Eriodictyol Flavanones Based Virtual Screening of Bioactive Compounds from ChEMBL 2D Database with Classic 3-point Pharmacophore Screening Method for HER2 Inhibitors for Breast Cancer

Abstract

Understanding binding interactions between flavanones and human epidermal growth factor receptor 2 (HER2) is an important step in developing effective treatments for breast cancer, and this study applies computational methods to do just that. This research presents a comprehensive computational methodology for identifying potential HER2 inhibitors with a focus on breast cancer treatment. The study leverages a combination of structural and pharmacophore-based approaches, starting with bioactive compound selection from the ChEMBL 2D database. The PDB-REDO refined crystal structure of Kinase domain of Human HER2 (erbB2) was used to conduct molecular docking simulations with the identified drugs. The Kleywegt-like plot analysis demonstrates the improved structural quality of the HER2 kinase domain after refinement, showing enhanced agreement with experimental data. Molecular docking simulations, conducted using the AutoDock tool, reveal the binding affinity and interaction patterns of selected compounds with the HER2 receptor. Virtual screening results highlight compounds with high binding affinity, favorable interaction patterns, and structural compatibility as potential lead candidates. To ensure safety and efficacy, ADMETox filtering was employed, providing insights into the compound’s toxicity profile and pharmacokinetic attributes. The selected compound, Eriodictyol (C20H20O6), exhibits a generally favorable safety profile, with predicted inactivity across multiple toxicity classifications and endpoints. While immunotoxicity is predicted, the overall low probabilities suggest a relatively low risk. Physicochemical and pharmacokinetic assessments indicate Eriodictyol’s potential for drug development. With a molecular weight of 356.37 g/mol, balanced lipophilicity, and high gastrointestinal absorption, the compound aligns with drug-likeness criteria. However, careful consideration is warranted due to its inhibitory effects on certain enzymes and alerts for catechol_A and isolated_alkene. In conclusion, this integrated computational approach streamlines the identification of potential HER2 inhibitors, offering a systematic strategy for drug discovery. Eriodictyol emerges as a promising candidate, demonstrating a favorable safety profile and pharmacokinetic attributes, paving the way for further in-depth studies and development as a potential therapeutic agent for breast cancer.