Uterine fibroids (UFs) are the most common benign tumors of female genital diseases, unlike uterine leiomyosarcoma (LMS), a rare and aggressive uterine cancer. This narrative review aims to discuss the biology and diagnosis of LMS and, at the same time, their differential diagnosis, in order to distinguish the biological and molecular origins. The authors performed a Medline and PubMed search for the years 1990–2022 using a combination of keywords on the topics to highlight the many genes and proteins involved in the pathogenesis of LMS. The mutation of these genes, in addition to the altered expression and functions of their enzymes, are potentially biomarkers of uterine LMS. Thus, the use of this molecular and protein information could favor differential diagnosis and personalized therapy based on the molecular characteristics of LMS tissue, leading to timely diagnoses and potential better outcomes for patients.

Chemotherapy resistance of ovarian cancer, regarded as the most lethal malignant gynecological disease, can be explained by several mechanisms, including increased activity of efflux transporters leading to decreased intracellular drug accumulation, increased efflux of the therapeutic agents from the cell by multidrug-resistance-associated protein (MRP1), enhanced DNA repair, altered apoptotic pathways, silencing of a number of genes, as well as drug inactivation, especially by glutathione transferase P1 (GSTP1). Indeed, GSTP1 has been recognized as the major enzyme responsible for the conversion of drugs most commonly used to treat metastatic ovarian cancer into less effective forms. Furthermore, GSTP1 may even be responsible for chemoresistance of non-GST substrate drugs by mechanisms such as interaction with efflux transporters or different signaling molecules involved in regulation of apoptosis. Recently, microRNAs (miRNAs) have been identified as important gene regulators in ovarian cancer, which are able to target GST-mediated drug metabolism in order to regulate drug resistance. So far, miR-186 and miR-133b have been associated with reduced ovarian cancer drug resistance by silencing the expression of the drug-resistance-related proteins, GSTP1 and MDR1. Unfortunately, sometimes miRNAs might even enhance the drug resistance in ovarian cancer, as shown for miR-130b. Therefore, chemoresistance in ovarian cancer treatment represents a very complex process, but strategies that influence GSTP1 expression in ovarian cancer as a therapeutic target, as well as miRNAs affecting GSTP1 expression, seem to represent promising predictors of chemotherapeutic response in ovarian cancer, while at the same time represent potential targets to overcome chemoresistance in the future.

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.

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.