Structures of hyperstable ancestral haloalkane dehalogenases show restricted conformational dynamics

Ancestral carbonic anhydrase with significantly enhanced stability and activity for CO2 capture and utilization

Carbonic anhydrases (CAs) has garnered increasing attention in carbon capture, utilization and storage (CCUS) due to their ecological friendliness. However, most of them suffer susceptibility to deactivation in harsh conditions. Herein, a reliable dataset was adopted for creating ancestral CAs through an optimized ancestral sequence reconstruction (ASR) method. After prescreening, the ancestor AncCA19 was obtained and successfully expressed. The hydration activity of AncCA19 was as high as 58,859 WAU/mg, with the optimum temperature and pH obtained by esterase assay at 100 ℃ and 9, respectively. AncCA19 had the longest half-life (1.7 h) at 95 ℃ compared with existing CAs. After 2 weeks' incubation in artificial seawater at 30 ℃ or 25.0 % N-methyldiethanolamine (MDEA) at 60 ℃, the activities remained above 47,370 WAU/mg and 6,596 WAU/mg, respectively. Thus, AncCA19, as a novel benchmark of CAs, exhibits exceptional stability in a variety CCUS applications, establishing a versatile candidate for effective CO2 capture.

Characterization, structural, and evolutionary analysis of an extremophilic GH5 endoglucanase from Bacillus sp. G131: Insights from ancestral sequence reconstruction

Nature has developed extremozymes that catalyze complex reaction processes in extreme environmental conditions. Accordingly, a combined approach consisting of extremozyme screening, ancestral sequence resurrection (ASR), and molecular dynamic simulation was utilized to construct a developed endoglucanase. The primary experimental and in-silico data led to the prediction of a hypothetical sequence of endoglucanase (EG5-G131) using Bacillus sp. G131 confirmed by amplification and sequencing. EG5-G131 exhibited noticeable stability in a broad-pH range, several detergents, organic solvents, and temperatures up to 80 °C. The molecular weight, Vmax, and Km of the purified endoglucanase were estimated to be 36 kDa, 4.32 μmol/min, and 23.62 mg/ml, respectively. The calculated thermodynamic parameters for EG5-G131 confirmed its intrinsic thermostability. Computational analysis revealed Glu142 and Glu230 as active-site residues of the enzyme. Furthermore, the enzyme remained bound to cellotetraose at 298 K, 333 K, 343 K, and 353 K for 300 ns, consistent with our experimental data. ASR of EG5-G131 led to the introduction of ancestral ANC204 and ANC205, which show similar thermodynamic characteristics with the last Firmicute common ancestor. Finally, truncating loops from the N-terminal of two sequences created two variants with desirable thermal stability, suggesting the evolutionary deciphering of the functional domain of the GH5 family in Bacillus sp. G131.

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.

Unlocking the potential of enzyme engineering via rational computational design strategies

Enzymes play a pivotal role in various industries by enabling efficient, eco-friendly, and sustainable chemical processes. However, the low turnover rates and poor substrate selectivity of enzymes limit their large-scale applications. Rational computational enzyme design, facilitated by computational algorithms, offers a more targeted and less labor-intensive approach. There has been notable advancement in employing rational computational protein engineering strategies to overcome these issues, it has not been comprehensively reviewed so far. This article reviews recent developments in rational computational enzyme design, categorizing them into three types: structure-based, sequence-based, and data-driven machine learning computational design. Case studies are presented to demonstrate successful enhancements in catalytic activity, stability, and substrate selectivity. Lastly, the article provides a thorough analysis of these approaches, highlights existing challenges and potential solutions, and offers insights into future development directions.

Stability Increase of Phenolic Acid Decarboxylase by a Combination of Protein and Solvent Engineering Unlocks Applications at Elevated Temperatures

Enzymatic decarboxylation of biobased hydroxycinnamic acids gives access to phenolic styrenes for adhesive production. Phenolic acid decarboxylases are proficient enzymes that have been applied in aqueous systems, organic solvents, biphasic systems, and deep eutectic solvents, which makes stability a key feature. Stabilization of the enzyme would increase the total turnover number and thus reduce the energy consumption and waste accumulation associated with biocatalyst production. In this study, we used ancestral sequence reconstruction to generate thermostable decarboxylases. Investigation of a set of 16 ancestors resulted in the identification of a variant with an unfolding temperature of 78.1 °C and a half-life time of 45 h at 60 °C. Crystal structures were determined for three selected ancestors. Structural attributes were calculated to fit different regression models for predicting the thermal stability of variants that have not yet been experimentally explored. The models rely on hydrophobic clusters, salt bridges, hydrogen bonds, and surface properties and can identify more stable proteins out of a pool of candidates. Further stabilization was achieved by the application of mixtures of natural deep eutectic solvents and buffers. Our approach is a straightforward option for enhancing the industrial application of the decarboxylation process.

Preparation and Characterization of an Ancient Aminopeptidase Obtained from Ancestral Sequence Reconstruction for L-Carnosine Synthesis

As a biologically active peptide, L-carnosine has been widely used in the pharmaceutical, cosmetic and health care industries due to its various physiological properties. However, relatively little research is available regarding L-carnosine's enzymatic synthesis function. In this study, a potential enzyme sequence with the function of carnosine synthesizing was screened out using the ancestral sequence reconstruction (ASR) technique. Identified with L-carnosine synthesis activity, this enzyme was further confirmed using autoproteolytic phenomenon via Western blot and N-terminal sequencing. After purification, the enzymatic properties of LUCA-DmpA were characterized. The melting temperature (T_m) and denaturation enthalpy (ΔH) of LUCA-DmpA were 60.27 ± 1.24 °C and 1306.00 ± 26.73 kJ·mol^-1, respectively. Circular dichroism (CD) spectroscopy results showed that this ancestral enzyme was composed of α-helix (35.23 ± 0.06%), β-sheet (11.06 ± 0.06%), β-turn (23.67 ± 0.06%) and random coil (32.03 ± 0.06%). The enzyme was characterized with the optimal temperature and pH of 45 °C and 9.0, respectively. Notably, LUCA-DmpA was also characterized with remarkable pH tolerance based on the observation of more than 85% remaining enzymatic activity after incubation at different pH buffers (pH = 6-11) for 12 h. Additionally, rather than being improved or inhibited by metal ions, its enzymatic activity was found to be promoted by introducing organic solvent with a larger log P value. Based on these homology modeling results, the screened LUCA-DmpA is suggested to have further optimization potential, and thereafter to be offered as a promising candidate for real industrial applications.

Engineering and characterization of dehalogenase enzymes from Delftia acidovorans in bioremediation of perfluorinated compounds

Per- and Polyfluorinated alkyl substances (PFAS) are a broad class of synthetic compounds that have fluorine substituted for hydrogen in several or all locations and are globally categorized as PFCs (perfluorochemicals; commonly called fluorinated chemicals). These compounds have unique chemical and physical properties that enable their use in non-stick surfaces, fire-fighting efforts, and as slick coatings. However, recent concerns over the health effects of such compounds, specifically perfluorooctanoic acid and perfluorooctane sulfonic acid (PFOA, PFOS; PFOA/S), have led to increased attention and research by the global community into degradation methods. In this study, soil samples from PFAS-contamination sites were cultured and screened for microbes with PFOA/S degradation potential, which led to the identification of Delftia acidovorans. It was found that D. acidovorans isolated from PFAS-contaminated soils was capable of growth in minimal media with PFOA as a sole carbon resource, and an observable fluoride concentration increase was observed when cells were exposed to PFOA. This suggests potential activity of a dehalogenase enzyme that may be of use in PFOA or PFAS microbial remediation efforts. Several associated haloacid dehalogenases have been identified in the D. acidovorans genome and have been engineered for expression in Escherichia coli for rapid production and purification. These enzymes have shown potential for enzymatic defluorination, a significant step in biological degradation and removal of PFOA/S from the environment. We hypothesize that bioremediation of PFAS using naturally occurring microbial degradation pathways may represent a novel approach to remove PFAS contamination.

Structural Analysis of the Ancestral Haloalkane Dehalogenase AncLinB-DmbA

Haloalkane dehalogenases (EC 3.8.1.5) play an important role in hydrolytic degradation of halogenated compounds, resulting in a halide ion, a proton, and an alcohol. They are used in biocatalysis, bioremediation, and biosensing of environmental pollutants and also for molecular tagging in cell biology. The method of ancestral sequence reconstruction leads to prediction of sequences of ancestral enzymes allowing their experimental characterization. Based on the sequences of modern haloalkane dehalogenases from the subfamily II, the most common ancestor of thoroughly characterized enzymes LinB from Sphingobium japonicum UT26 and DmbA from Mycobacterium bovis 5033/66 was in silico predicted, recombinantly produced and structurally characterized. The ancestral enzyme AncLinB-DmbA was crystallized using the sitting-drop vapor-diffusion method, yielding rod-like crystals that diffracted X-rays to 1.5 Å resolution. Structural comparison of AncLinB-DmbA with their closely related descendants LinB and DmbA revealed some differences in overall structure and tunnel architecture. Newly prepared AncLinB-DmbA has the highest active site cavity volume and the biggest entrance radius on the main tunnel in comparison to descendant enzymes. Ancestral sequence reconstruction is a powerful technique to study molecular evolution and design robust proteins for enzyme technologies.

Mini Review: Advances in 2-Haloacid Dehalogenases

The 2-haloacid dehalogenases (EC 3.8.1.X) are industrially important enzymes that catalyze the cleavage of carbon-halogen bonds in 2-haloalkanoic acids, releasing halogen ions and producing corresponding 2-hydroxyl acids. These enzymes are of particular interest in environmental remediation and environmentally friendly synthesis of optically pure chiral compounds due to their ability to degrade a wide range of halogenated compounds with astonishing efficiency for enantiomer resolution. The 2-haloacid dehalogenases have been extensively studied with regard to their biochemical characterization, protein crystal structures, and catalytic mechanisms. This paper comprehensively reviews the source of isolation, classification, protein structures, reaction mechanisms, biochemical properties, and application of 2-haloacid dehalogenases; current trends and avenues for further development have also been included.

Fully Automated Ancestral Sequence Reconstruction using FireProtASR

Protein evolution and protein engineering techniques are of great interest in basic science and industrial applications such as pharmacology, medicine, or biotechnology. Ancestral sequence reconstruction (ASR) is a powerful technique for probing evolutionary relationships and engineering robust proteins with good thermostability and broad substrate specificity. The following protocol describes the setting up and execution of an automated FireProt^ASR workflow using a dedicated web site. The service allows for inference of ancestral proteins automatically, from a single protein sequence. Once a protein sequence is submitted, the server will build a dataset of homology sequences, perform a multiple sequence alignment (MSA), build a phylogenetic tree, and reconstruct ancestral nodes. The protocol is also highly flexible and allows for multiple forms of input, advanced settings, and the ability to start jobs from: (i) a single sequence, (ii) a set of homologous sequences, (iii) an MSA, and (iv) a phylogenetic tree. This approach automates all necessary steps and offers a way for novices with limited exposure to ASR techniques to improve the properties of a protein of interest. The technique can even be used to introduce catalytic promiscuity into an enzyme. A web server for accessing the fully automated workflow is freely accessible at https://loschmidt.chemi.muni.cz/fireprotasr/. © 2021 Wiley Periodicals LLC. Basic Protocol: ASR using the Web Server FireProt^ASR.

Ancestral sequence reconstruction for protein engineers

In addition to its value in the study of molecular evolution, ancestral sequence reconstruction (ASR) has emerged as a useful methodology for engineering proteins with enhanced properties. Proteins generated by ASR often exhibit unique or improved activity, stability, and/or promiscuity, all of which are properties that are valued by protein engineers. Comparison between extant proteins and evolutionary intermediates generated by ASR also allows protein engineers to identify substitutions that have contributed to functional innovation or diversification within protein families. As ASR becomes more widely adopted as a protein engineering approach, it is important to understand the applications, limitations, and recent developments of this technique. This review highlights recent exemplifications of ASR, as well as technical aspects of the reconstruction process that are relevant to protein engineering.