TL;DR
Findings highlight Withaferin A as a promising natural inhibitor of UBE2J1 and provide a foundation for future experimental validation aimed at developing targeted therapies against ovarian cancer.
This study combines ligand- and structure-based in silico strategies to predict the inhibitory activity of natural flavonoids on the Polo-Like Kinase-1 (PLK-1) enzyme as candidate anticancer agents. This enzyme participates in mitosis and is overexpressed in cancer cells. Furthermore, it has been shown to have important implications for tumor metastasis, and its inhibitors are attractive starting points for drug development. First, classification models are developed using linear discriminant analysis and a multilayer perceptron neural network. Models with accuracy greater than 80%, validated using standard statistical performance metrics and applicability domain, are used for virtual screening identifying four compounds as potential antitumor drugs. Subsequently, the identified compounds are evaluated using a molecular docking methodology to verify their binding mode and interactions with the catalytic domain of PLK-1. Finally, the integration of molecular dynamics simulations, at 300 ns, with Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) thermodynamic calculations demonstrates that the hydroxylation pattern of ring B in the flavonol scaffold is the fundamental chemical-structural determinant of electrostatic interactions and the architecture of water-mediated networks. Among the evaluated flavonoids, myricetin showed the most favorable overall computational profile, including the highest virtual-screening score and the most favorable mean MM/GBSA estimate, supporting its prioritization for experimental evaluation as a potential PLK-1 inhibitor. The integration of these approaches offers a robust methodological framework for proposing candidates with a higher probability of success, in subsequent stages of experimental validation, reducing time and costs in the early stages of drug development.
Breast cancer is a prevalent and aggressive tumor affecting women, known for its molecular diversity and treatment resistance. This study investigates the anticancer potential of Icariin (ICA), a flavonol glycoside derived from Herba epimedii, against breast cancer using network pharmacology and molecular simulation. Using the SwissTargetPrediction database and GeneCards, the researchers identified 98 common targets shared by ICA and breast cancer. Gene ontology (GO) and KEGG enrichment analyses highlighted the targets' roles in the regulation of apoptosis, inflammatory signaling, receptor tyrosine kinase activity, chemokine signaling, sphingolipid metabolism, and VEGF pathways. Molecular docking revealed ICA's strong binding affinity for key oncogenic proteins, with binding energies ranging from −12 to −7.5 kcal/mol, particularly to SER783, THR862, ASP863, LYS753, and ARG849. Molecular dynamics (MD) simulations demonstrated the structural stability of the ICA‐HER2 complex, which maintained strong hydrogen bonds and exhibited minimal conformational changes over a 1000 ns trajectory, with average RMSD values of 1.7 Å for the protein and 1.0 Å for the protein‐ligand complex. Furthermore, ICA exhibited favorable pharmacokinetic properties, including moderate solubility and negligible inhibition of cytochrome P450. These findings support the hypothesis that ICA may serve as a valuable natural compound for treating HER2‐driven breast cancer; it requires further experimental validation.
Glioblastoma, the most prevalent and highly aggressive primary brain tumor, is characterized by high clinical recurrence rates and significant resistance to conventional therapies, highlighting the need for innovative targeted agents to address current treatment limitations. This study employed an integrated computational and experimental strategy to identify novel iodo-phenanthroimidazole derivatives (compounds 1-3). Compound 3 was identified as a lead candidate that inhibits HDAC1 and may trigger autophagy, thereby suppressing glioblastoma progression. Molecular docking and molecular dynamics simulations indicated stable interactions between compound 3 and the HDAC1 catalytic site (estimated binding energies of -7.75 and - 7.74 kcal/mol), with a notable halogen bond between the iodine atom and Asp104. The phenanthroimidazole scaffold was proposed as a potential zinc-binding group (ZBG) for HDAC1 inhibition. Biophysical validation using isothermal titration calorimetry (ITC) confirmed submicromolar binding affinity (Kd = 1.04 × 10-7 M, ΔH = -91.24 kJ·mol-1). In vitro evaluation demonstrated potent inhibition of U87-MG glioblastoma cell proliferation (IC50 = 0.23 μM), and flow cytometric analysis indicated concomitant cell cycle arrest at both G2/M and S phases. Transmission electron microscopy revealed autophagic vacuoles containing damaged mitochondria, and immunofluorescence showed an increased LC3-II/LC3-I ratio. Together with the observed loss of mitochondrial membrane potential and ATP depletion, these findings are consistent with the induction of a mitophagy-like process. Using an in vivo zebrafish orthotopic glioblastoma model, the lead compound demonstrated blood-brain barrier penetration and effectively suppressed tumor growth and U87-MG cell metastasis. This work highlights the potential of iodo-phenanthroimidazole derivatives as a novel therapeutic strategy for glioblastoma. The data support a model in which HDAC1 inhibition is associated with mitochondrial dysfunction and mitophagy, contributing to tumor suppression.
Cancer continues to be a major global health burden, with receptor tyrosine kinases such as EGFR, ERBB2, and VEGFR-3 being critical therapeutic targets due to their central roles in tumor growth, survival, and angiogenesis. Current therapies, while effective in some contexts, face limitations including resistance, toxicity, and high cost, highlighting the need for novel multi-target approaches. In this study, we report the isolation and computational characterization of a novel defensin-like peptide (DEFL) from Datura stramonium (GenBank accession KT371458). The peptide sequence encoded 74 amino acids and displayed characteristic cysteine-stabilized motifs. Docking simulations revealed favorable binding scores toward EGFR (- 80.6 ± 10.6), ERBB2 (- 63.6 ± 7.4), and VEGFR-3 (- 50.5 ± 6.7), with interactions involving residues located within predicted receptor-binding regions. To further assess stability, 100 ns molecular dynamics simulations were performed. RMSD profiles confirmed stable complexes, with EGFR stabilizing around 0.6-0.8 nm, ERBB2 around 0.7-0.9 nm, and VEGFR-3 at a tighter 0.3-0.4 nm. Ligand RMSDs indicated moderate flexibility for ERBB2 (peaks up to 1.3 nm) but tighter stability for VEGFR-3 (0.3-0.5 nm). RMSF analyses revealed minimal fluctuations (< 0.3 nm) at binding sites, and radius of gyration values remained stable, indicating compact receptor-peptide complexes (EGFR: 3.45-3.75 nm; ERBB2: 2.95-3.20 nm; VEGFR-3: 1.92-1.98 nm). Hydrogen bond profiling and additional trajectory analyses (DCCM and PCA) supported overall system equilibration without major structural disruption during the simulations. The Datura stramonium defensin-like peptide indicating a stable and energetically favorable peptide-receptor interactions at the computational level. Overall, the simulations indicate persistent peptide-receptor association and stable structural behavior of the complexes at the computational level. However, molecular docking and molecular dynamics simulations do not demonstrate functional inhibition of EGFR, ERBB2, or VEGFR-3, nor do they confirm anticancer efficacy. Therefore, these results should be interpreted strictly as hypothesis-generating in silico predictions, and experimental validation, including peptide synthesis, receptor-binding assays, extracellular-domain competition assays, and cancer cell-based functional studies, will be required to confirm biological relevance.