Abstract

Abstract Breast cancer ranks as one of the most prevalent forms of cancer and stands as the primary global cause of mortality among women. Overexpression of EGFR and ER receptors or their genomic alterations leads to malignant transformation, disease aggression and is linked to poor patient survival outcomes. The clinical breast cancer patient’s genomic expression, survival analysis, and computational drug-targeting approaches were used to identify best-hit phytochemicals for therapeutic purposes. Breast cancer patients have genomic alterations in EGFR (4%, n = 5699) and ER (9%, n = 8461), with the highest proportion being missense mutations. No statistically significant difference was observed in the patient survival rates between the altered and unaltered ER groups, unlike EGFR, with the lowest survival rates in the altered group. Computational screening of natural compound libraries (7711) against each EGFR (3POZ) and ER (3ERT) receptor shortlists the best-hit 3 compounds with minimum docking score (ΔG = −7.9 to −10.8), MMGBSA (−40.16 to −51.91 kcal/mol), strong intermolecular H-bonding, drug-like properties with least kd, and ki. MD simulation studies display stable RMSD, RMSF, and good residual correlation of best-hit common compounds (PubChem ID: 5281672 and 5280863) targeting both EGFR and ER receptors. In vitro, studies revealed that these common drugs exhibited a high anti-proliferative effect on MCF-7 and MDA-MB-231 breast cancer cells, with effective IC50 values (15–40 μM) and lower free energy, kd, and ki (5281672 > 5280863 > 5330286) much affecting HEK-293 non-cancerous cells, indicating the safety profile. The experimental and computational correlation studies suggest that the highly expressed EGFR and ER receptors in breast cancer patients having poor survival rates can be effectively targeted with best-hit common potent drugs with a multi-target therapeutic approach. Insight Box: The findings of this study provide valuable insights into the genomic/proteomic data, breast cancer patient’s survival analysis, and EGFR and ER receptor variants structural analysis. The genetic alterations analysis of EGFR and ER/ESR1 in breast cancer patients reveals the high frequency of mutation types, which affect patient’s survival rate and targeted therapies. The common best-hit compounds affect the cell survival patterns with effective IC50, drug-like properties having lower equilibrium and dissociation constants demonstrating the anti-proliferative effects. This work integrates altered receptor structural analysis, molecular interaction-based simulations, and ADMET properties to illuminate the identified best hits phytochemicals potential efficacy targeting both EGFR and ER receptors, demonstrating a multi-target therapeutic approach.

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