Structure-based computational assessment of Bacopa monnieri-derived compounds as potential dual target anti-seizure medications: An integrated docking and molecular dynamics simulation approach.

Mechanistic insights into marine-derived PDE6D inhibitors disrupting prenyl-binding to modulate leukemia-associated RAS trafficking.

Background SARS-CoV-2 continues to evolve, with new variants showing higher transmissibility and immune evasion. The limited effectiveness of current antiviral drugs highlights the potential of natural product compounds, such as eurycomanone as promising alternatives. Objective This study evaluated the antiviral efficacy of eurycomanone against SARS-CoV-2 variants through experimental and computational analyses. Methods The antiviral activity of eurycomanone was tested in vitro using a cytopathic effect-based assay with Vero E6 cells infected with the original Wuhan-wild-type (WT), Alpha, Delta, and Omicron variants. Cytotoxicity was measured using an ATP-based assay. Computational analysis was performed through molecular docking and dynamics simulations to analyse its binding with SARS-CoV-2 main protease (M pro ) in both WT and Omicron variants. Results Eurycomanone exhibited the strongest antiviral activity against the Omicron variant (EC 50 : 4.58 µM) among all tested variants, with low cytotoxicity (CC 50 > 100 µM) as determined by a cell viability assay in Vero E6 cells. Docking studies revealed strong binding affinities to M pro (WT: −7.7 kcal/mol; Omicron: −8.2 kcal/mol), comparable to nirmatrelvir. Molecular dynamics confirmed stable binding and MMGBSA calculations showed enhanced hydrophobic and electrostatic interactions with the Omicron variant. Conclusion Eurycomanone exhibited notable antiviral activity especially against Omicron, suggesting its potential as a lead compound for developing new antiviral therapies. Further in vivo studies are needed to explore its therapeutic potential.

EZH2 (Enhancer-Homozygous Protein 2), as a key epigenetic regulator, is closely associated with multiple cancers. Consequently, the design of EZH2-targeting inhibitors has become a significant focus in drug development. The application of deep learning methods in the chemical field can accelerate the process of discovering new molecules. This study utilized the SMILES sequence information of 1,202,321 small molecules from the ChEMBL29 database and the known molecular structures of 11 compounds with EZH2 inhibitory activity. A molecular generation model based on a gated recurrent unit (GRU) network and transfer learning was constructed, generating 50,000 SMILES molecular sequences. Through classification prediction by an ECFP4-SVM model, 37,802 effective and novel molecular structures were screened. Subsequent virtual screening incorporated Lipinski's Rules, ADMET properties, and molecular docking, ultimately identifying 10 candidate compounds for 100 ns molecular dynamics simulations and density functional theory (DFT) calculations. MM-GBSA calculations revealed binding free energies ≤ -42.3518kcal/mol for the candidate compounds, suggesting strong interactions with EZH2. DFT calculations further characterized the electronic interaction features underlying ligand-protein binding. This study demonstrates the feasibility of a deep learning-driven computational framework for the virtual identification and prioritization of potential EZH2 inhibitor candidates.

Enzymes such as oxidases are sustainable tools for hydrogel synthesis, but complex competing reactions have limited the mechanistic understanding and biomedical applications of these materials. Guided by molecular docking and MM-GBSA calculations, we identified two artificial substrates, desaminotyrosine (DAT) and desaminotyrosyltyrosine (DATT), that were experimentally more efficiently converted by mushroom tyrosinase (mTyr) than the natural substrate tyrosine. These substrates were used to synthesize hydrogels from DAT/DATT-functionalized star-shaped oligoethylene glycol (sOEG). Model reactions elucidated the chemical nature and functionality of the hydrogel netpoints. Material properties were systematically investigated depending on sOEG molecular weight (5, 10, 20 kDa), substrate type, and mTyr concentration. Functional mesh sizes and controlled release functions were investigated with fluorescent dextrans (4-500 kDa) and heparin. Cell culture studies with L929 fibroblasts and THP-1 monocytes suggested inertness of the material. These findings provide fundamental insight into mTyr-catalyzed hydrogel formation and support further exploration for in situ hydrogel synthesis.

AKT1 and AKT2 are central but functionally distinct kinases within the PI3K-AKT-mTOR pathway, and isoform-specific genomic alterations in these proteins have important implications for cancer prognosis and therapeutic responsiveness. This study aimed to integrate cancer pharmacogenomics with structure-based modeling to identify natural compounds capable of selectively targeting AKT1 or AKT2. Public cancer genomics datasets from TCGA and the Kaplan-Meier Plotter were analyzed to characterize mutation patterns, copy number alterations, and survival associations of AKT1 and AKT2 across malignancies. Based on isoform-specific differences, twenty phytochemicals from Pithecellobium dulce were docked against the allosteric binding sites of AKT1 (PDB: 3QKL) and AKT2 (PDB: 2JDO). Lead compounds were evaluated using ADME prediction and density functional theory to assess pharmacokinetic suitability and electronic stability. The dynamic behavior of ligand-protein complexes was examined through 200-ns molecular dynamics simulations using the Desmond-Schrödinger platform, and binding free energies were estimated via MM-GBSA analysis. Regulatory interactions involving AKT-associated non-coding RNAs were also examined to support pharmacogenomic relevance. Genomic analysis revealed that AKT1 alterations were dominated by activating missense mutations, particularly the E17K hotspot, whereas AKT2 showed frequent gene amplifications that were significantly associated with poor overall survival. Docking studies demonstrated clear isoform selectivity among P. dulce phytochemicals: oleanolic acid and pitheduloside I preferentially bound AKT1, while rutin and naringin exhibited stronger affinity toward AKT2. Oleanolic acid and rutin displayed binding energies comparable to established allosteric AKT inhibitors. ADME and DFT analyses supported favorable drug-likeness and molecular stability of the lead compounds. Molecular dynamics simulations confirmed stable complex formation with persistent hydrogen bonding, and MM-GBSA calculations indicated superior binding energetics for oleanolic acid-AKT1 and rutin-AKT2 complexes relative to controls. In parallel, analysis of miR-149-5p and lncRNA HOTAIR highlighted post-transcriptional regulatory mechanisms influencing AKT isoform activity. This study demonstrates that integrating pharmacogenomic profiling with multiscale molecular simulations can reveal isoform-specific vulnerabilities within the AKT signaling axis. Phytochemicals derived from Pithecellobium dulce, particularly oleanolic acid and rutin, emerge as promising selective modulators of AKT1 and AKT2, respectively. These findings provide a mechanistic and structural foundation for the development of isoform-guided AKT-targeted therapies and support further experimental validation toward precision oncology applications.

This study reports the biological evaluation of novel Schiff base-tethered organoselenium (OSe) compounds as potential anticancer agents. New derivatives (HB178, HB179, HB181, HB183, HB208, HB209, and HB210) were synthesized and screened for cytotoxicity against eight cancer cell lines (including HN9, FaDu, MCF7, A375, HEPG2, HuH7, A549, and HCT116) and two normal cell lines (OEC and HSF). Among them, HB183, HB209, and HB210 exhibited the most potent growth inhibition (GI) activity, with average values of 78.25%, 76.34%, and 79.14%, respectively—surpassing the reference drug doxorubicin (61.89%). HB183 demonstrated the strongest cytotoxic effects, with IC50 values of 9.72 µM (MCF7), 13.28 µM (HCT116), 13.50 µM (A549), and 31.28 µM (HEPG2), significantly outperforming doxorubicin across multiple cell lines. Importantly, HB183 showed selective cytotoxicity with lower GI% values against normal OEC (53.90%) and HSF (42.27%) cells. Mechanistic investigations revealed that HB183 upregulated key pro-apoptotic proteins—BAX (1.39-fold), caspase-3 (1.18-fold), caspase-7 (1.20-fold), and caspase-9 (1.45-fold)—while downregulating anti-apoptotic markers such as BCL-2 (1.22-fold), MMP2 (1.15-fold), and MMP9 (1.30-fold). Furthermore, flow cytometry analysis indicated that HB183 induced cell cycle arrest at the pre-G1 phase in MCF7 cells, increasing the population from 94.32% to 98.84%. Molecular docking, molecular dynamics simulation (for 500 ns), and MM-GBSA calculations for the lead analogue (HB183) towards the BCL-2 target, as a crucial one in the pathway of apoptosis induction, were performed to support the mechanistic investigation. These findings suggest that HB183 is a promising lead for further development as a selective and potent anticancer agent, particularly in the treatment of breast cancer.

Several pathological conditions, including glaucoma, malignant brain tumors, and renal, gastric, and pancreatic carcinomas, are commonly associated with carbonic anhydrase type II (CA-II). Additionally, CA-II plays a critical role in regulating bicarbonate concentration in the eyes. The inhibition of CA-II reduces aqueous humor production and thus lowers intraocular pressure associated with glaucoma. This study aimed to synthesize potent CA-II inhibitors, 5-nitro-1H-benzo[ d]imidazole-2(3H)-thione (5NBIT) and acylhydrazone derivatives (1-13). In this study, a new series of potent CA-II inhibitors, 5-nitro-1H-benzo[d]imidazole- 2(3H)-thione (5NBIT) and acylhydrazone derivatives (1-13), were synthesized and characterized by IR, NMR, UV and mass spectroscopy and evaluated against bovine carbonic anhydrase-II (bCA-II). Interestingly, most of the compounds showed better inhibition than the standard drug, acetazolamide (IC50: 18.2±0.51 μM), such as compounds 1 (IC50: 10.5±0.81 μM), 2 (IC50: 11.3±0.36 μM), 3 (IC50: 16.5±0.53 μM), 4 (IC50: 15.8±1.02 μM), 5 (IC50: 13.7±1.03 μM), and 9 (IC50: 12.2±1.03 μM). Among the synthesized compounds, compound 7 (IC50: 8.2±0.32 μM) exhibited the highest and compound 6 (IC50: 27.6±0.39 μM) showed the lowest inhibition. Structure-activity relationships suggest that the presence of nitro group on the phenyl ring contributed significantly to the overall inhibitory activity. Molecular docking of all the active compounds was performed to predict their binding behavior, which indicated good agreement between docking and experimental findings. Moreover, the MD simulation of compound 7 also showed excellent binding behavior and binding energy within the binding cavity of bCA-II. These findings suggest that the synthesized 5NBIT and acylhydrazone derivatives exhibited potent CA-II inhibition, with several compounds outperforming the standard drug acetazolamide. These results provide valuable insights for the development of novel CA-II inhibitors with potential therapeutic applications in glaucoma and other related conditions.

Harnessing nature's building blocks: potent and safe urease inhibition by simple amino acids.

Discovery of Mangifera indica-based natural inhibitors against TEM-1 β-lactamase from Escherichia coli using machine learning approaches.

Background: The development of Multi-Target-Directed Ligands (MTDLs) has emerged as a significant strategy for addressing complex, overlapping pathologies such as cancer and Alzheimer's disease (AD). This study aims to provide a robust computational framework for the design of dual-target inhibitors. Methods: This study presents an integrated and rigorous computational pipeline combining Quantitative Structure-Activity Relationship (QSAR) modeling, Molecular Docking, and Molecular Dynamics (MD) simulations with Dynamic Cross-Correlation Matrix (DCCM) analysis. Using a dataset of 57 known tubulin inhibitors, two high-performing QSAR models were developed to guide the rational design of 16 novel trimethoxyphenyl-based analogues. Results: Following ADMET and drug-likeness filtering, Lead Candidates 15 and 16 were identified. Quantitative activity predictions confirmed their enhanced potency thresholds, which were subsequently validated through static docking against β-tubulin (PDB: 4O2B) and Acetylcholinesterase (PDB: 1EVE). In total, 100 ns MD simulations and MM-GBSA calculations demonstrated superior binding stability and energetically favorable profiles for both targets, while DCCM analysis confirmed the functional synchrony of the protein-ligand complexes. Conclusions: The results provide a validated structural hypothesis for dual-target inhibition. The identified leads, 15 and 16, demonstrate strong predictive potential and are prioritized for chemical synthesis and in vitro biological evaluation.

The coronavirus disease 2019 (COVID-19) pandemic, caused the by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has had a profound impact on public health, overburdening healthcare systems, and disrupting global economies. Moreover, the absence of specific antiviral drugs remains a major challenge in COVID-19 treatment. The SARS-CoV-2 main protease (Mpro) is a crucial therapeutic target due to its essential role in viral replication. The objective of this study was to identify natural compounds with potential inhibitory activity against SARS-CoV-2 Mpro, which could be used alone or in combination with repositioned drugs for the treatment of COVID-19. A total of 224,205 natural compounds from the ZINC database were virtually screened against SARS-CoV-2 Mpro using a sequential molecular docking protocol with increasing levels of exhaustiveness. The top 88 compounds were further evaluated using MM-GBSA calculations to determine their binding free energies. Molecular dynamics (MD) simulations (100 ns) were conducted for the top four compounds to assess complex stability and ligand interactions. Structural stability and protein-ligand interactions were assessed using various statistical parameters. Post-MD binding free energy calculations were also performed. Four compounds, ZINC000085626103, ZINC000085625768, ZINC000085488571, and ZINC000085569275, were identified based on their docking scores (ranging from -11.876 to -12.682 kcal/mol) and MM-GBSA binding energies (ranging from -50.11 to -64.8 kcal/mol). All these compounds formed stable complexes with Mpro during MD simulations, with ZINC000085488571 exhibiting the lowest protein RMSD (0.15 ± 0.02 nm) and RMSF (0.10 ± 0.04 nm). These compounds interacted with key active site residues and maintained stable hydrogen bonding and compact structures throughout the simulation. Post-simulation binding free energy values ranged from -38.29 to -18.07 kcal/mol, further indicating strong and stable binding affinities. The in silico screening results confirmed the strong binding affinity and structural stability of the selected natural compounds at the SARS-CoV-2 Mpro active site. The MD simulation results further highlighted consistent engagement with catalytically relevant residues, indicating their potential for inhibitory activity. This study identifies four natural compounds with strong binding affinity and structural stability against SARS-CoV-2 Mpro, supporting their candidacy for further investigation as potential antiviral agents for COVID-19 treatment.

This study reports the design and synthesis of a series of pyrazole Schiff bases and their evaluation as potential antibacterial agents against methicillin-resistant Staphylococcus aureus (MRSA). The compounds were synthesized via condensation of pyrazole amines with aromatic aldehydes and characterized using FT-IR, NMR, and elemental analysis. Pharmacophore modeling and ADMET predictions indicated favorable pharmacokinetic properties. Among the synthesized derivatives, compound 7i showed the most promising results, with a docking score of -7.4 kcal/mol against the PBP2a enzyme of MRSA and a binding free energy of -42.8 kcal/mol from MM-GBSA calculations. Molecular dynamics simulations confirmed the stability of the 7i-PBP2a complex, while density functional theory (DFT) analysis revealed a HOMO-LUMO gap of 4.28 eV, indicating strong stability and reactivity. Antibacterial studies demonstrated that compound 7i exhibited a minimum inhibitory concentration (MIC) of 84 µg/mL and a zone of inhibition of 10 mm at 100 µg, highlighting measurable activity against MRSA. Compared with standard antibiotics, these results suggest that pyrazole Schiff bases, particularly compound 7i, represent a novel structural class with potential as lead molecules for the development of new anti-MRSA agents.

Inhibition of dipeptidyl peptidase 4 (DPP-4) is a crucial therapeutic strategy for the management of type 2 diabetes mellitus (T2DM). However, current inhibitors often exhibit unwanted toxicity, underscoring the need to discover novel, selective, and safer alternatives. This study employs an integrated computational pipeline to accelerate the identification of new DPP-4 inhibitor candidates. To that effect, GPU-accelerated molecular docking of 30,699 bioactive PubChem compounds was combined with molecular dynamics (MD) simulations and membrane permeability analyses. A workflow that systematically filters candidates was presented based on the score binding predicted by Uni-Dock. Subsequently, the stability of 32 promising protein-ligand systems was assessed using 100 ns MD trajectories, confirming their stable binding to the DPP-4 active site. Compounds EPZ005687, OSU-03012, and bemcentinib showed higher binding affinity and more favorable interactions within pockets S1, S2, S1', S2', and S2 ' than the FDA-approved reference drugs like alogliptin, based on MM-GBSA calculations. To assess the therapeutic viability of the candidates, their cellular absorption potential was also investigated. Permeability (free energy of transfer profile) and interactions were calculated via Umbrella Sampling and long-time MD across a physiologically relevant enterocyte membrane model. The results revealed that EPZ005687, OSU-03012, and bemcentinib exhibited better permeation characteristics than alogliptin. This combined evidence of high target affinity and enhanced cellular permeability strongly suggests these compounds are up-and-coming antidiabetic agents. These findings demonstrate the efficacy of this integrated computational strategy, along with the utilization of rigorously filtered public databases, for accelerating the discovery of safer and more effective antidiabetic treatments.

Protein arginine methyltransferase 5 (PRMT5) is a key epigenetic enzyme that catalyses symmetric arginine methylation on histone and non-histone proteins, influencing chromatin organisation, RNA splicing, and oncogenic signalling. Its overexpression and dependency in MTAP-deleted cancers such as glioblastoma, pancreatic adenocarcinoma, and non-small cell lung carcinoma highlight its therapeutic relevance. This study presents an integrative computational framework combining quantitative structure-activity relationship (QSAR) modelling, molecular docking, molecular dynamics (MD) simulations, and network pharmacology to identify potential PRMT5 inhibitors. The best QSAR models based on machine learning techniques used different fingerprint representations and algorithms to describe chemical structures; Random Forest models trained on PubChem and MACCS descriptor combinations provided the most accurate predictions. Analysis of consensus QSAR models identified two highly active PRMT5 inhibitor candidates (CHEMBL4539612 and CHEMBL4577464), with high affinity for binding (-13.5 to -13.7kcal/mol) to the PRMT5 active site and interactions similar to those of the known clinical PRMT5 inhibitor ONAMETOSTAT. Molecular dynamics simulations showed that both candidate molecules-maintained stability throughout the PRMT5 catalytic cleft, due to consistent hydrogen bonding, compact conformations, and low negative binding free energy values determined by MM-GBSA calculations. Network pharmacology analysis indicated that PRMT5 and its interacting partners are mainly associated with histone arginine methylation and spliceosomal assembly, processes that are frequently dysregulated in MTAP-deficient cancers. These findings suggest CHEMBL4539612 and CHEMBL4577464 as promising scaffolds for the development of selective PRMT5 inhibitors in epigenetic cancer therapy.

An important worldwide problem is the resistance of Plasmodium falciparum to practically all antimalarial medications. Therefore, new treatment approaches are urgently needed. The development of antimalarial medications frequently involves two important therapeutic targets: casein kinase 2 (CK2) and cGMP-dependent protein kinase (PKG). To identify naturally occurring chemicals that could be used as antimalarial medications to combat multidrug-resistant P. falciparum, we used a multi-targeted in silico strategy in this study. The top 20 compounds, including the reference drug RY-1–65, were selected after pharmacophore-based virtual screening of naturally produced compounds. These compounds were subsequently docked onto both target proteins using Maestro (Schrödinger 2020−3). The best-scoring compounds against PKG and CK2 were Ligand-9 (−7.490 kcal/mol) and Ligand-13 (−11.468 kcal/mol), respectively. These lead compounds may be useful as therapeutic targets based on an assessment of their pharmacological, toxicological, and bioactivity characteristics. Furthermore, Ligand-13’s strong reactivity and stability were demonstrated by density functional theory analysis, and these findings were confirmed by molecular dynamics simulations and binding free energy MMGBSA calculations. These results imply that Ligand-13 may be a promising antimalarial medication.

Trinitrotoluene (TNT) is widely used in military and industrial fields due to its strong explosive properties and chemical stability. However, its persistence in the environment and harmful effects on living organisms make it important to develop sensitive and selective detection methods. Previous research has identified the Escherichia coli genes yadG and aspC as promising components for TNT biosensors, based on their increased gene expression in response to TNT exposure. Although these findings are promising, it is still unclear whether the proteins produced from these genes directly interact with TNT at the molecular level. This study focuses on analyzing the binding interactions between TNT and the protein products of yadG and aspC using computational methods. Molecular docking showed that TNT binds more strongly to yadG (- 6.81 ± 0.02kcal/mol) than to aspC (- 6.23 ± 0.00kcal/mol). Further analysis using molecular dynamics simulations with MM-GBSA calculations confirmed that the yadG-TNT complex is more stable, with a binding free energy (ΔG) of - 23.58kJ/mol, in line with fluorescence data that also indicated stronger binding to yadG. TNT binding to yadG involves aromatic residues (Tyr-106, His-153) and hydrophobic contacts (Ala-150), which may promote π-π stacking and suggest reduced water occupancy. These features highlight key principles for protein engineering and suggest a clear route from computational findings to biosensor development.

ABSTRACT Tryptophan catabolism through the kynurenine pathway produces the oncometabolite kynurenine, which is strongly implicated in cancers such as triple-negative breast cancer (TNBC). The enzymes indoleamine 2,3-dioxygenase (IDO1) and tryptophan 2,3-dioxygenase (TDO) drive this pathway and promote an immunosuppressive tumour microenvironment, making them an attractive therapeutic target. However, no approved drug currently inhibits both enzymes simultaneously. In this study, we employed a machine learning (ML)-driven virtual screening pipeline to identify potent dual IDO1 and TDO inhibitors. Initially, an in-house ML classification model was developed using IC50 values from 1,037 distinct dual inhibitors sourced from the ChEMBL and BindingDB databases. Among the various models evaluated, the eXtreme Gradient Boosting with Random Forest (XGBRF) classifier achieved the highest performance (95% accuracy) and was selected to screen the MEGxp database. Subsequent molecular docking, MM-GBSA calculations, rescoring, and ADMET profiling identified two promising candidates, NP000319 and NP003833. Both compounds also showed predicted anticancer potential against MDA-MB-231 TNBC cells. Furthermore, the stability of the protein-ligand complexes was confirmed through 100 ns molecular dynamics simulations. Overall, the study highlights the value of ML-driven dual-inhibition strategies and provides strong leads for future experimental validation and potential therapeutic development for TNBC.

This study aimed to investigate the antioxidant activities of ethanol extracts from the flower, stem, and leaf parts of Amphoricarpos praedictus using both in silico and in vivo methods. Secondary metabolites were identified by LC-MS/MS, while total phenolic content (TPC), total flavonoid content (TFC), DPPH radical scavenging activity, FRAP, and CUPRAC reducing capacities, as well as total antioxidant status (TAS) and total oxidant status (TOS) levels, were measured spectrophotometrically. LC-MS/MS analysis identified quinic acid, protocatechuic acid, chlorogenic acid, rutin, hesperidin, and apigenin as the active secondary metabolites. Antioxidant activity showed a strong correlation with the higher phenolic and flavonoid content of the extracts. Density functional theory (DFT) calculations indicated that quinic acid is the most stable molecule, whereas rutin is the most reactive. Molecular docking revealed that fumaric acid exhibited the strongest interactions with key amino acid residues. To validate the docking results, MM-GBSA calculations were performed, demonstrating that rutin had the most negative binding free energies for both proteins (-51.324kcal/mol for 1Q41 and -38.340kcal/mol for 4UND). Overall, A. praedictus contains significant amounts of secondary metabolites and exhibits strong potential as a natural source of antioxidants.

A series of fifteen novel zerumbone-amide-triazole hybrids 12a-i and 15a-f were successfully designed and synthesized from azazerumbone II (2) via click reaction. The cytotoxicity of these derivatives was evaluated against four human cancer cell lines: gastric carcinoma (AGS), hepatocellular carcinoma (HepG2), lung carcinoma (A549), and acute leukemia (HL-60). Most derivatives displayed significantly improved cytotoxicity compared with the parent compound 9, and several hybrids showed low-micromolar potency. These results highlight the crucial role of the simultaneous incorporation of secondary amide and 1,2,3-triazole pharmacophores into the zerumbone scaffold in enhancing anticancer activity. In particular, compound 12g was the most active derivative, exhibiting IC50 values of 3.25 μM (AGS), 2.21 μM (HepG2), 3.84 μM (A549) and 2.43 μM (HL-60), while 15e also demonstrated consistently strong activity across all cell lines. Molecular docking suggested that the hybrids preferentially associate with non-canonical surface regions within the Rel homology domain (RHD) of NF-κB p65, rather than occupying the DNA-binding groove, with key contacts involving residues such as Phe298, Phe301, Pro303, Lys337 and Lys318. To further assess interaction stability, 50 ns molecular dynamics simulations and MM-GBSA calculations were performed, supporting productive surface binding for the most active ligands and helping discriminate less active candidates. Mechanistically, Western blot analysis in HepG2 cells showed that compound 12g reduced NF-κB p65 and phospho-p65 (Ser536) levels, together with phospho-IκB-α (Ser32), predominantly at 2× IC50, suggesting attenuation of NF-κB activation at higher effective concentrations. Overall, the combined experimental and computational results support zerumbone-amide-triazole hybrids as promising cytotoxic leads, with NF-κB p65 modulation likely contributing to their biological effects.