Abstract
The Gly2032Arg (G2032R) point mutation in proto-oncogene tyrosine-protein kinase 1 (ROS1) is one of the predominant factors of drug resistance to targeted therapies in patients with ROS1 fusion-positive non-small-cell lung cancer (NSCLC). This study aimed to identify novel inhibitors from a library of alkaloids (447 compounds) using computational approaches. Molecular docking-based virtual screening was performed to identify promising compounds, followed by ADMET property prediction and molecular dynamics simulations to assess their safety and stability. The top compounds identified were yibeinoside A and vomicine, which exhibited high binding affinities to the G2032R-mutant ROS1 protein. ADMET analysis indicated that yibeinoside A possessed better predicted pharmacokinetic profiles than vomicine and the positive control, lorlatinib. Molecular dynamics simulations demonstrated that yibeinoside A formed a highly stable complex with stable root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), and solvent accessible surface area (SASA) values. Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) calculations further confirmed that yibeinoside A and vomicine had better binding free energies than lorlatinib. Collectively, these findings suggest that yibeinoside A, with its balanced binding interactions and favorable predicted pharmacokinetic profile, is a promising lead candidate for further development as a selective inhibitor against G2032R-mutant ROS1.