Identification of potential methyltransferase NSD2 enzymatic inhibitors through a multi-step structure-based drug design.

Abstract

Reversing aberrant protein methylation levels is widely recognized as a key focus in cancer therapy. As an essential lysine methylation regulator, NSD2 (Nuclear receptor-binding SET Domain 2, also known as WHSC1/MMSET) regulates chromatin structural sparsity and DNA repair processes. Abnormal enhancement of NSD2 methylation activity (caused by NSD2 overexpression and point mutations) has been closely related to the initiation and development of various cancers and diseases. However, the lack of selective inhibitors hinders further therapeutic intervention and limits the exploration of its biological mechanism. Therefore, this study developed an integrated approach that includes binding feature pharmacophore modeling, gradient database screening of 120 million compounds, flexible docking, and molecular dynamic simulation. This approach was used to identify hit compounds targeting the substrate/coenzyme binding site of NSD2. Subsequently, 20 lead compounds were retrieved by using molecular docking analysis and ADMET prediction. Finally, MD simulations were performed to validate the binding stability of selected drug candidates. The findings indicated that these newly obtained compounds might be potent NSD2 inhibitors. We hope the integrated virtual screening approach will provide a valuable idea for discovering novel H3K36 methyltransferase inhibitors.