Objective: To evaluate the therapeutic potential of a novel vegetable oil blend containing natural bioactive compounds for the treatment of cervical carcinoma through in silico molecular docking analysis. Methods: Natural compounds were extracted from cold-pressed pumpkin oil (Curcubita maxima), horsetail oil (Equisetum arvense), and etheric clove oil (Syzygium aromaticum). Major phytochemicals quercetin 3-O-glucoside, γ-tocopherol, apigenin 5-O-glucoside, β-caryophyllene, kaempferol 3-O-glycoside, and EGCG were identified and standardized via HPLC. Molecular docking was performed using 1-Click Docking software to assess binding affinities against cervical carcinoma-associated targets (p16INK4a, Ki-67, VEGF, CEA, MMP-9, TP53, and pRb). Docking scores were expressed as Gibbs free energy (ΔG, Kcal/mol). Comparative analyses were conducted versus conventional agents (Paclitaxel, Pembrolizumab, Temsirolimus). AI-assisted optimization using ChatGPT-4o integrated molecular interaction data from over 10,000 peer-reviewed studies. Results: Apigenin 5-O-glucoside showed the strongest interaction with MMP-9 (-11.6 Kcal/mol) and CEA (-9.4 Kcal/mol). Quercetin 3-O-glucoside exhibited high affinity for TP53 (-8.1 Kcal/mol), Ki-67 (-9.1 Kcal/mol), and VEGF (-8.7 Kcal/mol). Natural compounds consistently outperformed standard chemotherapeutics, e.g., Paclitaxel with p16INK4a (-5.4 Kcal/mol) vs. apigenin 5-O-glucoside (-8.9 Kcal/mol). These results suggest robust multi-targeted anticancer potential, including inhibition of proliferation, angiogenesis, and metastasis, along with apoptosis induction. Conclusion: Natural compounds derived from a novel vegetable oil blend demonstrate promising molecular interactions with key biomarkers of cervical carcinoma. These findings support their potential role as effective therapeutic agents and warrant further in vitro and in vivo validation.

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.

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.