Search Results (143)

Wee1-like protein kinase 2 (WEE2) is an oocyte-specific kinase that regulates meiotic arrest and fertilization. Its largely restricted expression in female germ cells and absence in somatic tissues make it a highly selective target for reproductive health interventions. Despite its central role in human fertility, no clinically approved WEE2 modulator is available. In this study, we employed an integrated in silico approach that combines structure-based virtual screening, molecular dynamics (MD) simulations, and MM-PBSA free-energy calculations to identify repurposed drug candidates with potential WEE2 inhibitory activity. Screening of ~3800 DrugBank compounds against the WEE2 catalytic domain yielded ten high-affinity hits, from which Midostaurin and Nilotinib emerged as the most mechanistically relevant based on kinase-targeting properties and pharmacological profiles. Docking analyses revealed strong binding affinities (−11.5 and −11.3 kcal/mol) and interaction fingerprints highly similar to the reference inhibitor MK1775, including key contacts with hinge-region residues Val220, Tyr291, and Cys292. All-atom MD simulations for 300 ns demonstrated that both compounds induce stable protein–ligand complexes with minimal conformational drift, decreased residual flexibility, preserved compactness, and stable intramolecular hydrogen-bond networks. Principal component and free-energy landscape analyses further indicate restricted conformational sampling of WEE2 upon ligand binding, supporting ligand-induced stabilization of the catalytic domain. MM-PBSA calculations confirmed favorable binding free energies for Midostaurin (−18.78 ± 2.23 kJ/mol) and Nilotinib (−17.47 ± 2.95 kJ/mol), exceeding that of MK1775. To increase the translational prioritization of candidate hits, we place our structure-based pipeline in the context of modern machine learning (ML) and deep learning (DL)-enabled virtual screening workflows. ML/DL rescoring and graph-based molecular property predictors can rapidly re-rank docking hits and estimate absorption, distribution, metabolism, excretion, and toxicity (ADMET) liabilities before in vitro evaluation. Full article

Background: Due to chronic venous insufficiency, venous leg ulcers (VLUs) develop as chronic wounds characterized by impaired healing, persistent inflammation, and endothelial dysfunction. Nitrosative stress, mitochondrial damage, and tissue apoptosis caused by excess nitric oxide (NO) produced by iNOS in macrophages and fibroblasts are contributing factors in the chronic wound environment; therefore, pharmacological modulation of iNOS presents an attractive mechanistic target in chronic wound pathophysiology. Methods: Herein, we present the use of a structure-based computational strategy to assess the inhibition of tavaborole, a boron-based antifungal agent, against iNOS using human iNOS crystal structure (PDB ID: iNOS) by molecular docking using AutoDock 4.2, 500 ns simulation of molecular dynamics (MD), with equilibration within ~50 ns and analyses over full trajectory and binding free energy calculations through the MM-PBSA approach. Results: Docking studies showed favorable binding of tavaborole (–6.1 kcal/mol) in the catalytic domain, which stabilizes contacts with several key residues (CYS200, PRO350, PHE369, GLY371, TRP372, TYR373, and GLU377). MD trajectories for 1 ns showed stable structural configurations with negligible deviations (RMSD ≈ 0.44 ± 0.10 nm) and hydrogen bonding, and MM-PBSA analysis confirmed energetically favorable complex formation (ΔG_binding ≈ 18.38 ± 63.24 kJ/mol) similar to the control systems (L-arginine and 1400W). Conclusions: Taken together, these computational findings indicate that tavaborole can stably occupy the iNOS active site and interact with key catalytic residues, providing a mechanistic basis for further in vitro and ex vivo validation of its potential as an iNOS inhibitor to reduce nitrosative stress and restore endothelial homeostasis in venous leg ulcers, rather than direct therapeutic proof. Full article

The COVID-19 pandemic exposed critical vulnerabilities in single-target antiviral strategies, highlighting the urgent need for multi-mechanism therapeutic approaches against emerging viral threats. Here, we present an integrated computational framework systematically evaluating natural fatty acids as potential dual ACE2 (Angiotension Converting Enzyme 2)-inflammatory modulators; compounds simultaneously disrupting SARS-CoV-2 viral entry through allosteric ACE2 binding while suppressing host inflammatory cascades; through allosteric binding mechanisms rather than conventional competitive inhibition. Using molecular docking across eight ACE2 regions, 100 ns molecular dynamics simulations, MM/PBSA free energy calculations, and multivariate statistical analysis (PCA/LDA), we computationally assessed nine naturally occurring fatty acids representing saturated, monounsaturated, and polyunsaturated classes. Hierarchical dynamics analysis identified three distinct binding regimes spanning fast (τ < 50 ns) to slow (τ > 150 ns) timescales, with unsaturated fatty acids demonstrating superior binding affinities (ΔG = −6.85 ± 0.27 kcal/mol vs. −6.65 ± 0.25 kcal/mol for saturated analogs, p = 0.002). Arachidonic acid achieved optimal SwissDock affinity (−7.28 kcal/mol), while oleic acid exhibited top-ranked predicted binding affinity within the computational hierarchy (ΔG_bind = −24.12 ± 7.42 kcal/mol), establishing relative prioritization for experimental validation rather than absolute affinity quantification. Energetic decomposition identified van der Waals interactions as primary binding drivers (65–80% contribution), complemented by hydrogen bonds as transient directional anchors. Comprehensive ADMET profiling predicted favorable safety profiles compared to synthetic antivirals, with ω-3 fatty acids showing minimal nephrotoxicity risks while maintaining excellent intestinal absorption (>91%). Multi-platform bioactivity analysis identified convergent anti-inflammatory mechanisms through eicosanoid pathway modulation and kinase inhibition. This computational investigation positions natural fatty acids as promising candidates for experimental validation in next-generation pandemic preparedness strategies, integrating potential therapeutic efficacy with sustainable sourcing. The framework is generalizable to fatty acids from diverse biological origins. Full article

The proteasome β5 subunit plays a central role in protein degradation and is an established therapeutic target in glioblastoma. Marizomib (MZB), a natural β5 inhibitor, has shown promising anticancer activity, yet suboptimal pharmacological properties limit its clinical translation. Using a comprehensive computational approach, this study aimed to identify and characterize novel MZB analogs with improved binding affinity, stability, and drug-like profiles. An integrative in silico study was performed, including molecular docking, frontier molecular orbital (FMO) analysis, pharmacophore modeling, molecular dynamics (MD) simulations over 200 ns, MM/PBSA binding free energy calculations, and per-residue energy decomposition. ADMET profiling evaluated the pharmacokinetic and safety properties of MZB and top-performing analogs. Docking and pharmacophore modeling revealed strong complementarity between MZB analogs and the β5 catalytic pocket. MD simulations showed that MZBMOD-77 and MZBMOD-79 exhibited exceptional structural stability with low RMSD values (0.40–0.42 nm), persistent binding within the active site cavity, and significant disruption of hydrogen-bond networks in the active loop regions Ala19–Lys33 and Val87–Gly98. MM/PBSA analysis confirmed their superior binding free energies (−19.99 and −18.79 kcal/mol, respectively), surpassing native MZB (−6.26 kcal/mol). Per-residue decomposition highlighted strong contributions from Arg19, Ala20, Lys33, and Ala50. ADMET predictions indicated improved oral absorption, reduced toxicity, and favorable pharmacokinetics compared to native MZB. This integrative computational study identifies MZBMOD-77 and MZBMOD-79 as promising next-generation proteasome β5 inhibitors. These analogs mimic and enhance the inhibitory mechanism of native MZB, offering potential candidates for further optimization and preclinical development in glioblastoma therapy. Full article

β-site amyloid precursor protein cleaving enzyme 1 (BACE1) is a central therapeutic target in Alzheimer’s disease, as it catalyzes the rate-limiting step in amyloid-β production. Verubecestat (VER), a clinical BACE1 inhibitor, failed in late-stage trials due to limited efficacy and safety concerns. This study employed an integrative computational approach to design VER derivatives with improved binding affinity, stability, and pharmacokinetic profiles. Structural similarity analysis, Molecular docking, frontier molecular orbital (FMO) analysis, pharmacophore modeling, 200 ns molecular dynamics (MD) simulations, MM/PBSA free energy calculations, and per-residue decomposition were performed. In silico ADMET profiling assessed drug-likeness, absorption, and safety parameters. Docking and pharmacophore analyses identified derivatives with stronger complementarity in the BACE1 catalytic pocket. MD simulations revealed that VERMOD-33 and VERMOD-57 maintained low root mean square deviations (RMSDs) and stable binding orientations and induced characteristic flexibility in the flap and catalytic loops surrounding the catalytic dyad (Asp93 and Asp289), consistent with inhibitory activity. MM/PBSA confirmed the superior binding free energies of VERMOD-33 (−51.12 kcal/mol) and VERMOD-57 (−43.85 kcal/mol), both outperforming native VER (−35.33 kcal/mol). Per-residue decomposition highlighted Asp93, Asp289, and adjacent flap residues as major energetic contributors. ADMET predictions indicated improved oral absorption, BBB penetration, and no mutagenicity or toxicity alerts. Rationally designed VER derivatives, particularly VERMOD-33 and VERMOD-57, displayed enhanced binding energetics, stable inhibitory dynamics, and favorable pharmacokinetic properties compared with native VER. These findings provide a computational framework for rescuing VER and support further synthesis and experimental validation of next-generation BACE1 inhibitors for Alzheimer’s disease. Full article

GABA transporter 1 (GAT1), encoded by the SLC6A1 gene, is essential for maintaining inhibitory neurotransmission by mediating the reuptake of GABA from the synaptic cleft. Dysfunction of GAT1 has been linked to several neurological and neurodevelopmental disorders, including epilepsy and Alzheimer’s disease. In this study, we performed a comprehensive computational investigation of reported GAT1 mutations to understand their structural and functional implications. Seven mutations (G63S, Y140C, Q291Δ, F294Δ, N310I, D451G, and G457H) were analyzed using homology modeling, structural validation tools, molecular dynamics (MD) simulation triplicates, and binding free energy calculations via the gmx_MMPBSA method. The wild-type consistently exhibited the most favorable interaction energy (−59.89 kcal/mol), the strongest binding free energy (ΔG = −28.29 kcal/mol), and the most stable hydrogen-bonding network. While all mutants displayed elevated RMSD and energy fluctuations relative to the wild-type, these changes predominantly reflected local conformational disturbances rather than global unfolding, indicating that the overall structural framework of GAT1 remains largely preserved. Among the mutants, G63S exerted the mildest effect on ligand stabilization, whereas Y140C, G457H, Q291Δ, and D451G produced substantial reductions in protein–ligand stability, weakened hydrogen bonding, and increased ligand mobility within the binding pocket. Free-energy analysis further highlighted the pronounced destabilizing influence of N310I, Q291Δ, and G457H on tiagabine binding. These findings provide mechanistic insights into how specific GAT1 mutations may alter transporter stability and function, offering a structural framework for future studies on GABAergic dysfunction and therapeutic development. Full article

Background/Objectives: Janus kinase 2 (JAK2) is a pivotal signaling protein implicated in various hematological malignancies and inflammatory disorders, making it a compelling target for therapeutic intervention. Methods: In this study, we employed an integrative computational approach combining ligand-based screening, pharmacophore modeling, molecular docking, molecular dynamics (MD) simulations, and MM/PBSA free energy calculations to identify JAK2 inhibitors from the ChEMBL database. A comprehensive virtual screening of over 1,900,000 compounds was conducted using Tanimoto similarity and a validated pharmacophore model, resulting in the identification of 39 structurally promising candidates. Docking analyses prioritized compounds with favorable interaction energies, while MD simulations over 100 ns assessed the dynamic behavior and binding stability of top hits. Results: Four compounds, CHEMBL4169802, CHEMBL4162254, CHEMBL4286867, and CHEMBL2208033, exhibited consistently superior performance, forming stable hydrogen bonds, favorable RMSD profiles (≤0.5 nm), and strong binding interactions, including salt bridges. Notably, the binding free energies revealed ΔG values as low as −29.91 kcal/mol, surpassing that of the reference inhibitor, momelotinib (−24.17 kcal/mol). Conclusions: Among these, CHEMBL4169802 emerged as the most promising candidate due to its synergistic electrostatic and hydrophobic interactions. Collectively, our results highlight these compounds as probable, JAK2-selective inhibitors with strong potential for further biological validation and optimization. Full article

Oropouche virus (OROV), an emerging orthobunyavirus of increasing public health concern in the Americas, currently lacks approved antiviral therapies. In this study, we employed a structure-based in silico approach to identify natural antiviral scaffolds capable of targeting the Gc glycoprotein, a class II fusion protein essential for host membrane fusion and viral entry. A library of 537 plant-derived compounds was screened against the Gc head domain (PDB ID: 6H3X) through molecular docking and redocking, followed by 100-nanosecond molecular dynamics simulations, MM-PBSA free energy calculations, and ADMET profiling. Curcumin and Berberine emerged as standout candidates. Curcumin demonstrated a balanced profile, with stable binding (−38.14 kcal/mol), low backbone RMSD (1.82 Å), and consistent radius of gyration (Rg ~ 18.8 Å), suggesting strong conformational stability and compactness of the protein–ligand complex. Berberine exhibited the most favorable binding energy (−13.10 kcal/mol) and retained dynamic stability (RMSD 1.86 Å; Rg ~ 19.0 Å), though accompanied by predicted cytotoxicity that may require structural refinement. Both compounds induced reduced residue-level fluctuations (RMSF < 2.5 Å) in functionally critical regions of the Gc protein, consistent with a mechanism of action that involves stabilization of the prefusion conformation and interference with the structural transitions required for viral entry. These findings identify curcumin and berberine as promising scaffolds for anti-OROV drug development and offer a rational foundation for future experimental validation targeting viral fusion mechanisms. Full article

Chronic pain is a serious health issue, often irrationally managed by conventional analgesics. Duloxetine, a serotonin–norepinephrine reuptake inhibitor (SNRI), also effective in neuropathic and musculoskeletal pain, but the molecular mechanism of its analgesic action is still unclear. Here, we examined whether Duloxetine exerts pleiotropic effects by directly targeting phosphorylated STAT3 (pSTAT3), a key regulator of neuroinflammation and pain sensitization. Molecular docking showed that Duloxetine binds with pSTAT3 with binding energy −5.83 kcal/mol. Ruxolitinib, a JAK/STAT inhibitor used as reference, showed binding energy of −6.19 kcal/mol. Molecular dynamics (MD) simulations confirmed stable Duloxetine–pSTAT3 complexes, while MM-PBSA free energy analysis revealed more favorable binding for Duloxetine (ΔG = −15.17 kJ·mol⁻¹) than Ruxolitinib (ΔG = −12.98 kJ·mol⁻¹) for pSTAT3. In-vitro analyses, Western blot showed that Duloxetine significantly reduced IL-6–induced STAT3 and pSTAT3 expression in C2C12 cells in a dose-dependent manner (6.4 and 12.8 μM, *** p < 0.0001), although Ruxolitinib produced a stronger suppression. Transcriptomic analysis revealed Duloxetine-specific enrichment of mitochondrial, oxidative phosphorylation, and synaptic pathways, distinct from the immune-suppressive influence of Ruxolitinib. RNA-seq further revealed that STAT3 transcript abundance remains constant under all treatment conditions, indicating that post-transcriptional or post-translational mechanisms, such as phosphorylation-dependent activation, may be involved rather than transcriptional modulation of STAT3 in action of Ruxolitinib and Duloxetine and the formation of novel STAT3 indicating enhanced transcript diversity. The rMATS splicing analysis confirmed dose-dependent modulation, with Duloxetine promoting mild exon skipping at 6.4 μM (IncLevel 0.90 → 0.80) and recovery at 12.8 μM (0.85 → 0.86), while Ruxolitinib induced stronger exon inclusion (0.85 → 1.00,0.94), with broader transcript suppression at 6.4 μM and 12.8 μM, respectively. These findings establish Duloxetine as a dual-action therapeutic that combines neurotransmitter reuptake inhibition with pSTAT3 suppression and isoform-level transcriptomic modulation. This pleiotropic mechanism provides a rationale for its durable analgesic effects and supports repurposing in STAT3-associated disorders. Full article

Background/Objectives: Cancer progression is characterized by the suppression of apoptosis, activation of metastatic processes, and dysregulation of cell proliferation. The proper functioning of these mechanisms relies on critical signaling pathways, including Phosphoinositide 3-kinase/Protein kinase B/mammalian Target of Rapamycin (PI3K/Akt/mTOR), Mitogen-Activated Protein Kinase (MAPK), and Signal Transducer and Activator of Transcription 3 (STAT3). Although curcumin and resveratrol exhibit anticancer properties and affect these pathways, their pharmacokinetic limitations, including poor bioavailability and low solubility, restrict their clinical application. The aim of our study was to evaluate the synergistic anticancer potential of curcumin and resveratrol through hybrid molecules rationally designed from these compounds to mitigate their pharmacokinetic limitations. Furthermore, we analyzed the multi-target anticancer effects of these hybrids on the AKT serine/threonine kinase 1 (AKT1), MAPK, and STAT3 pathways using in silico molecular modeling approaches. Methods: Three hybrid molecules, including a long-chain (ELRC-LC) and a short-chain (ELRC-SC) hybrid, an ester-linked hybrid, and an ether-linked hybrid (EtLRC), were designed using the Avogadro software (v1.2.0), and their geometry optimization was carried out using Density Functional Theory (DFT). The electronic properties of the structures were characterized through Frontier Molecular Orbital (FMO), Molecular Electrostatic Potential (MEP), and Fourier Transform Infrared (FTIR) analyses. The binding energies of the hybrid molecules, curcumin, resveratrol, their analogs, and the reference inhibitor were calculated against the AKT1, MAPK, and STAT3 receptors using molecular docking. The stabilities of the best-fitting complexes were evaluated through 100 ns molecular dynamics (MD) simulations, and their binding free energies were estimated using the Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA) method. Results: DFT analyses demonstrated stable electronic characteristics for the hybrids. Molecular docking analyses revealed that the hybrids exhibited stronger binding compared to curcumin and resveratrol. The binding energy of −11.4 kcal/mol obtained for the ELRC-LC hybrid against AKT1 was particularly remarkable. Analysis of 100 ns MD simulations confirmed the conformational stability of the hybrids. Conclusions: Hybrid molecules have been shown to exert multi-target mechanisms of action on the AKT1, MAPK, and STAT3 pathways, and to represent potential anticancer candidates capable of overcoming pharmacokinetic limitations. Our in silico-based study provides data that will guide future in vitro and in vivo studies. These rationally designed hybrid molecules, owing to their receptor affinity, may serve as de novo hybrid inhibitors. Full article

Cid1 protein is a crucial component in the RNA interference pathway and abnormal nuclear RNA turnover processes, primarily responsible for adding uridine to the 3′ end of RNA. Cid1 exhibits selective polymerization of UTP over other nucleoside triphosphates. To explore the mechanism of this selectivity, five systems: free-Cid1, Cid1-ATP, Cid1-UTP, Cid1-CTP, and Cid1-GTP with 500 ns Gaussian accelerated molecular dynamics (GaMD) simulations were performed to investigate conformational changes and binding affinities between substrates and Cid1. The results showed that UTP formed stronger and more numerous non-covalent interactions with Cid1 compared to the other three substrates. The Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) binding energy analysis revealed a substrate preference for Cid1 polymerase in the order of UTP, followed by ATP, CTP, and GTP. These findings provide theoretical insights into the substrate selectivity mechanism of Cid1 and provide theoretical clues for the design and modification of Cid1 polymerase. Full article

The mammalian target of rapamycin pathway, mTOR, is a crucial signaling pathway that regulates cell growth, proliferation, metabolism, and survival. Due to its dysregulation it is involved in several ailments such as cancer or age-related diseases. The discovery of mTOR and the understanding of its biological functions were greatly facilitated by the use of rapamycin, an antibiotic of natural origin, which allosterically inhibits mTORC1, effectively blocking its function. In this entirely computational study, we investigated mTOR’s interaction with seven ligands: two clinically established inhibitors (everolimus and rapamycin) and five lignin-derived oligomers, a renewable natural polyphenol recently used for the drug delivery of everolimus. The seven complexes were analyzed through all-atom molecular dynamics simulations in explicit solvent using a high-performance computing platform. Trajectory analyses revealed stable interactions between mTOR and all ligands, with lignin-derived compounds showing comparable or enhanced binding stability relative to reference drugs. To evaluate the stability of the molecular complex and the behavior of the ligand over time, we analyzed key parameters including root mean square deviation, root mean square fluctuation, number of hydrogen bonds, binding free energy, and conformational dynamics assessed through principal component analysis. Our results suggest that lignin fragments are a promising, sustainable scaffold for developing novel mTOR inhibitors. Full article

This study aimed to investigate the molecular binding mechanisms of bromocriptine toward histamine-associated targets, exploring both antagonist-like and other potential interaction modes that may support therapeutic repurposing. Network pharmacology was applied to identify histamine-related pathways and prioritize potential protein targets. CXCR4, GHSR, and OXTR were selected based on combined docking scores and pharmacophore modeling evidence. Molecular dynamics (MD) simulations over 100 ns assessed structural stability, flexibility, compactness, and solvent exposure. Binding site contact analysis and MM/PBSA free binding energy calculations were conducted to characterize binding energetics and interaction persistence. Bromocriptine exhibited stable binding to all three receptors, engaging key residues implicated in receptor modulation (e.g., Asp187 in CXCR4, Asp99 in GHSR, Arg232 in OXTR). The MM/PBSA ΔG_binding values of bromocriptine were −22.67 ± 3.70 kcal/mol (CXCR4 complex), −22.11 ± 3.55 kcal/mol (GHSR complex), and −21.43 ± 2.41 kcal/mol (OXTR complex), stronger than standard agonists and comparable to antagonists. Contact profiles revealed shared and unique binding patterns across targets, reflecting their potential for diverse modulatory effects. Bromocriptine demonstrates high-affinity binding to multiple histamine-associated GPCR targets, potentially exerting both inhibitory and modulatory actions. These findings provide a molecular basis for further experimental validation and therapeutic exploration in histamine-related conditions. Full article

Carbonic anhydrase IX (CA IX) is a transmembrane metalloenzyme that is increased in tumor cells under hypoxia and plays an important role in solid tumor acidification. It is a marker of tumor hypoxia and a prognostic factor in human malignancies. Given the critical role of CA IX and their over expression in many cancer tissues, they have emerged as a promising target for developing novel anticancer therapeutics. In this study we designed a pharmacophore model based on known inhibitors to screen small compound libraries to discover potential inhibitors of CA IX. Molecular docking experiments discovered that four compounds ZINC613262012, ZINC427910039, ZINC616453231, and DB00482 exhibited a strong binding affinity towards CA IX, mimicking the interaction pattern similar to native inhibitors. Molecular dynamics simulations and an MM-PBSA analysis revealed ZINC613262012, ZINC427910039, and DB00482 as the most potential and stable inhibitors with the binding free energies −10.92, −18.77, and −12.29 kcal/mol, respectively. In addition, DFT-based analyses supported their favorable electronic properties, further validating their potential as CA IX inhibitors. These three hits demonstrated a greater stability and compactness relative to the known inhibitors, suggesting these might be used CA IX inhibitors to treat tumors. Full article

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. Full article