Employing steered MD simulations for effective virtual screening: Active pharmacophore search by dynamic corrections to target MKK3-MYC interactions

Abstract

The protein-protein interaction (PPI) between mitogen-activated protein kinase kinase 3 (MKK3), and MYC is a crucial regulator of oncogenic signaling, particularly in triple-negative breast cancer (TNBC). Despite its clinical significance, effective small molecule inhibitors targeting this interaction remain elusive. In this study, we employed a comprehensive in silico approach integrating dynamic structure-based pharmacophore modeling, virtual screening, molecular docking, and molecular dynamics (MD) simulations to identify potential inhibitors disrupting the MKK3-MYC interaction. The pharmacophore-based screening of over 2 million compounds from ChemDiv and Enamine libraries led to the identification of 16,766 hits, which were further refined through docking and MD-based analyses. The top-ranked molecules underwent steered molecular dynamics (sMD) simulations to evaluate the mechanical stability of their binding interactions, followed by binding free energy calculations (MM/GBSA) to assess their affinity. Notably, several hit compounds exhibited stronger binding affinities and mechanical stability compared to the reference inhibitor SGI-1027, with Z332428622, 4476-2273, and 4292-0516 emerging as the most promising candidates. The lead compounds demonstrated stable interactions with key residues at the interface of MKK3 and MYC, suggesting their potential as novel modulators of MYC-driven malignancies. These findings provide a strong computational foundation for further experimental validation and offer promising candidates for targeted therapy development in MYC-dependent cancers.

Keywords: Fragment-based drug design; MKK3; MYC; Molecular Dynamics (MD) simulations; Protein-protein interaction; Steered MD simulations; Triple-negative breast cancer (TNBC).