Discovering potential WRN inhibitors from natural product database through computational methods

Abstract

Microsatellite instability (MSI) is a relatively common feature associated with multiple cancers, and Werner syndrome (WRN) ATP-dependent helicase has been recognized as a novel target for treating MSI cancers, such as colorectal cancer. A small-molecule inhibitor targeting WRN would be a promising strategy for treating colorectal cancer with high MSI expression. In this study, we employed a computer-assisted drug discovery strategy to screen over 30,000 natural product molecules. By using a combination of docking, ligand efficiency, Molecular Mechanics/Generalized Born Surface Area (MM/GBSA), and thermodynamic integration (TI) calculations, we identified MOL008980, MOL010740, MOL011832, T4743, TN1166, and TNP-002173 as potential WRN inhibitors. Subsequent molecular dynamics simulation revealed that these screened natural products possessed better binding dynamic characteristics than ATP substrate and were capable of inhibiting the dynamic process of WRN, making them potential strong ATP competitive inhibitors. In conclusion, our computational approach revealed potential WRN inhibitors from a natural product database, providing a theoretical basis for future research.