A flexible data-free framework for structure-based de novo drug design with reinforcement learning

3D-MCTS employs retrosynthetic fragments to assemble molecules within the binding pocket, ensuring superior binding affinities, favorable drug-like properties, synthetic accessibility, and appropriate conformations.