Mechanism-Based Discovery of Novel Substrates of Haloalkane Dehalogenases Using in Silico Screening

Azobenzene-Based Photoswitchable Substrates for Advanced Mechanistic Studies of Model Haloalkane Dehalogenase Enzyme Family

The engineering of efficient enzymes for large-scale production of industrially relevant compounds is a challenging task. Utilizing rational protein design, which relies on a comprehensive understanding of mechanistic information, holds significant promise for achieving success in this endeavor. Pre-steady-state kinetic measurements, obtained either through fast-mixing techniques or photoswitchable substrates, provide crucial mechanistic insights. The latter approach not only furnishes mechanistic clarity but also affords real-time structural elucidation of reaction intermediates via time-resolved femtosecond crystallography. Unfortunately, only a limited number of such valuable mechanistic probes are available. To address this gap, we applied a multidisciplinary approach, including computational analysis, chemical synthesis, physicochemical property screening, and enzyme kinetics to identify promising candidates for photoswitchable probes. We demonstrate the approach by designing an azobenzene-based photoswitchable substrate tailored for haloalkane dehalogenases, a prototypic class of enzymes pivotal in developing computational tools for rational protein design. The probe was subjected to steady-state and pre-steady-state kinetic analysis, which revealed new insights about the catalytic behavior of the model biocatalysts. We employed laser-triggered Z-to-E azobenzene photoswitching to generate the productive isomer in situ, opening avenues for advanced mechanistic studies using time-resolved femtosecond crystallography. Our results not only pave the way for the mechanistic understanding of this model enzyme family, incorporating both kinetic and structural dimensions, but also propose a systematic approach to the rational design of photoswitchable enzymatic substrates.

Atypical homodimerization revealed by the structure of the (S)-enantioselective haloalkane dehalogenase DmmarA from Mycobacterium marinum

Haloalkane dehalogenases (HLDs) are a family of α/β-hydrolase fold enzymes that employ SN2 nucleophilic substitution to cleave the carbon-halogen bond in diverse chemical structures, the biological role of which is still poorly understood. Atomic-level knowledge of both the inner organization and supramolecular complexation of HLDs is thus crucial to understand their catalytic and noncatalytic functions. Here, crystallographic structures of the (S)-enantioselective haloalkane dehalogenase DmmarA from the waterborne pathogenic microbe Mycobacterium marinum were determined at 1.6 and 1.85 Å resolution. The structures show a canonical αβα-sandwich HLD fold with several unusual structural features. Mechanistically, the atypical composition of the proton-relay catalytic triad (aspartate-histidine-aspartate) and uncommon active-site pocket reveal the molecular specificities of a catalytic apparatus that exhibits a rare (S)-enantiopreference. Additionally, the structures reveal a previously unobserved mode of symmetric homodimerization, which is predominantly mediated through unusual L5-to-L5 loop interactions. This homodimeric association in solution is confirmed experimentally by data obtained from small-angle X-ray scattering. Utilizing the newly determined structures of DmmarA, molecular modelling techniques were employed to elucidate the underlying mechanism behind its uncommon enantioselectivity. The (S)-preference can be attributed to the presence of a distinct binding pocket and variance in the activation barrier for nucleophilic substitution.

Computational design of enzymes for biotechnological applications

Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.

Transcriptional regulation of organohalide pollutant utilisation in bacteria

Organohalides are organic molecules formed biotically and abiotically, both naturally and through industrial production. They are usually toxic and represent a health risk for living organisms, including humans. Bacteria capable of degrading organohalides for growth express dehalogenase genes encoding enzymes that cleave carbon-halogen bonds. Such bacteria are of potential high interest for bioremediation of contaminated sites. Dehalogenase genes are often part of gene clusters that may include regulators, accessory genes and genes for transporters and other enzymes of organohalide degradation pathways. Organohalides and their degradation products affect the activity of regulatory factors, and extensive genome-wide modulation of gene expression helps dehalogenating bacteria to cope with stresses associated with dehalogenation, such as intracellular increase of halides, dehalogenase-dependent acid production, organohalide toxicity and misrouting and bottlenecks in metabolic fluxes. This review focuses on transcriptional regulation of gene clusters for dehalogenation in bacteria, as studied in laboratory experiments and in situ. The diversity in gene content, organization and regulation of such gene clusters is highlighted for representative organohalide-degrading bacteria. Selected examples illustrate a key, overlooked role of regulatory processes, often strain-specific, for efficient dehalogenation and productive growth in presence of organohalides.

CaverDock: a molecular docking-based tool to analyse ligand transport through protein tunnels and channels

MOTIVATION

Protein tunnels and channels are key transport pathways that allow ligands to pass between proteins' external and internal environments. These functionally important structural features warrant detailed attention. It is difficult to study the ligand binding and unbinding processes experimentally, while molecular dynamics simulations can be time-consuming and computationally demanding.

RESULTS

CaverDock is a new software tool for analysing the ligand passage through the biomolecules. The method uses the optimized docking algorithm of AutoDock Vina for ligand placement docking and implements a parallel heuristic algorithm to search the space of possible trajectories. The duration of the simulations takes from minutes to a few hours. Here we describe the implementation of the method and demonstrate CaverDock's usability by: (i) comparison of the results with other available tools, (ii) determination of the robustness with large ensembles of ligands and (iii) the analysis and comparison of the ligand trajectories in engineered tunnels. Thorough testing confirms that CaverDock is applicable for the fast analysis of ligand binding and unbinding in fundamental enzymology and protein engineering.

AVAILABILITY AND IMPLEMENTATION

User guide and binaries for Ubuntu are freely available for non-commercial use at https://loschmidt.chemi.muni.cz/caverdock/. The web implementation is available at https://loschmidt.chemi.muni.cz/caverweb/. The source code is available upon request.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Fluorescent substrates for haloalkane dehalogenases: Novel probes for mechanistic studies and protein labeling

Haloalkane dehalogenases are enzymes that catalyze the cleavage of carbon-halogen bonds in halogenated compounds. They serve as model enzymes for studying structure-function relationships of >100.000 members of the α/β-hydrolase superfamily. Detailed kinetic analysis of their reaction is crucial for understanding the reaction mechanism and developing novel concepts in protein engineering. Fluorescent substrates, which change their fluorescence properties during a catalytic cycle, may serve as attractive molecular probes for studying the mechanism of enzyme catalysis. In this work, we present the development of the first fluorescent substrates for this enzyme family based on coumarin and BODIPY chromophores. Steady-state and pre-steady-state kinetics with two of the most active haloalkane dehalogenases, DmmA and LinB, revealed that both fluorescent substrates provided specificity constant two orders of magnitude higher (0.14-12.6 μM^-1 s^-1) than previously reported representative substrates for the haloalkane dehalogenase family (0.00005-0.014 μM^-1 s^-1). Stopped-flow fluorescence/FRET analysis enabled for the first time monitoring of all individual reaction steps within a single experiment: (i) substrate binding, (ii-iii) two subsequent chemical steps and (iv) product release. The newly introduced fluorescent molecules are potent probes for fast steady-state kinetic profiling. In combination with rapid mixing techniques, they provide highly valuable information about individual kinetic steps and mechanism of haloalkane dehalogenases. Additionally, these molecules offer high specificity and efficiency for protein labeling and can serve as probes for studying protein hydration and dynamics as well as potential markers for cell imaging.

The impact of tunnel mutations on enzymatic catalysis depends on the tunnel-substrate complementarity and the rate-limiting step

Transport of ligands between bulk solvent and the buried active sites is a critical event in the catalytic cycle of many enzymes. The rational design of transport pathways is far from trivial due to the lack of knowledge about the effect of mutations on ligand transport. The main and an auxiliary tunnel of haloalkane dehalogenase LinB have been previously engineered for improved dehalogenation of 1,2-dibromoethane (DBE). The first chemical step of DBE conversion was enhanced by L177W mutation in the main tunnel, but the rate-limiting product release was slowed down because the mutation blocked the main access tunnel and hindered protein dynamics. Three additional mutations W140A + F143L + I211L opened-up the auxiliary tunnel and enhanced the product release, making this four-point variant the most efficient catalyst with DBE. Here we study the impact of these mutations on the catalysis of bulky aromatic substrates, 4-(bromomethyl)-6,7-dimethoxycoumarin (COU) and 8-chloromethyl-4,4'-difluoro-3,5-dimethyl-4-bora-3a,4a-diaza-s-indacene (BDP). The rate-limiting step of DBE conversion is the product release, whereas the catalysis of COU and BDP is limited by the chemical step. The catalysis of COU is mainly impaired by the mutation L177W, whereas the conversion of BDP is affected primarily by the mutations W140A + F143L + I211L. The combined computational and kinetic analyses explain the differences in activities between the enzyme-substrate pairs. The effect of tunnel mutations on catalysis depends on the rate-limiting step, the complementarity of the tunnels with the substrates and is clearly specific for each enzyme-substrate pair.

A Haloalkane Dehalogenase from a Marine Microbial Consortium Possessing Exceptionally Broad Substrate Specificity

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.IMPORTANCE 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.

Catalytic Cycle of Haloalkane Dehalogenases Toward Unnatural Substrates Explored by Computational Modeling

The anthropogenic toxic compound 1,2,3-trichloropropane is poorly degradable by natural enzymes. We have previously constructed the haloalkane dehalogenase DhaA31 by focused directed evolution ( Pavlova, M. et al. Nat. Chem. Biol. 2009 , 5 , 727 - 733 ), which is 32 times more active than the wild-type enzyme and is currently the most active variant known against that substrate. Recent evidence has shown that the structural basis responsible for the higher activity of DhaA31 was poorly understood. Here we have undertaken a comprehensive computational study of the main steps involved in the biocatalytic hydrolysis of 1,2,3-trichloropropane to decipher the structural basis for such enhancements. Using molecular dynamics and quantum mechanics approaches we have surveyed (i) the substrate binding, (ii) the formation of the reactive complex, (iii) the chemical step, and (iv) the release of the products. We showed that the binding of the substrate and its transport through the molecular tunnel to the active site is a relatively fast process. The cleavage of the carbon-halogen bond was previously identified as the rate-limiting step in the wild-type. Here we demonstrate that this step was enhanced in DhaA31 due to a significantly higher number of reactive configurations of the substrate and a decrease of the energy barrier to the S_N2 reaction. C176Y and V245F were identified as the key mutations responsible for most of those improvements. The release of the alcohol product was found to be the rate-limiting step in DhaA31 primarily due to the C176Y mutation. Mutational dissection of DhaA31 and kinetic analysis of the intermediate mutants confirmed the theoretical observations. Overall, our comprehensive computational approach has unveiled mechanistic details of the catalytic cycle which will enable a balanced design of more efficient enzymes. This approach is applicable to deepen the biochemical knowledge of a large number of other systems and may contribute to robust strategies in the development of new biocatalysts.

A receptor dependent-4D QSAR approach to predict the activity of mutated enzymes

Screening and selection tools to obtain focused libraries play a key role in successfully engineering enzymes of desired qualities. The quality of screening depends on efficient assays; however, a focused library generated with a priori information plays a major role in effectively identifying the right enzyme. As a proof of concept, for the first time, receptor dependent - 4D Quantitative Structure Activity Relationship (RD-4D-QSAR) has been implemented to predict kinetic properties of an enzyme. The novelty of this study is that the mutated enzymes also form a part of the training data set. The mutations were modeled in a serine protease and molecular dynamics simulations were conducted to derive enzyme-substrate (E-S) conformations. The E-S conformations were enclosed in a high resolution grid consisting of 156,250 grid points that stores interaction energies to generate QSAR models to predict the enzyme activity. The QSAR predictions showed similar results as reported in the kinetic studies with >80% specificity and >50% sensitivity revealing that the top ranked models unambiguously differentiated enzymes with high and low activity. The interaction energy descriptors of the best QSAR model were used to identify residues responsible for enzymatic activity and substrate specificity.

Metagenome-derived haloalkane dehalogenases with novel catalytic properties

Haloalkane dehalogenases (HLDs) are environmentally relevant enzymes cleaving a carbon-halogen bond in a wide range of halogenated pollutants. PCR with degenerate primers and genome-walking was used for the retrieval of four HLD-encoding genes from groundwater-derived environmental DNA. Using specific primers and the environmental DNA as a template, we succeeded in generating additional amplicons, resulting altogether in three clusters of sequences with each cluster comprising 8-13 closely related putative HLD-encoding genes. A phylogenetic analysis of the translated genes revealed that three HLDs are members of the HLD-I subfamily, whereas one gene encodes an enzyme from the subfamily HLD-II. Two metagenome-derived HLDs, eHLD-B and eHLD-C, each from a different subfamily, were heterologously produced in active form, purified and characterized in terms of their thermostability, pH and temperature optimum, quaternary structure, substrate specificity towards 30 halogenated compounds, and enantioselectivity. eHLD-B and eHLD-C showed striking differences in their activities, substrate preferences, and tolerance to temperature. Profound differences were also determined in the enantiopreference and enantioselectivity of these enzymes towards selected substrates. Comparing our data with those of known HLDs revealed that eHLD-C exhibits a unique combination of high thermostability, high activity, and an unusually broad pH optimum, which covers the entire range of pH 5.5-8.9. Moreover, a so far unreported high thermostability for HLDs was determined for this enzyme at pH values lower than 6.0. Thus, eHLD-C represents an attractive and novel biocatalyst for biotechnological applications.