Abstract
Cancer is the most prevalent disease globally, which presents a significant challenge to the healthcare industry, with breast and lung cancer being predominant malignancies. This study used RNA-seq data from the TCGA database to identify potential biomarkers for lung and breast cancer. Tumor Necrosis Factor (TNFAIP8) and Sulfite Oxidase (SUOX) showed significant expression variation and were selected for further study using structure-based drug discovery (SBDD). Compounds derived from the Euphorbia ammak plant were selected for in-silico study with both TNFAIP8 and SUOX. Stigmasterol had the greatest binding scores (normalized scores of −8.53 kcal/mol and −9.69 kcal/mol) with both proteins, indicating strong stability in their binding pockets throughout the molecular dynamics’ simulation. Although Stigmasterol first changed its initial conformation (RMSD = 0.5 nm with the starting conformation) in SUOX, it eventually reached a stable conformation (RMSD of 1.5 nm). The compound on TNFAIP8 showed a persistent shape (RMSD of 0.35 nm), indicating strong protein stability. The binding free energy of the complex was calculated using the MM/GBSA technique; TNFAIP8 had a ΔGTOTAL of −24.98 kcal/mol, with TYR160 being the most significant residue, contributing −2.52 kcal/mol. On the other hand, the SUOX complex had a binding free energy of −16.87 kcal/mol, with LEU151 being the primary contributor (-1.17 kcal/mol). Analysis of the complexes' free energy landscape unveiled several states with minimum free energy, indicating robust interactions between the protein and ligand. In its conclusion, this work emphasises the favourable ability of Stigmasterol to bind with prospective targets for lung and breast cancer, indicating the need for more experimental study.
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