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.

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The haloalkane dehalogenase enzyme DmmA was identified by marine metagenomic screening. Determination of its crystal structure revealed an unusually large active site compared to those of previously characterized haloalkane dehalogenases. Here we present a biochemical characterization of this interesting enzyme with emphasis on its structure-function relationships. DmmA exhibited an exceptionally broad substrate specificity and degraded several halogenated environmental pollutants that are resistant to other members of this enzyme family. In addition to having this unique substrate specificity, the enzyme was highly tolerant to organic cosolvents such as dimethyl sulfoxide, methanol, and acetone. Its broad substrate specificity, high overexpression yield (200 mg of protein per liter of cultivation medium; 50% of total protein), good tolerance to organic cosolvents, and a broad pH range make DmmA an attractive biocatalyst for various biotechnological applications. We present a thorough biochemical characterization of the haloalkane dehalogenase DmmA from a marine metagenome. This enzyme with an unusually large active site shows remarkably broad substrate specificity, high overexpression, significant tolerance to organic cosolvents, and activity under a broad range of pH conditions. DmmA is an attractive catalyst for sustainable biotechnology applications, e.g., biocatalysis, biosensing, and biodegradation of halogenated pollutants. We also report its ability to convert multiple halogenated compounds to corresponding polyalcohols.

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The functionality of an enzyme depends on its unique three-dimensional structure, which is a result of the folding process when the nascent polypeptide follows a funnel-like energy landscape to reach a global energy minimum. Computer-encoded algorithms are increasingly employed to stabilize native proteins for use in research and biotechnology applications. Here, we reveal a unique example where the computational stabilization of a monomeric α/β-hydrolase enzyme (T m = 73.5 °C; ΔT m > 23 °C) affected the protein folding energy landscape. The introduction of eleven single-point stabilizing mutations based on force field calculations and evolutionary analysis yielded soluble domain-swapped intermediates trapped in local energy minima. Crystallographic structures revealed that these stabilizing mutations might (i) activate cryptic hinge-loop regions and (ii) establish secondary interfaces, where they make extensive noncovalent interactions between the intertwined protomers. The existence of domain-swapped dimers in a solution is further confirmed experimentally by data obtained from small-angle X-ray scattering (SAXS) and cross-linking mass spectrometry. Unfolding experiments showed that the domain-swapped dimers can be irreversibly converted into native-like monomers, suggesting that the domain swapping occurs exclusively in vivo. Crucially, the swapped-dimers exhibited advantageous catalytic properties such as an increased catalytic rate and elimination of substrate inhibition. These findings provide additional enzyme engineering avenues for next-generation biocatalysts.