Lecanoric Acid As a Multi-Target Candidate Against Breast Cancer: In Silico Interactions With 17β-HSD1, ERα, EGFR, Bcl-xL and ADMET Profiling

Aim: Breast cancer is a common disease in women with high morbidity and mortality. Although various treatment modalities are available, chemoresistance remains a major problem in breast cancer. This study aimed to investigate the interactions of lecanoric acid, a natural compound with bioactive properties, with receptors considered therapeutic targets in breast cancer.Materials and Methods: The 3D structures of the target proteins 17β-HSD1 (1FDW), ERα (6CBZ), EGFR (1M17), and Bcl-xL (2W3L) were retrieved from the RCSB Protein Data Bank (RCSB PDB; https://www.rcsb.org) using their PDB IDs. The 3D structure of lecanoric acid was downloaded from the PubChem database and prepared for analysis. AutoDock Vina was used for molecular docking analyses. Ligand-receptor interactions were visualized using Discovery Studio 2021 (BIOVIA, USA). In addition, the physicochemical, medicinal chemistry, pharmacokinetic, and toxicity profiles of lecanoric acid as a drug candidate were comprehensively evaluated using ADMETlab 3.0.Results: Molecular docking analyses indicated that lecanoric acid bound to the target proteins with docking scores ranging from -7.1 to -7.7 kcal/mol. In addition, the probability of P-gp inhibition by lecanoric acid was predicted to be very low, and the radar plot showed that the evaluated ADMET parameters remained within the predefined lower and upper limits.Conclusions: Lecanoric acid was found to exhibit notable binding affinity toward 17β-HSD1, ERα, EGFR, and Bcl-xL, which are of critical importance in breast cancer pathology. Although lecanoric acid appears to have important advantages in terms of its physicochemical, medicinal chemistry, pharmacokinetic, and toxicity profiles, in vitro and in vivo studies are needed to validate its therapeutic potential.