Integrated systems biology and structural approaches to discover novel biomarkers and small molecule inhibitors using the gene expression data from drug-resistant breast cancer cell lines

Abstract

Breast cancer, the leading cause of cancer-related deaths in women, is driven by multidrug resistance, highlighting the urgent need for novel therapeutic targets. Consequently, we employed network-based gene expression profiling to analyse datasets from normal and tamoxifen-resistant MCF7 cell lines. The analysis identified 372 DEGs, including 133 upregulated and 239 downregulated genes, with ISG15 emerging as the top hub gene. Survival analyses indicated that high ISG15 expression correlates with poorer overall survival in breast cancer. To identify potent inhibitors of ISG15, we screened an anticancer drug database and selected three top hits with docking scores of −6.6, −6.5 and −5.4 kcal/mol. Molecular dynamics simulations confirmed the dynamic stability and strong binding affinity of these top hits. The top hit (1-3) complexes showed favourable binding-free energies of −31.57, −23.92 and −28.05 kcal/mol, respectively, with desirable pharmacokinetic properties. This study highlights promising drug candidates targeting ISG15 in tamoxifen-resistant breast cancer, warranting further experimental validation.