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    Repurposing Nirmatrelvir for Hepatocellular Carcinoma: Network Pharmacology and Molecular Dynamics Simulations Identify HDAC3 as a Key Molecular Target

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    Date
    2025-08-01
    Author
    Suleman, Muhammad
    Arbab, Hira
    Yassine, Hadi M.
    Sayaf, Abrar Mohammad
    Ilahi, Usama
    Alissa, Mohammed
    Alghamdi, Abdullah
    Alghamdi, Suad A.
    Crovella, Sergio
    Shaito, Abdullah A.
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    Abstract
    Background: 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. Methods: In this study, we employed network pharmacology, molecular docking, and molecular dynamics (MD) simulations to explore the potential therapeutic targets of Nirmatrelvir in HCC. Results: 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. Conclusions: 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.
    URI
    https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105014397660&origin=inward
    DOI/handle
    http://dx.doi.org/10.3390/ph18081144
    http://hdl.handle.net/10576/67184
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