Enantioselective Enzymes by Computational Design and In Silico Screening

Abstract

Computational enzyme design holds great promise for providing new biocatalysts for synthetic chemistry. A strategy to design small mutant libraries of complementary enantioselective epoxide hydrolase variants for the production of highly enantioenriched (S,S)-diols and (R,R)-diols is developed. Key features of this strategy (CASCO, catalytic selectivity by computational design) are the design of mutations that favor binding of the substrate in a predefined orientation, the introduction of steric hindrance to prevent unwanted substrate binding modes, and ranking of designs by high-throughput molecular dynamics simulations. Using this strategy we obtained highly stereoselective mutants of limonene epoxide hydrolase after experimental screening of only 37 variants. The results indicate that computational methods can replace a substantial amount of laboratory work when developing enantioselective enzymes.Recentsuccesses with de novo computational protein design (CPD) [1] and redesign of enzyme active sites [2] suggest that computational methods can be used for controlling enzyme selectivity, which is an important goal in industrial biocatalyst development. Enantioselectivity engineering is often pursued by directed evolution, in most cases with the use of large mutant libraries. [3] Although important successes have been reported, [3] further development could benefit from improved predictability of mutant properties and a higher abundance of beneficial substitutions in mutant libraries. We have recently explored the use of computational methods for the design of small mutant libraries harboring thermostable enzyme variants. [4] In the work reported herein, we demonstrate the use of computational library design for engineering enzyme stereoselectivity.The computational strategy that we explored is to place a substrate in the enzyme active site in an orientation required for the desired enantioselective conversion and to redesign the active site to stabilize that geometry. Protein sequences forming predefined substrate-binding sites or sites with shape complementarity to transition-state models can be generated by CPD methods such as implemented in RosettaDesign [5] after which laboratory screening is carried out to identify improved variants. [6] In the approach that we termed CASCO (Scheme 1), high-throughput molecular dynamics simulations that predict relative reactivity and thereby enantioselectivity replace most of the experimental screening. The strategy was tested with a challenging case of biocatalytic relevance: the design of a pair of enantiocomplementary epoxide hydrolases for the enantioselective transformation of cyclopentene oxide (1 a) to yield either (R,R)-or (S,S)-cyclopentane-1,2-diol (1 b) (Scheme 2). As the stereochemical outcome of this asymmetric conversion is controlled by regioselectivity of water attack, accurate placement of the substrate in the active site is essential. This is highly challenging because epoxide 1 a lacks bulky or polar groups that could position the substrate in a defin...

Origins of stereoselectivity in evolved ketoreductases

“…Enzyme design and engineering for enantioselective synthesis pose significant challenges for chemical biology that are receiving increasing attention (20). The highly enantioselective enzymes obtained through DE for the reduction of 3-oxacyclopentanone and 3-thiacyclopentanone are less active than the WT, however.…”

X-ray crystallographic validation of structure predictions used in computational design for protein stabilization

“…These results demonstrate that the strategy not to mutate residues close to the active site was successful for the design of fully active, thermostable LEH‐P variants. Similarly, stabilizing mutations in the dehalogenase LinB only reduced enzyme activity when they were introduced close to the active site . This strategy could be a simple but effective way to maintain catalytic activity during computational design, provided that more distant mutations do not reduce activity.…”

Extending enzyme molecular recognition with an expanded amino acid alphabet

“…Moreover, enzymes are efficient catalysts, function under mild conditions with relatively nontoxic reagents, and enable the production of relatively pure products, minimizing waste generation. In recent years, there has been much success in engineering enzymes for desired reactions (3-5) using methods such as rational protein engineering (6)(7)(8), directed evolution (9)(10)(11), and, most recently, computational enzyme design (12)(13)(14)(15).…”