Fig. 1: Overview of clickgen and case study based on protein pocket generation.

a The complete ClickGen model after incorporating reinforcement learning (RL), where the prior model encompasses both the reaction-based combinator and the inpainting generative model; b Overview of the selection, expansion, simulation, and backpropagation processes in Monte Carlo Tree Search (MCTS), where the yellow- brown-yellow connecting lines represent the Copper-Catalyzed Azide-Alkyne Cycloaddition (CuAAC) reaction and the black brown-yellow connecting lines represent the amidation reaction; c A complete example of ClickGen generating molecules within the SARS-Cov2 Mpro pocket, and the generation process of this compound is guided by MCTS, which selects the highest-scoring reaction pathway through the stages of expansion, simulation, and backpropagation. comprising a total of four synthons, with the reinforcement learning algorithm guiding the steps of the chemical-reaction combinator and inpainting generator during the generation process based on the pocket’s properties.