Transport of ligands between buried active sites and bulk solvent is a key step in the catalytic cycle of many enzymes. The absence of evolutionary optimized transport tunnels is an important barrier limiting the efficiency of biocatalysts prepared by computational design. Creating a structurally defined and functional "hole" into the protein represents an engineering challenge. Here we describe the computational design and directed evolution of a de novo transport tunnel in haloalkane dehalogenase. Mutants with a blocked native tunnel and newly opened auxiliary tunnel in a distinct part of the structure showed dramatically modified properties. The mutants with blocked tunnels acquired specificity never observed with native family members: up to 32 times increased substrate inhibition and 17 times reduced catalytic rates. Opening of the auxiliary tunnel resulted in specificity and substrate inhibition similar to those of the native enzyme and the most proficient haloalkane dehalogenase reported to date (k cat = 57 s −1 with 1,2-dibromoethane at 37 °C and pH 8.6). Crystallographic analysis and molecular dynamics simulations confirmed the successful introduction of a structurally defined and functional transport tunnel. Our study demonstrates that, whereas we can open the transport tunnels with reasonable proficiency, we cannot accurately predict the effects of such change on the catalytic properties. We propose that one way to increase efficiency of an enzyme is the direct its substrates and products into spatially distinct tunnels. The results clearly show the benefits of enzymes with de novo transport tunnels, and we anticipate that this engineering strategy will facilitate the creation of a wide range of useful biocatalysts.

Millions of protein sequences are being discovered at an incredible pace, representing an inexhaustible source of biocatalysts. Here, we describe an integrated system for automated in silico screening and systematic characterization of diverse family members. The workflow consists of (i) identification and computational characterization of relevant genes by sequence/structural bioinformatics, (ii) expression analysis and activity screening of selected proteins, and (iii) complete biochemical/biophysical characterization and was validated against the haloalkane dehalogenase family. The sequence-based search identified 658 potential dehalogenases. The subsequent structural bioinformatics prioritized and selected 20 candidates for exploration of protein functional diversity. Out of these 20, the expression analysis and the robotic screening of enzymatic activity provided 8 soluble proteins with dehalogenase activity. The enzymes discovered originated from genetically unrelated Bacteria, Eukaryota, and also Archaea. Overall, the integrated system provided biocatalysts with broad catalytic diversity showing unique substrate specificity profiles, covering a wide range of optimal operational temperature from 20 to 70 °C and an unusually broad pH range from 5.7 to 10. We obtained the most catalytically proficient native haloalkane dehalogenase enzyme to date (k cat /K 0.5 = 96.8 mM −1 s −1 ), the most thermostable enzyme with melting temperature 71 °C, three different cold-adapted enzymes showing dehalogenase activity at near-to-zero temperatures, and a biocatalyst degrading the warfare chemical sulfur mustard. The established strategy can be adapted to other enzyme families for exploration of their biocatalytic diversity in a large sequence space continuously growing due to the use of next-generation sequencing technologies.

Ancestral sequence reconstruction (ASR) represents a powerful approach for empirical testing structure-function relationships of diverse proteins. We employed ASR to predict sequences of five ancestral haloalkane dehalogenases (HLDs) from the HLD-II subfamily. Genes encoding the inferred ancestral sequences were synthesized and expressed in Escherichia coli, and the resurrected ancestral enzymes (AncHLD1-5) were experimentally characterized. Strikingly, the ancestral HLDs exhibited significantly enhanced thermodynamic stability compared to extant enzymes (ΔT up to 24 °C), as well as higher specific activities with preference for short multi-substituted halogenated substrates. Moreover, multivariate statistical analysis revealed a shift in the substrate specificity profiles of AncHLD1 and AncHLD2. This is extremely difficult to achieve by rational protein engineering. The study highlights that ASR is an efficient approach for the development of novel biocatalysts and robust templates for directed evolution.