A Haloalkane Dehalogenase from Saccharomonospora viridis Strain DSM 43017, a Compost Bacterium with Unusual Catalytic Residues, Unique (S)-Enantiopreference, and High Thermostability.

Haloalkane dehalogenases can cleave a carbon-halogen bond in a broad range of halogenated aliphatic compounds. However, a highly conserved catalytic pentad composed of a nucleophile, a catalytic base, a catalytic acid, and two halide-stabilizing residues is required for their catalytic activity. Only a few family members, e.g., DsaA, DmxA, or DmrB, remain catalytically active while employing a single halide-stabilizing residue. Here, we describe a novel haloalkane dehalogenase, DsvA, from a mildly thermophilic bacterium, Saccharomonospora viridis strain DSM 43017, possessing one canonical halide-stabilizing tryptophan (W125). At the position of the second halide-stabilizing residue, DsvA contains the phenylalanine F165, which cannot stabilize the halogen anion released during the enzymatic reaction by a hydrogen bond. Based on the sequence and structural alignments, we identified a putative second halide-stabilizing tryptophan (W162) located on the same α-helix as F165, but on the opposite side of the active site. The potential involvement of this residue in DsvA catalysis was investigated by the construction and biochemical characterization of the three variants, DsvA01 (F165W), DsvA02 (W162F), and DsvA03 (W162F and F165W). Interestingly, DsvA exhibits a preference for the (S)- over the (R)-enantiomers of ß-bromoalkanes, which has not been reported before for any characterized haloalkane dehalogenase. Moreover, DsvA shows remarkable operational stability at elevated temperatures. The present study illustrates that protein sequences possessing an unconventional composition of catalytic residues represent a valuable source of novel biocatalysts.IMPORTANCE The present study describes a novel haloalkane dehalogenase, DsvA, originating from a mildly thermophilic bacterium, Saccharomonospora viridis strain DSM 43017. We report its high thermostability, remarkable operational stability at high temperatures, and an (S)-enantiopreference, which makes this enzyme an attractive biocatalyst for practical applications. Sequence analysis revealed that DsvA possesses an unusual composition of halide-stabilizing tryptophan residues in its active site. We constructed and biochemically characterized two single point mutants and one double point mutant and identified the noncanonical halide-stabilizing residue. Our study underlines the importance of searching for noncanonical catalytic residues in protein sequences.

Computer-assisted engineering of hyperstable fibroblast growth factor 2.

Fibroblast growth factors (FGFs) serve numerous regulatory functions in complex organisms, and their corresponding therapeutic potential is of growing interest to academics and industrial researchers alike. However, applications of these proteins are limited due to their low stability. Here we tackle this problem using a generalizable computer-assisted protein engineering strategy to create a unique modified FGF2 with nine mutations displaying unprecedented stability and uncompromised biological function. The data from the characterization of stabilized FGF2 showed a remarkable prediction potential of in silico methods and provided insight into the unfolding mechanism of the protein. The molecule holds a considerable promise for stem cell research and medical or pharmaceutical applications.

HotSpot Wizard 2.0: automated design of site-specific mutations and smart libraries in protein engineering.

HotSpot Wizard 2.0 is a web server for automated identification of hot spots and design of smart libraries for engineering proteins' stability, catalytic activity, substrate specificity and enantioselectivity. The server integrates sequence, structural and evolutionary information obtained from 3 databases and 20 computational tools. Users are guided through the processes of selecting hot spots using four different protein engineering strategies and optimizing the resulting library's size by narrowing down a set of substitutions at individual randomized positions. The only required input is a query protein structure. The results of the calculations are mapped onto the protein's structure and visualized with a JSmol applet. HotSpot Wizard lists annotated residues suitable for mutagenesis and can automatically design appropriate codons for each implemented strategy. Overall, HotSpot Wizard provides comprehensive annotations of protein structures and assists protein engineers with the rational design of site-specific mutations and focused libraries. It is freely available at http://loschmidt.chemi.muni.cz/hotspotwizard.

Ancestral Haloalkane Dehalogenases Show Robustness and Unique Substrate Specificity.

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 (ΔTm 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.

FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.

There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.

CAVER Analyst 1.0: graphic tool for interactive visualization and analysis of tunnels and channels in protein structures.

UNLABELLED: The transport of ligands, ions or solvent molecules into proteins with buried binding sites or through the membrane is enabled by protein tunnels and channels. CAVER Analyst is a software tool for calculation, analysis and real-time visualization of access tunnels and channels in static and dynamic protein structures. It provides an intuitive graphic user interface for setting up the calculation and interactive exploration of identified tunnels/channels and their characteristics. AVAILABILITY AND IMPLEMENTATION: CAVER Analyst is a multi-platform software written in JAVA. Binaries and documentation are freely available for non-commercial use at http://www.caver.cz.

CAVER: Algorithms for Analyzing Dynamics of Tunnels in Macromolecules.

The biological function of a macromolecule often requires that a small molecule or ion is transported through its structure. The transport pathway often leads through void spaces in the structure. The properties of transport pathways change significantly in time; therefore, the analysis of a trajectory from molecular dynamics rather than of a single static structure is needed for understanding the function of pathways. The identification and analysis of transport pathways are challenging because of the high complexity and diversity of macromolecular shapes, the thermal motion of their atoms, and the large amount of conformations needed to properly describe conformational space of protein structure. In this paper, we describe the principles of the CAVER 3.0 algorithms for the identification and analysis of properties of transport pathways both in static and dynamic structures. Moreover, we introduce the improved clustering solution for finding tunnels in macromolecules, which is included in the latest CAVER 3.02 version. Voronoi diagrams are used to identify potential pathways in each snapshot of a molecular dynamics trajectory and clustering is then used to find the correspondence between tunnels from different snapshots. Furthermore, the geometrical properties of pathways and their evolution in time are computed and visualized.

Computational tools for designing smart libraries.

Traditional directed evolution experiments are often time-, labor- and cost-intensive because they involve repeated rounds of random mutagenesis and the selection or screening of large mutant libraries. The efficiency of directed evolution experiments can be significantly improved by targeting mutagenesis to a limited number of hot-spot positions and/or selecting a limited set of substitutions. The design of such "smart" libraries can be greatly facilitated by in silico analyses and predictions. Here we provide an overview of computational tools applicable for (a) the identification of hot-spots for engineering enzyme properties, and (b) the evaluation of predicted hot-spots and selection of suitable amino acids for substitutions. The selected tools do not require any specific expertise and can easily be implemented by the wider scientific community.

DspA from Strongylocentrotus purpuratus: The first biochemically characterized haloalkane dehalogenase of non-microbial origin.

Haloalkane dehalogenases are known as bacterial enzymes cleaving a carbon-halogen bond in halogenated compounds. Here we report the first biochemically characterized non-microbial haloalkane dehalogenase DspA from Strongylocentrotus purpuratus. The enzyme shows a preference for terminally brominated hydrocarbons and enantioselectivity towards ß-brominated alkanes. Moreover, we identified other putative haloalkane dehalogenases of eukaryotic origin, representing targets for future experiments to discover dehalogenases with novel catalytic properties.