Combination of computational prescreening and experimental library construction can accelerate enzyme optimization by directed evolution.

Chiral compounds can be produced efficiently by using biocatalysts. However, wild-type enzymes often do not meet the requirements of a production process, making optimization by rational design or directed evolution necessary. Here, we studied the lipase-catalyzed hydrolysis of the model substrate 1-(2-naphthyl)ethyl acetate both theoretically and experimentally. We found that a computational equivalent of alanine scanning mutagenesis based on QM/MM methodology can be applied to identify amino acid positions important for the activity of the enzyme. The theoretical results are consistent with concomitant experimental work using complete saturation mutagenesis and high-throughput screening of the target biocatalyst, a lipase from Bacillus subtilis. Both QM/MM-based calculations and molecular biology experiments identify histidine 76 as a residue that strongly affects the catalytic activity. The experiments demonstrate its important influence on enantioselectivity.