Additionally, by combining the data from Figures and, we observe that TRPV4 inhibitor molecules are directly related to various distinct molecular fragments. The red region in Figure shows an overlap ratio of about 25%, indicating limitations in TRPV4-Gemma-3B's ability to capture the quantity of essential structural fragment features. We can infer that this limitation is also the reason why the binding affinity data for the generated molecules, as shown in Figure , is lower than that of the sample data. Specifically, this is because TRPV4-Gemma-3B misses molecular fragments that significantly contribute to binding affinity when designing inhibitor molecules. In the context of current advanced technologies, this can be improved through reinforcement learning involving human expertise and multi-agent algorithms to enhance the performance of TRPV4-Gemma-3B. ; the light blue section corresponds to fragments in (b), also belonging to the blue area substructure fragments in Figure ; the green section corresponds to fragments in (f), belonging to the green area substructure fragments in Figure . (g) Similar substructure fragments to those in (f), which belong to the blue area substructure fragments in Figure , are shown.