One of the major barriers to the use of enzymes in industrial biotechnology is their insufficient stability under processing conditions. The use of organic solvent systems instead of aqueous media for enzymatic reactions offers numerous advantages, such as increased solubility of hydrophobic substrates or suppression of water-dependent side reactions. For example, reverse hydrolysis reactions that form esters from acids and alcohols become thermodynamically favorable. However, organic solvents often inactivate enzymes. Industry and academia have devoted considerable effort into developing effective strategies to enhance the lifetime of enzymes in the presence of organic solvents. The strategies can be grouped into three main categories: (i) isolation of novel enzymes functioning under extreme conditions, (ii) modification of enzyme structures to increase their resistance toward nonconventional media, and (iii) modification of the solvent environment to decrease its denaturing effect on enzymes. Here we discuss successful examples representing each of these categories and summarize their advantages and disadvantages. Finally, we highlight some potential future research directions in the field, such as investigation of novel nanomaterials for immobilization, wider application of computational tools for semirational prediction of stabilizing mutations, knowledge-driven modification of key structural elements learned from successfully engineered proteins, and replacement of volatile organic solvents by ionic liquids and deep eutectic solvents.

Engineering enzymes to degrade anthropogenic compounds efficiently is challenging. We obtained Rhodococcus rhodochrous haloalkane dehalogenase mutants with up to 32-fold higher activity than wild type toward the toxic, recalcitrant anthropogenic compound 1,2,3-trichloropropane (TCP) using a new strategy. We identified key residues in access tunnels connecting the buried active site with bulk solvent by rational design and randomized them by directed evolution. The most active mutant has large aromatic residues at two out of three randomized positions and two positions modified by site-directed mutagenesis. These changes apparently enhance activity with TCP by decreasing accessibility of the active site for water molecules, thereby promoting activated complex formation. Kinetic analyses confirmed that the mutations improved carbon-halogen bond cleavage and shifted the rate-limiting step to the release of products. Engineering access tunnels by combining computer-assisted protein design with directed evolution may be a valuable strategy for refining catalytic properties of enzymes with buried active sites.

Enzyme engineering plays a central role in developing efficient biocatalysts for biotechnology, biomedicine, and life sciences. Apart from classical rational design and directed evolution approaches, machine learning methods have been increasingly applied to find patterns in data that help predict protein structures, improve enzyme stability, solubility, and function, predict substrate specificity, and guide rational protein design. In this Perspective, we analyze the state of the art in databases and methods used for training and validating predictors in enzyme engineering. We discuss current limitations and challenges which the community is facing and recent advancements in experimental and theoretical methods that have the potential to address those challenges. We also present our view on possible future directions for developing the applications to the design of efficient biocatalysts.