Wet-lab validation does more than confirm CAS predictions---it reveals the limitations and surprises of the model. Discrepancies between prediction and function often point to:
Unmodeled solvent effects or post-translational modifications
Allosteric interactions missed by topological approximations
Unexpected co-factor dependencies or protein-protein interactions
Such emergent insights not only enrich the simulation framework but also extend scientific understanding of enzyme evolution itself, particularly when synthetic pathways outperform natural analogs or demonstrate novel substrate specificity.
5. Toward a Unified Platform for Synthetic Evolution
The integration of CAS-based design with wet-lab infrastructure leads toward a unified AI-driven synthetic evolution platform, with modules for:
Evolutionary simulation (graph-based, thermodynamically bounded)
AI-guided mutation driver (e.g., RL agents)
Experimental synthesis and high-throughput validation
Data feedback, retraining, and model refinement
