An Integrated Virtual Screening Platform to Identify Potent Co-Assembled Nanodrugs for Cancer Treatment

Abstract

Co-assembled nanodrugs provide significant advantages in cancer treatment and drug delivery, yet effective screening methods to identify molecular combinations for co-assembly are lacking. This study presents a screening strategy integrating ligand-based virtual screening (LBVS) and density functional theory (DFT) calculations to explore new molecular combinations with co-assembly capabilities. The accuracy of this screening was validated by synthesizing various co-assembled nanodrugs under mild conditions. Vinpocetine (Vin) and lenvatinib (Len) are representative co-assembly combinations that can directly co-assemble into nanoparticles (NPs) through hydrogen bonding, van der Waals forces, and π-π interactions. These NPs were further functionalized with polyethylene glycol (PEG), resulting in PEG-L/V NPs that exhibited enhanced stability and biocompatibility. In addition, PEG-L/V NPs can respond to acidic conditions and release Vin and Len, working synergistically to induce cell cycle arrest and apoptosis in tumor cells in vitro while also inhibiting xenograft tumor growth in vivo. RNA sequencing (RNA-seq) analysis revealed that the co-assembled nanodrugs exhibited mechanisms that are distinct from those of single drugs. This study demonstrates the feasibility of utilizing a computational approach combining LBVS and DFT to identify small molecules with co-assembly capabilities, leading to innovative anticancer strategies.