Enhanced D-Lac Activity for Efficient Production of D-Pantothenic Acid: A Novel Computational Strategy

D-Lac holds immense potential for the optical resolution of racemic pantolatone (DL-PL), yielding D-pantothenic acid, an integral component of the vitamin B5 family (Scheme S1). Vitamin B5 and its derivatives find extensive applications in various industries, including food, pharmaceuticals, animal feed, cosmetics, and others.52 Notably, it facilitates the synthesis of the neurotransmitter acetylcholine via acetyl-CoA, a process that has attracted considerable attention in the context of neurodegenerative diseases.53

Early attempts to evolve D-Lac relied on error-prone PCR and DNA shuffling,54 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 mechanically derived transition states. The substrate (D-pantolactone, D-PL) lacks substantial or polar groups, and a single amino acid alteration within the active pocket leads to limited complementarity between the active site and the overall ligand shape.

This study introduces a novel computational design pipeline that has unlocked combinatorial strategies for ultra-low throughput screening. The proposed CSFp strategy provides a practical and generic solution for minimizing experimental effort while maximizing the exploration of supernumerary effects related to additivity and/or synergy among mutant sets. This approach ultimately yielded 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 demonstration suggests that the CSFp strategy can facilitate optimized computational enzyme engineering. It holds the potential to rescue enzymes lacking crystal structure information or with relatively obscure catalytic mechanisms, enabling their application in situations demanding enhanced enzyme activity. As a complement to existing enzyme engineering methods, this strategy offers valuable insights for computational enzyme modification.