Integrative network and computational simulation of clinical and genomic data for the identification of mutated EGFR in breast cancer patients for therapeutic targeting using purine analogues

Abstract

EGFR/HER-1, a major oncogene, is frequently activated in breast cancers due to rear mutational events, which reduces the patient's survival rate, hence is a significant target for therapeutics. A total of 5699 clinical samples data was analysed at the genomic and proteomic level, revealing 4% genetic alterations in EGFR, with the highest number of missense mutations at D916N in exon 20. The Kaplan–Meier plots indicated that the unaltered group's overall survival rate was higher than the altered group. Molecular network analysis shows 10 probable partners associated with EGFR involved in breast cancer. For identifying the specific drugs to target unaltered/altered EGFR, high throughput virtual screenings (HTVS) of purines analogues using Molecular docking and dynamic (MD) simulation were performed. Docking studies shortlist the top three lead compounds (of 619 screened) based on minimum free energy for each (ΔG = −7.6 to −8.0 kcal/mol.) target. Residues Thr854 and Asp855 of both unaltered/altered EGFR form strong interactions with the top three compounds. MD simulations showed only one compound-PubChem-id-113801230, which had good interaction with both altered and unaltered EGFR with drug-likeliness as assessed by ADME properties. Therefore, compound-113801230 can effectively and selectively target unaltered/altered EGFR as an effective breast cancer therapeutic drug.