This study presents a comparative analysis of molecular docking data, focusing on the binding interactions of the natural compounds apigenin and luteolin with the proteins TP-53, pRb, and APOBEC, in comparison to conventional pharmacological ligands. Advanced bioinformatics techniques were employed to evaluate and contrast binding energies, showing that apigenin and luteolin demonstrate significantly higher affinities for TP-53, pRb, and APOBEC, with binding energies of −6.9 kcal/mol and −6.6 kcal/mol, respectively. These values suggest strong potential for therapeutic intervention against HPV-16. Conventional ligands, by comparison, exhibited lower affinities, with energies ranging from −4.5 to −5.5 kcal/mol. Additionally, protein–protein docking simulations were performed to assess the interaction between HPV-16 E6 oncoprotein and tumor suppressors TP-53 and pRb, which revealed high binding energies around −976.7 kcal/mol, indicative of their complex interaction. A conversion formula was applied to translate these protein–protein interaction energies to a comparable scale for non-protein interactions, further underscoring the superior binding potential of apigenin and luteolin. These findings highlight the therapeutic promise of these natural compounds in preventing HPV-16-induced oncogenesis, warranting further experimental validation for clinical applications.

This study investigates the use of artificial intelligence (AI) and ethnobotanical knowledge to identify natural compounds with potent antiviral activity against HPV-16. Through molecular docking simulations, we evaluated the binding affinities of various essential oil components, in-cluding Apigenin, against the key antigenic determinants of HPV-16 (E6, E7 oncoproteins, and L1 major capsid protein). Apigenin exhibited strong binding affinities, particularly to E6 Oncopro-tein. To further enhance these findings, we employed an AI-driven reverse engineering approach to predict a natural compound with superior efficacy. The AI identified Luteolin, a flavonoid with additional hydroxyl groups, as a promising candidate. Comparative docking studies demon-strated that Luteolin possesses significantly stronger binding affinities to all three HPV-16 targets, surpassing the efficacy of Apigenin. This work highlights the potential of AI in accelerating the discovery and optimization of natural antiviral agents, providing a powerful tool for pharmaco-logical and ethnopharmacological screenings. Our findings suggest that AI-guided identification of natural compounds can lead to the development of more effective antiviral therapies, warranting further experimental validation and potential synthesis in laboratory settings.

Background: Malignant melanoma is characterized by molecular heterogeneity, adap-tive signaling, and limited durability of therapeutic responses. This exploratory study examined a chemically characterized dual-oil formulation composed of cold-pressed Prunus dulcis oil and Pinus sylvestris needle essential oil as an integrated life-science model linking formulation chemistry, comparator-context molecular docking, and cel-lular viability. Methods: GC-MS/FAME profiling defined the principal formula-tion-associated markers. Docking was used to prioritize structurally plausible interac-tions across a melanoma-relevant target panel, while Neutral Red Uptake assays quan-tified 24-h viability in B16F10 melanoma cells and MRC-5 fibroblasts. Spearman rank analysis was applied to the concentration–viability series to test monotonic biological coherence; a direct component-level docking-to-cellular correlation was prospectively evaluated for estimability. Results: The combined formulation yielded estimated IC50 values of 1.42% in B16F10 cells and 4.85% in MRC-5 cells (selectivity index, 3.41). Across the complete concentration range, the relationship was non-monotonic (B16F10: ρs = −0.429, p = 0.289; MRC-5: ρs = −0.381, p = 0.352), whereas the descending high-dose branch (≥0.37% v/v) showed strong inverse rank associations (B16F10: ρs = −1.000, p < 0.001; MRC-5: ρs = −0.900, p = 0.037). A statistically valid direct in silico–in vitro Spear-man coefficient could not be calculated because compound-resolved cellular pheno-types were unavailable for the six docked chemical markers. Conclusions: The data support a biologically coherent, concentration-dependent cytotoxic phenotype within the descending exposure range and define a rigorous framework for future com-pound-matched computational–experimental validation. The study should be inter-preted as hypothesis-generating rather than as evidence of cellular target engagement or therapeutic efficacy.

Background: Malignant melanoma remains a biologically aggressive cancer in which pathway redundancy and adaptive signaling can complicate durable therapeutic control. The working hypothesis is based on the following testable question: whether an archived dual-oil formulation composed of cold-pressed Prunus dulcis oil and Pinus sylvestris oil, in which α-pinene is the major component, generated a measurable NRU viability phenotype in B16F10 melanoma cells that justified subsequent standardized chemical, mechanistic, and statistical follow-up. Methods: Comparator-context docking observations were generated across a melanoma-relevant target panel, and the computational layer was used only to organize qualitative pocket-context hypotheses. The archived NRU dataset was then descriptively evaluated in B16F10 melanoma cells and MRC-5 fibroblasts. Results: The NRU data indicate an observable concentration-associated reduction in B16F10 viability for the combined formulation; and IC50/selectivity-index values were estimated from fitted dose-response curves; however, the absence of complete replicate-level raw metadata and confidence intervals requires cautious exploratory interpretation. Conclusions: The results support the cautious interpretation that a dual-oil P. dulcis and P. sylvestris formulation may serve as a pilot, hypothesis-generating anti-melanoma exploratory platform. The principal value of the study is to define the minimum experimental program required for future validation, including GC-MS batch standardization, orthogonal viability assays, replicated dose-response modeling, biochemical target assays, pathway readouts, and in vivo evaluation where justified. GC-MS/FAME profiling is incorporated as a chemical-standardization anchor for the dual-oil system. GC/MS analysis was performed to characterize the chemical profiles of cold-pressed P. dulcis oil and P. sylvestris needle essential oil, supporting chemical standardization of the dual-oil system.

Localized phytochemical formulations may provide complementary strategies for controlling mucosal colonization by Streptococcus agalactiae and Streptococcus pyogenes, but computational prioritization requires orthogonal biological validation. This study integrated molecular docking against the redox-sensing transcriptional repressor Rex of S. agalactiae and a protein tyrosine phosphatase target of S. pyogenes (SP-PTP) with in vitro broth microdilution, biofilm, target-bridging, and epithelial-tolerance experiments. Isoflavone showed the most favorable natural-compound interaction with Rex (ΔG = −8.3 kcal/mol), whereas secoisolariciresinol diglucoside (SDG) led the natural-ligand ranking for SP-PTP (ΔG = −5.2 kcal/mol). The complete formulation produced MIC50 values of 0.031% and 0.063% v/v against S. agalactiae and S. pyogenes, respectively; inhibited biofilm formation by 89.2% and 80.1%; and preserved >92% epithelial viability at 1× MIC. Among the three natural candidates with complete matched broth data, target-normalized docking and composite MIC50/MIC90/MBC50 ranks were perfectly concordant in both species; pooled species-stratified Spearman analysis yielded ρ = 1.000 (exact p = 0.0556; n = 6). In contrast, the extended panel including antibacterial comparators showed negligible concordance (ρ = 0.081; p = 0.7826; n = 14). Principal component analysis assigned 74.8% of variance to an in vitro potency axis and 24.6% to a largely orthogonal docking axis. Thus, the experiments confirmed the target-specific ordering of the natural candidates but did not support extrapolation of docking rank across mechanistically heterogeneous antibacterial classes. Intracellular target inhibition, genetic causality, and component synergy remain unestablished.

This study presents a detailed comparative analysis of Molecular Docking data, focusing on the binding interactions of conventional ligands and natural compounds, Apigenin and Luteolin, with TP-53, pRb, and APOBEC. Utilizing advanced bioinformatics techniques, coupled with Ar-tificial Intelligence software and High-Performance Computing (HPC), we measured and con-trasted the binding energies of these interactions. Additionally, we investigated protein-protein interactions between HPV-16 oncoprotein E6 and tumor suppressors TP-53 and pRb. Our findings demonstrate that the natural compounds Apigenin and Luteolin exhibit significantly higher binding affinities to TP-53, pRb, and APOBEC compared to conventional pharmacological ligands. The binding energies for Apigenin and Luteolin were approximately -6.9 kcal/mol and -6.6 kcal/mol, respectively, indicating their strong potential as therapeutic agents in inhibiting the oncogenic functions of HPV-16. In contrast, conventional ligands showed lower binding affinities, with energies around -4.5 to -5.5 kcal/mol. The study further revealed that the protein-protein interactions between E6 and TP-53, and E6 and pRb, exhibited considerably higher binding en-ergies, approximately -976.7 kcal/mol, due to the multiple interaction sites and the complex nature of protein interfaces. A conversion formula was developed to translate these high-energy inter-actions to a comparable scale for non-protein-protein interactions, highlighting the superior binding potential of natural compounds, which, through the same conversion formula, was shown to be higher than that of interaction between E6 with TP-53 and E6 with pRb. These results underscore the therapeutic promise of Apigenin and Luteolin in preventing HPV-16-related on-cogenesis. By demonstrating their higher binding affinities to crucial tumor suppressors, this study supports the development of natural compound-based therapies. The findings also em-phasize the necessity for further experimental validation to explore these compounds' efficacy in clinical settings. This comprehensive analysis provides a robust framework for understanding the comparative binding interactions and lays the groundwork for innovative therapeutic strategies against HPV-16.