In Silico Evaluation of Hyptis Verticillata-Derived Phytochemicals Targeting Estrogen Receptor Alpha (Erα) and Progesterone Receptor in Hormone-Dependent Breast Cancer

by Dada, Emmanuel Damilo, Dearsly, Emmanuel Markus, Emmanuel Ikegima, Emmanuel Ofutet, Ogidigo, Jane Chinwe, Okoo, Blessing Ahiowawanyohe, Oshatuyi Olukayode, Peter Janet

Published: December 4, 2025 • DOI: 10.51584/IJRIAS.2025.101100020

Abstract

Hormone-dependent breast cancers, primarily driven by estrogen receptor alpha (ERα) and progesterone receptor (PR) signaling, account for most breast malignancies and remain a major therapeutic challenge due to frequent resistance to endocrine therapy. The search for novel, plant-derived ligands with dual modulatory activity on ERα and PR is therefore critical. This study employed an in silico approach to evaluate selected phytochemicals from Hyptis verticillata—a medicinal plant known for its diverse bioactive constituents—against ERα (Y537S mutant; PDB ID: 6CHZ) and PR (PDB ID: 4A2J). Seven phytocompounds were retrieved from the PubChem database and subjected to drug-likeness analysis using SwissADME, molecular docking with AutoDock Vina, and pharmacokinetic/toxicity prediction via ADMETlab 2.0. Among the screened compounds, squalene (−6.9 kcal/mol) and 4,7-methanon-1H-indene (−6.4 kcal/mol) demonstrated the highest binding affinities toward ERα and PR, respectively. Both ligands showed favorable hydrophobic interactions within the receptor ligand-binding domains, suggesting potential receptor antagonism or modulation. Drug-likeness and ADMET profiling revealed that 3a,4,5,6,7,7a-hexahydro-4,7-methanoindene and 4,7-methanon-1H-indene possess acceptable physicochemical and pharmacokinetic properties, indicating promising oral bioavailability and low toxicity risks. The findings highlight H. verticillata phytochemicals as potential scaffolds for developing multitargeted agents capable of counteracting endocrine resistance in hormone receptor–positive breast cancers. Further validation through molecular dynamics simulations and in vitro receptor-binding assays is recommended to confirm these computational predictions and explore their mechanistic potential.