Abstract
Breast cancer is one of the most prevalent cancers worldwide, ranked as the second most diagnosed cancer and the fourth leading cause of cancer-related deaths. Despite the availability of FDA-approved therapies, limitations such as drug resistance and off-target effects highlight the need for novel, multitargeted therapeutic agents. In this study, we aimed to identify and design an in-silico promising multitarget drug for breast cancer by simultaneously targeting three critical proteins: Glucocorticoid Receptor, Estrogen Receptor-alpha (ER-alpha), and Cyclin-Dependent Kinase 2 (CDK2). FDA-approved drugs corresponding to these targets were initially subjected to multitarget molecular docking to evaluate their binding affinities. Based on this screening, the 15 highest-ranking ligands were selected and underwent molecular enumeration, resulting in the generation of 14,750 novel derivative compounds. The re-docking identified 1-((R)-2,3-dihydroxypropyl) -3-(3-((R)-1-5-methyl-1H-pyrrolo [2,3-b]pyridin-3-yl)ethyl)phenyl) urea (DdpMPyPEPhU) (Patent No. 202024101028.0) as a promising multitarget candidate. The compound exhibited enhanced binding pocket engagement through numerous stabilising interactions, including hydrogen bonds, π-π stacking, and π-cation interactions, with high docking scores (-14.869 to -4.57 kcal/mol) and favourable Molecular Mechanics Generalised Born Surface Area (MM-GBSA) energies (-72.32 to -11.97 kcal/mol). Comparative docking and pharmacokinetic analyses with standard drugs Lapatinib and Tamoxifen indicated better drug-like properties and pharmacokinetic advantages for DdpMPyPEPhU. Additional validation using Density Functional Theory (DFT) optimisation, 5 ns WaterMap analysis, and 250 ns molecular dynamics simulations under neutralised conditions confirmed structural stability and strong intermolecular interactions, supported by binding free energy calculations. Overall, our computational findings suggest that DdpMPyPEPhU is a promising therapeutic candidate for breast cancer, providing a rational basis for further experimental evaluation.