D-Lac can be utilized for the optical resolution of racemic pantolatone (DL-PL) to yield D-pantothenic acid, a member of the vitamin B5 family (Scheme S1). Vitamin B5 and its derivatives are widely employed in the food, pharmaceutical, animal feed, cosmetic, and other industries,52 as they enable acetyl-CoA to synthesize the neurotransmitter acetylcholine, which has garnered considerable attention in the field of neurodegenerative diseases.53

In the evolution of D-Lac, researchers initially attempted error-prone PCR and DNA shuffling54, which lacked rational design due to the absence of crystal structure information. The catalytic mechanism of D-Lac remains poorly understood, and enzymes cannot be designed based on transition states obtained through quantum mechanics. The substrate (D-pantolactone, D-PL) lacks large or polar groups, and a single amino acid change in the active pocket results in low complementarity between the active site and the overall shape of the ligand.

This study introduces a novel computational design pipeline that has led to the discovery of combinatorial strategies for ultra-low throughput screening. The proposed CSFp strategy offers a viable generic solution to minimize experimental effort while maximizing the exploration of supernumerary effects in terms of additivity and/or synergy between mutant sets. This approach ultimately yielded an encouraging mutant (N96S/A271E/F274Y/F308G) with a 56-fold increase in activity towards D-PL compared to wild-type (WT) D-Lac.

With this experimental example, we anticipate that the CSFp strategy will facilitate optimized computational enzyme engineering, rescuing various enzymes that lack crystal structure information and have relatively obscure catalytic mechanisms, and enabling their application in situations where improved enzyme activity is required. Complementing many excellent enzyme engineering methods, this approach will provide inspiration for computational enzyme modification.

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

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