Inter-domain flexibility and AI-guided sequence optimization enhance de novo enzyme function

Incorporating metal cofactors into computationally designed protein scaffolds is a powerful strategy to catalyze new-to-nature reactions. However, a major challenge in de novo enzyme design is the optimization of conformational equilibria and protein dynamics crucial for catalysis. Here we show that a modular scaffold architecture with flexible inter-domain linkers enables opening/closing motions in otherwise rigid de novo proteins. Furthermore, we modified the scaffold’s metal-binding specificity and conformational behavior by rational point mutations. Structural and biophysical analyses revealed that a lanthanide-specific variant was initially trapped in an inactive conformational state, which impaired efficient metal coordination and cerium-dependent photocatalytic activity. Stabilization of the active conformation by AI-guided sequence optimization led to accelerated lanthanide binding and a 10-fold increase in k _cat / K _m for a photoenzymatic model reaction. Our results underscore the importance of inter-domain flexibility and AI-guided sequence redesign in de novo enzyme engineering. *Paula Wagner Egea & Florent Delhommel contributed equally.