后。在本研究中,我们采用网络药理学、分子对接和分子动力学(MD)模拟来探索Nirmatrelvir在HCC中的潜在治疗靶点。通过SwissTarget(101个靶点)、SuperPred(1111个靶点)和Way2Drug(38个靶点)预测Nirmatrelvir的靶点。同时,从DisGeNet检索HCC相关基因(5726个)。对这两个数据集进行交叉参考,确定了29个重叠蛋白。使用CytoHubba分析由重叠蛋白构建的蛋白质-蛋白质相互作用(PPI)网络,确定了10个枢纽基因,其中HDAC1、HDAC3和STAT3的度得分最高。分子对接显示Nirmatrelvir与HDAC1(对接得分=-7.319 kcal/mol)、HDAC3(-6.026 kcal/mol)和STAT3(-6.304 kcal/mol)具有很强的结合亲和力。此外,在重复的200 ns模拟分析中,Nirmatrelvir表现出稳定的动态行为。使用MM/GBSA进行的结合自由能计算显示,HDAC1-Nirmatrelvir复合物的值为-23.692 kcal/mol,HDAC3为-33.360 kcal/mol,STAT3为-21.167 kcal/mol。MM/PBSA分析得出HDAC1为-17.987 kcal/mol,HDAC3为-27.767 kcal/mol,STAT3为-16.986 kcal/mol。研究结果表明Nirmatrelvir对HDAC3具有很强的结合亲和力,突出了其在未来药物开发中的潜力。总体而言,这些数据为将Nirmatrelvir重新用作HCC治疗中的多靶点抑制剂提供了计算证据,需要进行体外和体内研究以确认其临床疗效和安全性,并阐明其在HCC中的作用机制。