Open access
Sep 2026
DFRL-Mol: a dual-stage framework of reinforcement learning for multi-scenario molecule optimization
Abstract As a critical step in drug discovery, molecule optimization aims to improve specific properties of lead compounds. Inspired by isosteres (i.e. molecular substructures with similar reactive electron shells), existing AI-based methods have been proposed for molecule optimization. However, they often rely on avai...
Zhen-Yi Wu, Peng-Cheng Zhao, Jia-Ning Li et al.
· Briefings in Bioinformatics · 0 citations