Computational Enzyme Engineering: A Novel CSFp Strategy for Enhanced D-Lac Activity

D-Lac holds significant potential for the optical resolution of racemic pantolatone (DL-PL), yielding D-pantothenic acid, a vital component of the vitamin B5 family (Scheme S1). Vitamin B5 and its derivatives find widespread use in the food, pharmaceutical, animal feed, cosmetics, and other industries,52 and play a crucial role in the synthesis of the neurotransmitter acetylcholine by acetyl-CoA, a topic of intense interest in neurodegenerative disease research.53 Initial attempts to evolve D-Lac employed error-prone (PCR) and DNA shuffling54 techniques, lacking rational design due to the absence of D-Lac's crystal structure. The catalytic mechanism of D-Lac remains poorly understood, hindering the design of enzymes based on quantum mechanics-derived transition states. The substrate (D-pantolactone, D-PL) lacks large or polar groups, and a single amino acid substitution in the active pocket results in limited complementarity between the active site and the overall shape of the ligand.

The innovative computational design pipeline has led to the identification of combinatorial strategies for ultra-low throughput screening. The proposed CSFp strategy provides a viable generic solution to minimize experimental effort while maximizing the exploration of supernumerary effects, encompassing additivity and/or synergy between mutant sets. This approach ultimately resulted in a promising mutant (N96S/A271E/F274Y/F308G), exhibiting a 56-fold increase in activity towards D-PL compared to wild-type (WT) D-Lac. This experimental example underscores the potential of the CSFp strategy to facilitate optimized computational enzyme engineering, effectively rescuing enzymes lacking crystal structure information and those with relatively obscure catalytic mechanisms. This strategy paves the way for its application in scenarios demanding enhanced enzyme activity. By complementing a multitude of established enzyme engineering methods, this approach provides innovative ideas for computational enzyme modification.