Search Results (279)

Immune checkpoint inhibitors targeting the PD-1 (Programmed Cell Death Protein 1)/PD-L1 (Programmed Death-Ligand 1) axis have transformed cancer therapeutics, yet their efficacy in gynecologic malignancies particularly high-grade serous ovarian carcinoma remains disappointingly limited. This therapeutic resistance stems from a highly orchestrated, multidimensional immunosuppressive tumor microenvironment (TME) characterized by the convergent actions of regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and an inhibitory cytokine network (IL-10, TGF-β, VEGF). Emerging evidence positions TIGIT (T-cell immunoreceptor with immunoglobulin and ITIM domain) as a master checkpoint integrator that coordinately regulates CD8+ T-cell exhaustion, NK-cell dysfunction, and Treg-mediated suppression. Dual blockade of PD-1 and TIGIT represents a mechanistically rational strategy to dismantle this immunosuppressive fortress. This review synthesizes current understanding of the gynecologic TME architecture, delineates the molecular and cellular basis for TIGIT/PD-1 synergy, critically evaluates ongoing clinical translation efforts, and proposes an integrative framework leveraging spatial transcriptomics, single-cell resolution immunoprofiling, and patient-derived experimental models to accelerate biomarker-driven therapeutic development. Full article

Identification of ligands targeting essential enzymes in Mycobacterium species remains an important strategy for anti-tuberculosis drug discovery. Here, a native mass spectrometry approach was employed using pooled 100-compound mixtures, enabling the direct detection of intact HPPK–ligand complexes in solution. Dual-mode MS acquisitions (low collision energy for complex detection and high collision energy for ligand confirmation), combined with an automated data analysis workflow, ensured robust identification of binding events from these complex samples. This strategy led to the identification of several HPPK-binding small molecules, all belonging to the dammarane triterpene glycoside (ginsenoside) class. Subsequent analysis of the hits revealed clear structure–affinity relationships, highlighting how specific aglycone modifications and glycosylation patterns influence binding to HPPK. Our findings expand the known chemical space of HPPK ligands and demonstrate the utility of native MS-based screening coupled with automated data analysis to uncover new ligand scaffolds for challenging enzyme targets. Full article

Epithelial ovarian cancer (EOC) remains one of the most aggressive gynecological malignancies, largely due to late-stage diagnosis, therapeutic resistance, and molecular heterogeneity. This study aimed to identify biologically relevant hub genes and evaluate potential dual-target compounds against Cyclin-Dependent Kinase 1 (CDK1) and DNA Topoisomerase II Alpha (TOP2A) through an integrated computational framework. Transcriptomic datasets from GSE28799, GSE54388, and GSE14407 were analyzed to identify overlapping differentially expressed genes, followed by protein–protein interaction analysis, functional enrichment, survival assessment, molecular docking, ADMET profiling, and molecular dynamics simulations. Mechanistically, CDK1 and TOP2A participate in coordinated cell-cycle regulation associated with G2/M progression and chromosomal dynamics in ovarian cancer. Among the identified hub genes, CDK1 and TOP2A demonstrated marked overexpression and central topological importance within the interaction network. Functional enrichment analyses highlighted significant associations with mitotic cell-cycle regulation, DNA replication, and proliferative signaling pathways. Molecular docking analyses identified Naringin as a potential dual-target candidate with favorable binding affinity toward both CDK1 and TOP2A. ADMET profiling suggested acceptable pharmacokinetic and toxicity characteristics, while molecular dynamics simulations supported stable protein–ligand interactions under dynamic conditions. Although survival analyses did not demonstrate statistically significant independent prognostic associations, the findings support the biological relevance of CDK1 and TOP2A in EOC progression. Collectively, this study provides an integrated computational perspective on CDK1/TOP2A-associated oncogenic signaling and prioritizes Naringin as a preliminary candidate for future experimental investigation in epithelial ovarian cancer. Full article

Background/Objectives: Aldo–keto reductase isoforms AKR1C1–3 and 17β-hydroxysteroid dehydrogenase 1 and 2 (17β-HSD1 and 17β-HSD2) are key enzymes in steroid metabolism and validated targets in hormone-dependent cancers. Methods: In this study, Δ¹⁵- and 15β-substituted estrone derivatives were evaluated as inhibitors of AKR1C1–3 and 17β-HSD1 using enzymatic assays, cell viability assaysand computational modeling. Cellular uptake of the fluorescent estrone-based inhibitor was investigated using confocal microscopy. Results: The Δ¹⁵-estrone derivative showed potent and selective inhibition of 17β-HSD1 in the low nanomolar range, while 15β-O-propargyl and 15β-azide derivatives exhibited dual inhibitory activity against 17β-HSD1 and AKR1C2. The Δ¹⁵- and 15β-azide derivatives reduced cell viability in hormone-dependent breast, endometrial, and ovarian cancer cell lines in the sub- to low-micromolar range. A BODIPY-labeled 15β-O-propargyl analogue retained submicromolar inhibitory potency toward 17β-HSD1, representing the first fluorescent estrane-based inhibitor with preserved biological activity. Confocal microscopy confirmed efficient cellular uptake and predominant cytosolic localization in MCF-7 cells. Conclusions: These findings identify Δ¹⁵- and 15β-modified estrone derivatives as promising single- and dual-target inhibitors and introduce a fluorescent probe suitable for investigating intracellular steroid metabolism in hormone-dependent malignancies. Full article

Background: Esophageal squamous cell carcinoma (ESCA) represents one of the most common aggressive malignancies worldwide. Insulin-like growth factor binding protein 1 (IGFBP1), a typical member of the IGF superfamily, is closely linked to adverse prognosis in numerous cancers. Up to now, little is known about its functional relevance to cell migration and tumor progression in ESCA. This work focuses on clarifying the relationship between IGFBP1 expression and the progression and migratory characteristics of ESCA. Methods: mRNA expression profiles from ESCA patients were obtained from the TCGA and GEO databases. Differential expression analysis was performed using R software(version 4.2.2), followed by an intersection of DEGs between datasets. The STRING database was applied to establish PPI networks. Cytoscape software(Version 3.7.2) was then used for visual presentation and hub gene identification. IGFBP1 expression was validated in ESCA tissues versus adjacent normal tissues. Prognostic correlation was assessed using GEPIA, while diagnostic and predictive values were evaluated through ROC analysis and Cox regression. Genetic alterations of IGFBP1 were analyzed via cBioPortal. Immune cell infiltration patterns were investigated using TIMER. Functional enrichment analyses (GO, KEGG) were performed on IGFBP1-associated DEGs. In the in vitro experiments, esophageal cancer cell lines (such as Eca109 and TE-1) and normal human esophageal epithelial cell lines (such as HEEC) were selected. The transcriptional level of IGFBP1 was examined using RT-qPCR, while Western blot analysis was conducted to validate its protein expression changes. Changes in the proliferative capacity of cancer cells after IGFBP1 silencing were detected by the CCK-8 assay, and cell migration capacity was determined via wound scratch assays to clarify the related biological effects. Results: Overall, 2870 DEGs were screened from the GEO database, 153 DEGs were screened from the TCGA database, and 34 genes were found to be common to both databases; 10 core genes were screened from the PPI network. IGFBP1 was abnormally expressed in esophageal cancer. Cox regression confirmed that IGFBP1 is an independent risk factor, and prognostic analysis indicated that IGFBP1 is closely associated with poor prognosis. Gene mutation analysis showed that amplification mutations are the most common type of IGFBP1 gene mutation, and genetic alterations in IGFBP1 in ESCA patients are significantly associated with overall survival (OS) (p = 0.0002568). GO analysis indicated that IGFBP1-related differentially expressed genes were enriched in organic anion transport, epidermal development, apical cell components, and metal ion transmembrane transporter activity. Pathway enrichment based on the KEGG database illustrated the main enrichment of target genes in neuroactive ligand–receptor interactions, calcium signaling and cAMP signaling pathways. Additionally, remarkable differences in immune cell infiltration were observed between IGFBP1 high-expression and low-expression subgroups through tumor immune profiling. IGFBP1 expression differed significantly between esophageal cancer cells and normal esophageal epithelial cells, as detected by RT-qPCR (p < 0.05). Moreover, knockdown of IGFBP1 markedly inhibited the proliferation (p < 0.05) and migration abilities (p < 0.05) of TE-1 and Eca109 cells. Conversely, IGFBP1 overexpression facilitated these cellular processes. Conclusions: As a key oncogenic driver for ESCA, IGFBP1 may participate in the oncogenesis of ESCA, possibly influencing clinical outcomes via IGF signaling and the tumor microenvironment. Its dual functions in tumor and immune systems suggest it might be a candidate for ESCA immunotherapy research. Full article

Background: Positron emission tomography (PET) is a molecular imaging technique that exploits the β⁺ decay of selected radionuclides to enable non-invasive in vivo investigation of biochemical and physiological processes, including early and subclinical disease alterations. Radiotracers are designed to bind specific molecular targets with high affinity and selectivity. Among the targets to which PET devotes increasing attention are G protein-coupled receptors (GPCRs)—the largest class of transmembrane receptors—which orchestrate a wide spectrum of biological outcomes and are widely implicated in human disease. Objectives: This review analyzes patents published between 2020 and 2025 focusing on GPCR-targeted PET radiotracers, highlighting design strategies, radionuclide selection, and translational perspectives across oncology, central nervous system (CNS) disorders, and inflammatory diseases. Results: Patent activity shows that most GPCR-targeted PET tracers are derived from validated ligands adapted for imaging while preserving affinity and selectivity. Oncology patents mainly favor peptide-based or modular metal–chelator platforms enabling radionuclide flexibility and theranostic extension, whereas CNS tracers rely on drug-like small molecules optimized under strict ADME and blood–brain barrier constraints. Increasing emphasis on non-orthosteric, function-sensitive, and dual-targeting approaches reflects a shift toward interrogating GPCR signaling states, while inflammatory indications remain comparatively underrepresented despite clear biological foundations. Conclusions: Current patent trends consolidate GPCR-targeted PET tracers as well-established diagnostic tools while progressively expanding their clinical utility, both as platforms supporting translational research—informing mechanistic insight and drug development—and as components of emerging theranostic strategies across multiple disease areas. Full article

Epithelial ovarian cancer (EOC) remains one of the most lethal gynecologic malignancies, largely owing to advanced-stage presentation, high rates of relapse, and the eventual emergence of therapeutic resistance. Despite the transformative success of immune checkpoint inhibitors (ICIs) across multiple solid tumors, their clinical impact in ovarian cancer has been comparatively modest. This literature review provides a comprehensive synthesis of recent advances in ICI strategies for ovarian cancer (OC), with particular emphasis on phase II and III clinical trials evaluating programmed cell death protein 1 (PD-1), programmed death-ligand 1 (PD-L1), cytotoxic T-lymphocyte–associated protein 4 (CTLA-4), and T cell immunoglobulin and mucin-domain-containing-3 (TIM-3)-directed therapies. Accumulating evidence indicates that PD-1/PD-L1 monotherapy yields limited clinical activity in unselected OC populations, with low objective response rates and minimal survival benefit. Dual checkpoint blockade with PD-1 and CTLA-4 inhibitors demonstrates enhanced antitumor activity, particularly in clear cell ovarian carcinoma (CCOC), albeit at the expense of increased immune-related toxicity. Large randomized trials incorporating ICI into first-line chemotherapy or maintenance settings have largely failed to improve outcomes in biomarker-unselected cohorts. Available evidence demonstrates that combinatorial approaches integrating ICI with anti-angiogenic agents, PARP inhibitors, or neoadjuvant chemotherapy provide modest benefit in selected molecular and histologic subgroups. Early-phase investigations of TIM-3–targeting strategies further expand the immunotherapeutic landscape, although clinical efficacy remains preliminary. Current evidence underscores that OC is not uniformly responsive to immunotherapy and that rational combination strategies, biomarker-driven patient selection, and improved understanding of tumor immune microenvironment heterogeneity are essential to unlocking the full therapeutic potential of ICI in this disease. Full article

Cancer is a complex and evolutionary disease, with the development of different types of cancers leading to various different defective gene mutations. Synthetic lethality is a genetic-level precision medical strategy. Currently, treating BRCA (BReast CAncer)-mutated breast or ovarian cancer cells with a chemical inhibitor (Poly(ADP-ribose) polymerase, PARPi) is a typical synthetic lethal application in clinical practice. However, PARPi therapy has been found to cause off-target effects and therapy-induced immune escape driven by PD-L1 upregulation, allowing for cancer cells to escape attack from the immune response. To overcome these challenges, we developed a core–shell structure comprising a hydrophobic core of quercetin (Q)-mediated PARP inhibition and iron oxide nanoparticles (IONPs), enveloped by a hydrophilic fucoidan (Fu) shell to encapsulate short hairpin RNA targeting Programmed Death Ligand 1 (shPD-L1) for efficient gene transfection (shPD-L1@QIO@Fu). Structurally, the incorporation of quercetin into the intermediate hydrophobic layer enables modulate of the PARP effect, while the inner aqueous core with shPD-L1 gene silencing can inhibit the expression of PD-L1 protein. In this study, we proved that shPD-L1@QIO@Fu demonstrated a dual therapeutic mechanism against BRCA-mutant cancer cells by inducing extensive DNA double-strand breaks and promoting apoptosis. Furthermore, the combined action of quercetin-mediated DNA damage and shPD-L1-driven PD-L1 suppression led to a significant reduction in PD-L1 mRNA to approximately 5% at 72 h and decreased surface PD-L1 below baseline by 96 h. This effectively suppresses PARPi-induced PD-L1 upregulation and enhances antitumor immunity. These findings demonstrate the therapeutic efficacy of shPD-L1@QIO@Fu nanomedicine, providing a promising foundation for advanced co-delivery strategies to synergize PARP inhibition mediated synthetic lethality with immune checkpoint blockade in next-generation precision medicine. Full article

Background/Objectives: Immune evasion remains a critical barrier to effective hepatocellular carcinoma (HCC) therapy. Lactate dehydrogenase A (LDHA) drives lactate accumulation and histone lysine lactylation (Kla), reshaping the immunosuppressive microenvironment, while bromodomain-containing protein 4 (BRD4) sustains B7-H3 transcription via super-enhancer occupancy. Despite their synergistic roles in the lactate–Kla–B7-H3 immunosuppressive axis, no dual-target inhibitor simultaneously engaging both proteins has been reported. This study aimed to discover dual LDHA/BRD4 inhibitors from natural product libraries using an integrated AI-driven computational pipeline. Methods: We established a multi-tier virtual screening cascade comprising Lipinski/QED drug-likeness filtration, DiffDock-based AI docking, QuickVina binding energy validation, PLIP interaction profiling, 200 ns all-atom molecular dynamics simulations, MM-GBSA binding free energy calculations, and density functional theory analysis. Natural product libraries from COCONUT and CMNPD databases (84,730 compounds post-filtration) were screened against both targets. Results: High-throughput DiffDock screening identified 11 dual-target hits, from which CNP0038114.1 and CMNPD16582 emerged as prioritized lead candidates. All four protein–ligand complexes maintained structural stability throughout MD simulations, with MM-GBSA binding free energies ranging from −27.24 to −32.45 kcal/mol, predominantly driven by van der Waals interactions. DFT calculations revealed distinct electronic profiles: CNP0038114.1 exhibited a narrow HOMO–LUMO gap (2.718 eV) favoring charge-transfer reactivity, whereas CMNPD16582 displayed a larger gap (4.822 eV), suggesting superior chemical stability. Conclusions: This computational study furnishes two novel natural product leads for targeting the lactate–Kla–B7-H3 immunosuppressive axis in HCC, establishing a generalizable AI-driven workflow for dual-target inhibitor discovery. Full article

Bone metastases remain one of the most clinically devastating complications of advanced cancer, particularly in breast, prostate, and lung malignancies, where they drive pain, fractures, hypercalcemia, and progressive functional decline. Their management is further complicated by a highly immunosuppressive bone microenvironment characterized by osteoclast-driven bone destruction, myeloid cell dominance, impaired antigen presentation, and weak effector T-cell infiltration, all of which limit the activity of conventional immunotherapies. In this setting, nanoparticles are emerging not merely as passive drug carriers but as programmable platforms capable of reshaping the metastatic niche. This review discusses how bone-targeted and immune-responsive nanocarriers can improve therapeutic precision through hydroxyapatite-binding ligands, dual-targeting strategies, stealth coatings, enzyme- and pH-responsive release systems, and externally guided platforms. We further examine how these systems modulate key immune compartments within bone metastases, including reprogramming tumor-associated macrophages and myeloid-derived suppressor cells, restoring cytotoxic T-cell activity, enhancing dendritic-cell activation, and enabling in situ vaccination through photothermal or photodynamic immunogenic cell death. Particular attention is given to the delivery of checkpoint inhibitors, cytokines, siRNA/miRNA, mRNA, and clustered regularly interspaced short palindromic repeats (CRISPR)-based payloads, as well as to the rational combination of these with chemotherapy, bone-modifying agents, and radiotherapy. Finally, we highlight major translational barriers, including lesion heterogeneity, limited penetration into mineralized tissue, off-target immune effects, manufacturing complexity, and the continued lack of bone-specific preclinical and clinical validation. Collectively, immunomodulatory nanoparticles represent a promising strategy to convert bone metastases from immune-refractory sites into more therapeutically responsive lesions. Full article

Chronic neuroinflammation driven by microglial activation is a pathological hallmark of neurodegenerative diseases, and the NF-$\kappa$B/iNOS signaling axis plays a central role in propagating this damage. NF-$\kappa$B-mediated iNOS transcription generates excessive nitric oxide, causing oxidative neuronal injury. The medicinal mushroom Hericium erinaceus produces cyathane diterpenoid erinacines and isoindolinone erinacerins, both reported to attenuate neuroinflammation; however, the molecular basis of their interactions with iNOS and NF-$\kappa$B remains poorly characterized. We screened 21 erinacerins and 18 erinacines against both targets using validated molecular docking, then subjected top-ranked candidates and negative controls to 100 ns molecular dynamics simulations, MM-PBSA binding free energy calculations (±SEM), per-residue energy decomposition, backbone RMSD, and ligand–protein minimum distance analyses, with quercetin as reference. The analysis revealed scaffold-dependent target selectivity: erinacerins exhibited preferential stability with iNOS (erinacerin L: RMSD 0.185 nm), whereas erinacines formed more stable complexes with NF-$\kappa$B (erinacines G and J: RMSD < 0.36 nm). Minimum-distance monitoring confirmed that the elevated ligand RMSD in iNOS predominantly reflected surface relocation rather than dissociation. Erinacine S emerged as the most promising dual-target candidate ($\Delta G_{bind}$: −24.31 ± 0.16 and −14.24 ± 0.11 kcal/mol for iNOS and NF-$\kappa$B, respectively), over twofold stronger than quercetin for iNOS. Negative controls revealed that docking-based ranking was target-dependent in its discriminative capacity, underscoring the need for MD-based refinement. These results identify erinacine S as a priority candidate for experimental validation. Full article

Adenosine triphosphate (ATP) serves as a central energy currency and signaling molecule in cellular processes, with ATP-binding sites in proteins playing critical roles in enzymatic catalysis, signal transduction, and gene regulation. The accurate identification of ATP-binding sites is essential for understanding protein function mechanisms and facilitating drug discovery, enzyme engineering, and disease pathway analysis. In this study, we present a novel hybrid deep learning framework that synergizes heterogeneous learning paradigms based on protein sequence information for accurate ATP-binding site prediction. Our approach integrates two complementary base classifiers. One is a Transformer-based model, which leverages high-level contextual embeddings generated by Evolutionary Scale Modeling 2 (ESM-2), a state-of-the-art protein language model, combined with a local–global dual-attention mechanism that enables the model to simultaneously characterize short-segment and long-range contextual dependencies across the entire protein sequence. The other is a deep Q-network (DQN)-inspired classifier that achieves residue-level prediction as a sequential decision-making process. The final predictions are generated using a weighted ensemble strategy, where optimal weights are determined via cross-validations to leverage the strengths of both models. The prediction results on benchmark independent testing sets indicate that our method achieves satisfactory performance on key metrics. Beyond predictive efficacy, this work uncovers the intrinsic biological mechanisms underlying protein–ATP interactions, including the synergistic roles of local structural motifs and global conformational constraints, as well as family-specific binding patterns, endowing the research with substantial biological significance. The research in this work offers a deeper understanding of the protein–ligand recognition mechanisms and supportive efforts on large-scale functional annotations that are critical for system biology and drug target discovery. Full article

Alzheimer’s disease (AD) remains a significant global health challenge, highlighting the need for novel dual inhibitors targeting acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). This study investigated the trunk bark of Terminalia triptera Stapf. as a potential source of bioactive secondary metabolites for AD management. Bioassay-guided isolation led to the identification of two flavan-3-ol derivatives, epicatechin-(4β→8)-ent-catechin (1) and (−)-catechin (2), reported here for the first time from this species. In vitro assays demonstrated that the dimeric compound 1 exhibited stronger dual inhibitory activity against AChE and BChE, with IC₅₀ values of 4.41 × 10⁻⁴ and 4.75 × 10⁻⁴ mol/L, respectively, surpassing the reference compound berberine chloride. Molecular docking analysis revealed that compound 1 formed extensive interactions within both catalytic and peripheral anionic sites of the enzymes. Density Functional Theory (DFT) calculations indicated high kinetic stability, reflected by large HOMO–LUMO energy gaps (6.66–6.97 eV), while global reactivity descriptors suggested lower electrophilicity (ω = 2.19–2.34 eV), supporting a potentially favorable safety profile. Furthermore, 100 ns molecular dynamics simulations confirmed stable ligand–protein complexes stabilized by hydrogen-bond networks and deep binding within catalytic pockets. Overall, these findings highlight T. triptera and its dimeric proanthocyanidins as promising multi-target candidates for anti-Alzheimer drug development. Full article

The immunosuppressive nature of porcine reproductive and respiratory syndrome virus (PRRSV) remains the central obstacle to its effective control. Conventional microRNA (miRNA)-based antiviral approaches are limited by their modest potency and the high risk of viral escape. Here, we rationally designed an engineered miRNA carrying a 5′-triphosphate (5′-PPP) terminus that integrates RIG-I-driven innate immune activation and sequence-specific gene silencing within a single molecule. In vitro-transcribed 5′-PPP miRNAs are efficiently recognized by the pattern-recognition receptor RIG-I, triggering a robust type I interferon response that counteracts PRRSV-induced immunosuppression. In MARC-145 cells, one such construct, 5′-PPP BZL-sRNA-20, potently inhibited PRRSV replication through the synergistic action of immune activation and gene silencing. However, in porcine alveolar macrophages (PAMs)—the natural host cells for PRRSV—the antiviral effect depended primarily on 5′-PPP-induced interferon responses, with the targeting sequence providing limited or context-dependent benefits. Dual-luciferase assays confirmed that the gene-silencing activity depends on 5′-PPP modification, which enhances the stability of BZL-sRNA-20. This bifunctional strategy establishes an “immune activation plus targeting” paradigm by simultaneously acting as a RIG-I ligand that triggers broad antiviral responses and specifically cleaves viral RNA via direct base-pairing to conserved regions of the PRRSV genome. These findings reveal the potential of engineered 5′-PPP miRNAs as immunomodulatory antiviral agents, while highlighting that the contribution of RNAi targeting varies depending on the cellular context. Full article

Multitarget-directed ligands offer a promising strategy for overcoming tumor complexity through simultaneous modulation of complementary oncogenic pathways. In this work, a novel (E)-6-(3-(4-methyl-2-thioxo-2,3-dihydrothiazol-5-yl)-3-oxoprop-1-en-1-yl)-2H-chromen-2-one (compound 6) was synthesized and evaluated as a dual inhibitor of tubulin polymerization and tumor-associated carbonic anhydrases (CAs) IX and XII. Compound 6 displayed potent antiproliferative activity, particularly against MDA-MB-231 triple-negative breast cancer cells (IC₅₀ = 0.37 µM), with excellent selectivity toward non-tumorigenic cells. Mechanistic studies demonstrated strong tubulin polymerization inhibition (IC₅₀ = 3.40 ± 0.09 µM) and submicromolar inhibition of CA IX (IC₅₀ = 0.102 ± 0.005 µM) and CA XII (IC₅₀ = 0.213 ± 0.004 µM), accompanied by downregulation of CA-IX and CA-XII protein expression. Cellular investigations revealed pronounced G₂/M phase arrest and apoptosis induction via mitochondrial signaling and caspase activation. Anti-angiogenic activity was supported by inhibition of endothelial migration and concentration-dependent suppression of VEGFR-2 (Tyr1175) phosphorylation in HUVEC cells. Human liver microsomal assays indicated measurable metabolic stability, while molecular docking and in silico ADMET predictions supported target engagement and drug-like properties. Collectively, these findings identify compound 6 as a promising multitarget anticancer lead integrating antimitotic, metabolic, and anti-angiogenic mechanisms. Full article