Computational Design of Enantiocomplementary Epoxide Hydrolases for Asymmetric Synthesis of Aliphatic and Aromatic Diols

Abstract

The use of enzymes in preparative biocatalysis often requires tailoring enzyme selectivity by protein engineering. Herein we explore the use of computational library design and molecular dynamics simulations to create variants of limonene epoxide hydrolase that produce enantiomeric diols from meso ‐epoxides. Three substrates of different sizes were targeted: cis ‐2,3‐butene oxide, cyclopentene oxide, and cis ‐stilbene oxide. Most of the 28 designs tested were active and showed the predicted enantioselectivity. Excellent enantioselectivities were obtained for the bulky substrate cis ‐stilbene oxide, and enantiocomplementary mutants produced ( S , S )‐ and ( R , R )‐stilbene diol with >97 % enantiomeric excess. An ( R , R )‐selective mutant was used to prepare ( R , R )‐stilbene diol with high enantiopurity (98 % conversion into diol, >99 % ee ). Some variants displayed higher catalytic rates ( k cat ) than the original enzyme, but in most cases K M values increased as well. The results demonstrate the feasibility of computational design and screening to engineer enantioselective epoxide hydrolase variants with very limited laboratory screening.

Computational Prediction of ω-Transaminase Specificity by a Combination of Docking and Molecular Dynamics Simulations

“…The use of NAC frequencies as indication of enzymatic selectivity has been adopted successfully in previous studies on a variety of enzymes. [36][37][38][39][40][41][42]46 For the substrate-range prediction, we found the Rosetta interface energy between the enzyme and the external aldimine form of the query compound to be in agreement with the experimental activities of the whole transamination reaction. Conversely, there was no apparent correlation between the percentage of NACs and the enzymatic activity (results not shown).…”

“…Still, the length of the simulations should be long enough to generate conformational sampling of the ground-state region set at the docking stage, but short enough to maintain a conformation close to the initial structure. Our research group has previously shown that ps-scale MD simulations are long enough to allow meaningful counting of binding poses and that running multiple-independent MD simulations is better for sampling than performing a single long simulation. ,,, Additionally, no large difference was found when comparing the ee % obtained from using the top10% or top20% of Rosetta structures for MD simulations (Table S1). Again, only low-energy conformations should be used to avoid working with unfavorable ground states (unfavorable Rosetta interface energies), but the structures should be diverse enough to prevent single outliers from dominating the averaged frequency of NAC conformations.…”

“…Comparing the free energy of NAC formation for the ( R )- and ( S )-enantiomer gives a direct estimate of the ee %. The use of NAC frequencies as indication of enzymatic selectivity has been adopted successfully in previous studies on a variety of enzymes. − , …”

“…Our research group has previously shown that ps-scale MD simulations are long enough to allow meaningful counting of binding poses and that running multipleindependent MD simulations is better for sampling than performing a single long simulation. 36,37,46,67 Additionally, no large difference was found when comparing the ee% obtained from using the top10% or top20% of Rosetta structures for MD simulations (Table S1). Again, only low-energy conformations should be used to avoid working with unfavorable ground states (unfavorable Rosetta interface energies), but the structures should be diverse enough to prevent single outliers from dominating the averaged frequency , where the H α is positioned close to the catalytic lysine, because of steric hindrance with the small binding pocket (S: small, L: large binding pockets).…”

Computation-Aided Engineering of Cytochrome P450 for the Production of Pravastatin

“…An important example is the work of Arnold et al, in which molecular dynamics simulations and Markov models were used to evaluate the effect of a single mutation in a flexible loop region of the nitrating cytochrome P450 TxtE. Recently, Rosetta design and molecular dynamics simulations ,− with scoring for near-attack conformations along the simulated trajectory ,,, were used to computationally design and rank enzyme variants. Near-attack conformations (NACs) are transient conformations of enzyme–substrate complexes that are close to the transition state.…”