Determinants and Prediction of Esterase Substrate Promiscuity Patterns

Identification and characterization of a promiscuous metallohydrolase in metallo-β-lactamase superfamily from a locally isolated organophosphate-degrading Bacillus sp. strain S3wahi

In this present study, characteristics and structure-function relationship of an organophosphate-degrading enzyme from Bacillus sp. S3wahi were described. S3wahi metallohydrolase, designated as S3wahi-MH (probable metallohydrolase YqjP), featured the conserved αβ/βα metallo-β-lactamase-fold (MBL-fold) domain and a zinc bimetal at its catalytic site. The metal binding site of S3wahi-MH also preserves the H-X-H-X-D-H motif, consisting of specific amino acids at Zn1 (Asp69, His70, Asp182, and His230) and Zn2 (His65, His67, and His137). The multifunctionality of S3wahi-MH was demonstrated through a steady-state kinetic study, revealing its highest binding affinity (KM) and catalytic efficiency (kcat/KM) for OP compound, paraoxon, with values of 8.09 × 10-6 M and 4.94 × 105 M-1 s-1, respectively. Using OP compound, paraoxon, as S3wahi-MH native substrate, S3wahi-MH exhibited remarkable stability over a broad temperature range, 20 °C - 60 °C and a broad pH tolerance, pH 6-10. Corresponded to S3wahi-MH thermal stability characterization, the estimated melting temperature (Tm) was found to be 72.12 °C. S3wahi-MH was also characterized with optimum catalytic activity at 30 °C and pH 8. Additionally, the activity of purified S3wahi-MH was greatly enhanced in the presence of 1 mM and 5 mM of manganese (Mn2+), showing relative activities of 1323.68 % and 2073.68 %, respectively. The activity of S3wahi-MH was also enhanced in the presence of DMSO and DMF, showing relative activities of 270.37 % and 307.41 %, respectively. The purified S3wahi-MH retained >60 % residual activity after exposure to non-ionic Tween series surfactants. Nevertheless, the catalytic activity of S3wahi-MH was severely impacted by the treatment of SDS, even at low concentrations. Considering its enzymatic properties and promiscuity, S3wahi-MH emerges as a promising candidate as a bioremediation tool in wide industrial applications, including agriculture industry.

Descriptor-augmented machine learning for enzyme-chemical interaction predictions

Descriptors play a pivotal role in enzyme design for the greener synthesis of biochemicals, as they could characterize enzymes and chemicals from the physicochemical and evolutionary perspective. This study examined the effects of various descriptors on the performance of Random Forest model used for enzyme-chemical relationships prediction. We curated activity data of seven specific enzyme families from the literature and developed the pipeline for evaluation the machine learning model performance using 10-fold cross-validation. The influence of protein and chemical descriptors was assessed in three scenarios, which were predicting the activity of unknown relations between known enzymes and known chemicals (new relationship evaluation), predicting the activity of novel enzymes on known chemicals (new enzyme evaluation), and predicting the activity of new chemicals on known enzymes (new chemical evaluation). The results showed that protein descriptors significantly enhanced the classification performance of model on new enzyme evaluation in three out of the seven datasets with the greatest number of enzymes, whereas chemical descriptors appear no effect. A variety of sequence-based and structure-based protein descriptors were constructed, among which the esm-2 descriptor achieved the best results. Using enzyme families as labels showed that descriptors could cluster proteins well, which could explain the contributions of descriptors to the machine learning model. As a counterpart, in the new chemical evaluation, chemical descriptors made significant improvement in four out of the seven datasets, while protein descriptors appear no effect. We attempted to evaluate the generalization ability of the model by correlating the statistics of the datasets with the performance of the models. The results showed that datasets with higher sequence similarity were more likely to get better results in the new enzyme evaluation and datasets with more enzymes were more likely beneficial from the protein descriptor strategy. This work provides guidance for the development of machine learning models for specific enzyme families.

Identification, Characterization, and Computer-Aided Rational Design of a Novel Thermophilic Esterase from Geobacillus subterraneus, and Application in the Synthesis of Cinnamyl Acetate

Investigation of a novel thermophilic esterase gene from Geobacillus subterraneus DSMZ 13552 indicated a high amino acid sequence similarity of 25.9% to a reported esterase from Geobacillus sp. A strategy that integrated computer-aided rational design tools was developed to select mutation sites. Six mutants were selected from four criteria based on the simulated saturation mutation (including 19 amino acid residues) results. Of these, the mutants Q78Y and G119A were found to retain 87% and 27% activity after incubation at 70 °C for 20 min, compared with the 19% activity for the wild type. Subsequently, a double-point mutant (Q78Y/G119A) was obtained and identified with optimal temperature increase from 65 to 70 °C and a 41.51% decrease in Km. The obtained T1/2 values of 42.2 min (70 °C) and 16.9 min (75 °C) for Q78Y/G119A showed increases of 340% and 412% compared with that in the wild type. Q78Y/G119A was then employed as a biocatalyst to synthesize cinnamyl acetate, for which the conversion rate reached 99.40% with 0.3 M cinnamyl alcohol at 60 °C. The results validated the enhanced enzymatic properties of the mutant and indicated better prospects for industrial application as compared to that in the wild type. This study reported a method by which an enzyme could evolve to achieve enhanced thermostability, thereby increasing its potential for industrial applications, which could also be expanded to other esterases.

Targeted sampling of natural product space to identify bioactive natural product-like polyketide macrolides

Polyketide or polyketide-like macrolides (pMLs) continue to serve as a source of inspiration for drug discovery. However, their inherent structural and stereochemical complexity challenges efforts to explore related regions of chemical space more broadly. Here, we report a strategy termed the Targeted Sampling of Natural Product space (TSNaP) that is designed to identify and assess regions of chemical space bounded by this important class of molecules. Using TSNaP, a family of tetrahydrofuran-containing pMLs are computationally assembled from pML inspired building blocks to provide a large collection of natural product-like virtual pMLs. By scoring functional group and volumetric overlap against their natural counterparts, a collection of compounds are prioritized for targeted synthesis. Using a modular and stereoselective synthetic approach, a library of polyketide-like macrolides are prepared to sample these unpopulated regions of pML chemical space. Validation of this TSNaP approach by screening this library against a panel of whole-cell biological assays, reveals hit rates exceeding those typically encountered in small molecule libraries. This study suggests that the TSNaP approach may be more broadly useful for the design of improved chemical libraries for drug discovery.

Role of the C-Terminal β Sandwich of Thermoanaerobacter tengcongensis Thermophilic Esterase in Hydrolysis of Long-Chain Acyl Substrates

To search for a novel thermostable esterase for optimized industrial applications, esterase from a thermophilic eubacterium species, Thermoanaerobacter tengcongensis MB4, was purified and characterized in this work. Sequence analysis of T. tengcongensis esterase with other homologous esterases of the same family revealed an apparent tail at the C-terminal that is not conserved across the esterase family. Hence, it was hypothesized that the tail is unlikely to have an essential structural or catalytic role. However, there is no documented report of any role for this tail region. We probed the role of the C-terminal domain on the catalytic activity and substrate preference of T. tengcongensis esterase EstA3 with a view to see how it could be engineered for enhanced properties. To achieve this, we cloned, expressed, and purified the wild-type and the truncated versions of the enzyme. In addition, a naturally occurring member of the family (from Brevibacillus brevis) that lacks the C-terminal tail was also made. In vitro characterization of the purified enzymes showed that the C-terminal domain contributes significantly to the catalytic activity and distinct substrate preference of T. tengcongensis esterase EstA3. All three recombinant enzymes showed the highest preference for paranitrophenyl butyrate (pNPC4), which suggests they are true esterases, not lipases. Kinetic data revealed that truncation had a slight effect on the substrate-binding affinity. Thus, the drop in preference towards long-chain substrates might not be a result of substrate binding affinity alone. The findings from this work could form the basis for future protein engineering allowing the modification of esterase catalytic properties through domain swapping or by attaching a modular protein domain.

Andean soil-derived lignocellulolytic bacterial consortium as a source of novel taxa and putative plastic-active enzymes

An easy and straightforward way to engineer microbial environmental communities is by setting up liquid enrichment cultures containing a specific substrate as the sole source of carbon. Here, we analyzed twenty single-contig high-quality metagenome-assembled genomes (MAGs) retrieved from a microbial consortium (T6) that was selected by the dilution-to-stimulation approach using Andean soil as inoculum and lignocellulose as a selection pressure. Based on genomic metrics (e.g., average nucleotide and amino acid identities) and phylogenomic analyses, 15 out of 20 MAGs were found to represent novel bacterial species, with one of those (MAG_26) belonging to a novel genus closely related to Caenibius spp. (Sphingomonadaceae). Following the rules and requirements of the SeqCode, we propose the name Andeanibacterium colombiense gen. nov., sp. nov. for this taxon. A subsequent functional annotation of all MAGs revealed that MAG_7 (Pseudobacter hemicellulosilyticus sp. nov.) contains 20, 19 and 16 predicted genes from carbohydrate-active enzymes families GH43, GH2 and GH92, respectively. Its lignocellulolytic gene profile resembles that of MAG_2 (the most abundant member) and MAG_3858, both of which belong to the Sphingobacteriaceae family. Using a database that contains experimentally verified plastic-active enzymes (PAZymes), twenty-seven putative bacterial polyethylene terephthalate (PET)-active enzymes (i.e., alpha/beta-fold hydrolases) were detected in all MAGs. A maximum of five putative PETases were found in MAG_3858, and two PETases were found to be encoded by A. colombiense. In conclusion, we demonstrate that lignocellulose-enriched liquid cultures coupled with genome-resolved metagenomics are suitable approaches to unveil the hidden bacterial diversity and its polymer-degrading potential in Andean soil ecosystems.

Worldwide trend discovery of structural and functional relationship of metallo-β-lactamase for structure-based drug design: A bibliometric evaluation and patent analysis

Metallo-β-lactamase (MBL) is an enzyme produced by clinically important bacteria that can inactivate many commonly used antibiotics, making them a significant concern in treating bacterial infections and the risk of having high antibiotic resistance issues among the community. This review presents a bibliometric and patent analysis of MBL worldwide research trend based on the Scopus and World Intellectual Property Organization databases in 2013-2022. Based on the keywords related to MBL in the article title, abstract, and keywords, 592 research articles were retrieved for further analysis using various tools such as Microsoft Excel to determine the frequency analysis, VOSviewer for bibliometric networks visualization, and Harzing's Publish or Perish for citation metrics analysis. Standard bibliometric parameters were analysed to evaluate the field's research trend, such as the growth of publications, topographical distribution, top subject area, most relevant journal, top cited documents, most relevant authors, and keyword trend analysis. Within 10 years, MBL discovery has shown a steady and continuous growth of interest among the community of researchers. United States of America, China, and the United Kingdom are the top 3 countries contribute high productivity to the field. The patent analysis also shows several impactful filed patents, indicating the significance of development research on the structural and functional relationship of MBL for an effective structure-based drug design (SBDD). Developing new MBL inhibitors using SBDD could help address the research gap and provide new successful therapeutic options for treating MBL-producing bacterial infections.

The metagenome-derived esterase PET40 is highly promiscuous and hydrolyses polyethylene terephthalate (PET)

Polyethylene terephthalate (PET) is a widely used synthetic polymer and known to contaminate marine and terrestrial ecosystems. Only few PET-active microorganisms and enzymes (PETases) are currently known, and it is debated whether degradation activity for PET originates from promiscuous enzymes with broad substrate spectra that primarily act on natural polymers or other bulky substrates, or whether microorganisms evolved their genetic makeup to accepting PET as a carbon source. Here, we present a predicted diene lactone hydrolase designated PET40, which acts on a broad spectrum of substrates, including PET. It is the first esterase with activity on PET from a GC-rich Gram-positive Amycolatopsis species belonging to the Pseudonocardiaceae (Actinobacteria). It is highly conserved within the genera Amycolatopsis and Streptomyces. PET40 was identified by sequence-based metagenome search using a PETase-specific hidden Markov model. Besides acting on PET, PET40 has a versatile substrate spectrum, hydrolyzing δ-lactones, β-lactam antibiotics, the polyester-polyurethane Impranil® DLN, and various para-nitrophenyl ester substrates. Molecular docking suggests that the PET degradative activity is likely a result of the promiscuity of PET40, as potential binding modes were found for substrates encompassing mono(2-hydroxyethyl) terephthalate, bis(2-hydroxyethyl) terephthalate, and a PET trimer. We also solved the crystal structure of the inactive PET40 variant S178A to 1.60 Å resolution. PET40 is active throughout a wide pH (pH 4-10) and temperature range (4-65 °C) and remarkably stable in the presence of 5% SDS, making it a promising enzyme as a starting point for further investigations and optimization approaches.

Advances in ligand-specific biosensing for structurally similar molecules

The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.

The structure of a Lactobacillus helveticus chlorogenic acid esterase and the dynamics of its insertion domain provide insights into substrate binding

Chlorogenic acid esterases (ChlEs) are a useful class of enzymes that hydrolyze chlorogenic acid (CGA) into caffeic and quinic acids. ChlEs can break down CGA in foods to improve their sensory properties and release caffeic acid in the digestive system to improve the absorption of bioactive compounds. This work presents the structure, molecular dynamics, and biochemical characterization of a ChlE from Lactobacillus helveticus (Lh). Molecular dynamics simulations suggest that substrate access to the active site of LhChlE is modulated by two hairpin loops above the active site. Docking simulations and mutational analysis suggest that two residues within the loops, Gln145 and Lys164 , are important for CGA binding. Lys164 provides a slight substrate preference for CGA, whereas Gln145 is required for efficient turnover. This work is the first to examine the dynamics of a bacterial ChlE and provides insights on substrate binding preference and turnover in this type of enzyme.

An archaeal lid-containing feruloyl esterase degrades polyethylene terephthalate

Polyethylene terephthalate (PET) is a commodity polymer known to globally contaminate marine and terrestrial environments. Today, around 80 bacterial and fungal PET-active enzymes (PETases) are known, originating from four bacterial and two fungal phyla. In contrast, no archaeal enzyme had been identified to degrade PET. Here we report on the structural and biochemical characterization of PET46 (RLI42440.1), an archaeal promiscuous feruloyl esterase exhibiting degradation activity on semi-crystalline PET powder comparable to IsPETase and LCC (wildtypes), and higher activity on bis-, and mono-(2-hydroxyethyl) terephthalate (BHET and MHET). The enzyme, found by a sequence-based metagenome search, is derived from a non-cultivated, deep-sea Candidatus Bathyarchaeota archaeon. Biochemical characterization demonstrated that PET46 is a promiscuous, heat-adapted hydrolase. Its crystal structure was solved at a resolution of 1.71 Å. It shares the core alpha/beta-hydrolase fold with bacterial PETases, but contains a unique lid common in feruloyl esterases, which is involved in substrate binding. Thus, our study widens the currently known diversity of PET-hydrolyzing enzymes, by demonstrating PET depolymerization by a plant cell wall-degrading esterase.

Molecular determinants of protein evolvability

The plethora of biological functions that sustain life is rooted in the remarkable evolvability of proteins. An emerging view highlights the importance of a protein's initial state in dictating evolutionary success. A deeper comprehension of the mechanisms that govern the evolvability of these initial states can provide invaluable insights into protein evolution. In this review, we describe several molecular determinants of protein evolvability, unveiled by experimental evolution and ancestral sequence reconstruction studies. We further discuss how genetic variation and epistasis can promote or constrain functional innovation and suggest putative underlying mechanisms. By establishing a clear framework for these determinants, we provide potential indicators enabling the forecast of suitable evolutionary starting points and delineate molecular mechanisms in need of deeper exploration.

Harnessing extremophilic carboxylesterases for applications in polyester depolymerisation and plastic waste recycling

The steady growth in industrial production of synthetic plastics and their limited recycling have resulted in severe environmental pollution and contribute to global warming and oil depletion. Currently, there is an urgent need to develop efficient plastic recycling technologies to prevent further environmental pollution and recover chemical feedstocks for polymer re-synthesis and upcycling in a circular economy. Enzymatic depolymerization of synthetic polyesters by microbial carboxylesterases provides an attractive addition to existing mechanical and chemical recycling technologies due to enzyme specificity, low energy consumption, and mild reaction conditions. Carboxylesterases constitute a diverse group of serine-dependent hydrolases catalysing the cleavage and formation of ester bonds. However, the stability and hydrolytic activity of identified natural esterases towards synthetic polyesters are usually insufficient for applications in industrial polyester recycling. This necessitates further efforts on the discovery of robust enzymes, as well as protein engineering of natural enzymes for enhanced activity and stability. In this essay, we discuss the current knowledge of microbial carboxylesterases that degrade polyesters (polyesterases) with focus on polyethylene terephthalate (PET), which is one of the five major synthetic polymers. Then, we briefly review the recent progress in the discovery and protein engineering of microbial polyesterases, as well as developing enzyme cocktails and secreted protein expression for applications in the depolymerisation of polyester blends and mixed plastics. Future research aimed at the discovery of novel polyesterases from extreme environments and protein engineering for improved performance will aid developing efficient polyester recycling technologies for the circular plastics economy.

Enzymatic Characterization of a Novel HSL Family IV Esterase EstD04 from Pseudomonas sp. D01 in Mealworm Gut Microbiota

Pseudomonas sp. D01, capable of growing in tributyrin medium, was isolated from the gut microbiota of yellow mealworm. By using in silico analyses, we discovered a hypothesized esterase encoding gene in the D01 bacterium, and its encoded protein, EstD04, was classified as a bacterial hormone-sensitive lipase (bHSL) of the type IV lipase family. The study revealed that the recombinant EstD04-His(6x) protein exhibited esterase activity and broad substrate specificity, as it was capable of hydrolyzing p-nitrophenyl derivatives with different acyl chain lengths. By using the most favorable substrate p-nitrophenyl butyrate (C₄), we defined the optimal temperature and pH value for EstD04 esterase activity as 40 °C and pH 8, respectively, with a catalytic efficiency (k_cat/K_m) of 6.17 × 10³ mM^-1 s^-1 at 40 °C. EstD04 demonstrated high stability between pH 8 and 10, and thus, it might be capably used as an alkaline esterase in industrial applications. The addition of Mg²⁺ and NH₄⁺, as well as DMSO, could stimulate EstD04 enzyme activity. Based on bioinformatic motif analyses and tertiary structural simulation, we determined EstD04 to be a typical bHSL protein with highly conserved motifs, including a triad catalytic center (Ser¹⁶⁰, Glu²⁵³, and His²⁸³), two cap regions, hinge sites, and an oxyanion hole, which are important for the type IV enzyme activity. Moreover, the sequence analysis suggested that the two unique discrete cap regions of EstD04 may contribute to its alkali mesophilic nature, allowing EstD04 to exhibit extremely distinct physiological properties from its evolutionarily closest esterase.

Contrastive learning in protein language space predicts interactions between drugs and protein targets

Sequence-based prediction of drug-target interactions has the potential to accelerate drug discovery by complementing experimental screens. Such computational prediction needs to be generalizable and scalable while remaining sensitive to subtle variations in the inputs. However, current computational techniques fail to simultaneously meet these goals, often sacrificing performance of one to achieve the others. We develop a deep learning model, ConPLex, successfully leveraging the advances in pretrained protein language models ("PLex") and employing a protein-anchored contrastive coembedding ("Con") to outperform state-of-the-art approaches. ConPLex achieves high accuracy, broad adaptivity to unseen data, and specificity against decoy compounds. It makes predictions of binding based on the distance between learned representations, enabling predictions at the scale of massive compound libraries and the human proteome. Experimental testing of 19 kinase-drug interaction predictions validated 12 interactions, including four with subnanomolar affinity, plus a strongly binding EPHB1 inhibitor (KD = 1.3 nM). Furthermore, ConPLex embeddings are interpretable, which enables us to visualize the drug-target embedding space and use embeddings to characterize the function of human cell-surface proteins. We anticipate that ConPLex will facilitate efficient drug discovery by making highly sensitive in silico drug screening feasible at the genome scale. ConPLex is available open source at https://ConPLex.csail.mit.edu.

Repurposing degradation pathways for modular metabolite biosynthesis in nematodes

Recent studies have revealed that Caenorhabditis elegans and other nematodes repurpose products from biochemical degradation pathways for the combinatorial assembly of complex modular structures that serve diverse signaling functions. Building blocks from neurotransmitter, amino acid, nucleoside and fatty acid metabolism are attached to scaffolds based on the dideoxyhexose ascarylose or glucose, resulting in hundreds of modular ascarosides and glucosides. Genome-wide association studies have identified carboxylesterases as the key enzymes mediating modular assembly, enabling rapid compound discovery via untargeted metabolomics and suggesting that modular metabolite biosynthesis originates from the 'hijacking' of conserved detoxification mechanisms. Modular metabolites thus represent a distinct biosynthetic strategy for generating structural and functional diversity in nematodes, complementing the primarily polyketide synthase- and nonribosomal peptide synthetase-derived universe of microbial natural products. Although many aspects of modular metabolite biosynthesis and function remain to be elucidated, their identification demonstrates how phenotype-driven compound discovery, untargeted metabolomics and genomic approaches can synergize to facilitate the annotation of metabolic dark matter.

In-depth analysis of biocatalysts by microfluidics: An emerging source of data for machine learning

Nowadays, the vastly increasing demand for novel biotechnological products is supported by the continuous development of biocatalytic applications which provide sustainable green alternatives to chemical processes. The success of a biocatalytic application is critically dependent on how quickly we can identify and characterize enzyme variants fitting the conditions of industrial processes. While miniaturization and parallelization have dramatically increased the throughput of next-generation sequencing systems, the subsequent characterization of the obtained candidates is still a limiting process in identifying the desired biocatalysts. Only a few commercial microfluidic systems for enzyme analysis are currently available, and the transformation of numerous published prototypes into commercial platforms is still to be streamlined. This review presents the state-of-the-art, recent trends, and perspectives in applying microfluidic tools in the functional and structural analysis of biocatalysts. We discuss the advantages and disadvantages of available technologies, their reproducibility and robustness, and readiness for routine laboratory use. We also highlight the unexplored potential of microfluidics to leverage the power of machine learning for biocatalyst development.

Unique alcohol dehydrogenases involved in algal sugar utilization by marine bacteria

Marine algae produce complex polysaccharides, which can be degraded by marine heterotrophic bacteria utilizing carbohydrate-active enzymes. The red algal polysaccharide porphyran contains the methoxy sugar 6-O-methyl-D-galactose (G6Me). In the degradation of porphyran, oxidative demethylation of this monosaccharide towards D-galactose and formaldehyde occurs, which is catalyzed by a cytochrome P450 monooxygenase and its redox partners. In direct proximity to the genes encoding for the key enzymes of this oxidative demethylation, genes encoding for zinc-dependent alcohol dehydrogenases (ADHs) were identified, which seem to be conserved in porphyran utilizing marine Flavobacteriia. Considering the fact that dehydrogenases could play an auxiliary role in carbohydrate degradation, we aimed to elucidate the physiological role of these marine ADHs. Although our results reveal that the ADHs are not involved in formaldehyde detoxification, a knockout of the ADH gene causes a dramatic growth defect of Zobellia galactanivorans with G6Me as a substrate. This indicates that the ADH is required for G6Me utilization. Complete biochemical characterizations of the ADHs from Formosa agariphila KMM 3901T (FoADH) and Z. galactanivorans DsijT (ZoADH) were performed, and the substrate screening revealed that these enzymes preferentially convert aromatic aldehydes. Additionally, we elucidated the crystal structures of FoADH and ZoADH in complex with NAD+ and showed that the strict substrate specificity of these new auxiliary enzymes is based on a narrow active site. KEY POINTS: • Knockout of the ADH-encoding gene revealed its role in 6-O-methyl-D-galactose utilization, suggesting a new auxiliary activity in marine carbohydrate degradation. • Complete enzyme characterization indicated no function in a subsequent reaction of the oxidative demethylation, such as formaldehyde detoxification. • These marine ADHs preferentially convert aromatic compounds, and their strict substrate specificity is based on a narrow active site.

Thermophilic Carboxylesterases from Hydrothermal Vents of the Volcanic Island of Ischia Active on Synthetic and Biobased Polymers and Mycotoxins

Hydrothermal vents are geographically widespread and host microorganisms with robust enzymes useful in various industrial applications. We examined microbial communities and carboxylesterases of two terrestrial hydrothermal vents of the volcanic island of Ischia (Italy) predominantly composed of Firmicutes, Proteobacteria, and Bacteroidota. High-temperature enrichment cultures with the polyester plastics polyhydroxybutyrate and polylactic acid (PLA) resulted in an increase of Thermus and Geobacillus species and to some extent Fontimonas and Schleiferia species. The screening at 37 to 70°C of metagenomic fosmid libraries from above enrichment cultures identified three hydrolases (IS10, IS11, and IS12), all derived from yet-uncultured Chloroflexota and showing low sequence identity (33 to 56%) to characterized enzymes. Enzymes expressed in Escherichia coli exhibited maximal esterase activity at 70 to 90°C, with IS11 showing the highest thermostability (90% activity after 20-min incubation at 80°C). IS10 and IS12 were highly substrate promiscuous and hydrolyzed all 51 monoester substrates tested. Enzymes were active with PLA, polyethylene terephthalate model substrate, and mycotoxin T-2 (IS12). IS10 and IS12 had a classical α/β-hydrolase core domain with a serine hydrolase catalytic triad (Ser155, His280, and Asp250) in their hydrophobic active sites. The crystal structure of IS11 resolved at 2.92 Å revealed the presence of a N-terminal β-lactamase-like domain and C-terminal lipocalin domain. The catalytic cleft of IS11 included catalytic Ser68, Lys71, Tyr160, and Asn162, whereas the lipocalin domain enclosed the catalytic cleft like a lid and contributed to substrate binding. Our study identified novel thermotolerant carboxylesterases with a broad substrate range, including polyesters and mycotoxins, for potential applications in biotechnology. IMPORTANCE High-temperature-active microbial enzymes are important biocatalysts for many industrial applications, including recycling of synthetic and biobased polyesters increasingly used in textiles, fibers, coatings and adhesives. Here, we identified three novel thermotolerant carboxylesterases (IS10, IS11, and IS12) from high-temperature enrichment cultures from Ischia hydrothermal vents and incubated with biobased polymers. The identified metagenomic enzymes originated from uncultured Chloroflexota and showed low sequence similarity to known carboxylesterases. Active sites of IS10 and IS12 had the largest effective volumes among the characterized prokaryotic carboxylesterases and exhibited high substrate promiscuity, including hydrolysis of polyesters and mycotoxin T-2 (IS12). Though less promiscuous than IS10 and IS12, IS11 had a higher thermostability with a high temperature optimum (80 to 90°C) for activity and hydrolyzed polyesters, and its crystal structure revealed an unusual lipocalin domain likely involved in substrate binding. The polyesterase activity of these enzymes makes them attractive candidates for further optimization and potential application in plastics recycling.

Enzyme adaptation to habitat thermal legacy shapes the thermal plasticity of marine microbiomes

Microbial communities respond to temperature with physiological adaptation and compositional turnover. Whether thermal selection of enzymes explains marine microbiome plasticity in response to temperature remains unresolved. By quantifying the thermal behaviour of seven functionally-independent enzyme classes (esterase, extradiol dioxygenase, phosphatase, beta-galactosidase, nuclease, transaminase, and aldo-keto reductase) in native proteomes of marine sediment microbiomes from the Irish Sea to the southern Red Sea, we record a significant effect of the mean annual temperature (MAT) on enzyme response in all cases. Activity and stability profiles of 228 esterases and 5 extradiol dioxygenases from sediment and seawater across 70 locations worldwide validate this thermal pattern. Modelling the esterase phase transition temperature as a measure of structural flexibility confirms the observed relationship with MAT. Furthermore, when considering temperature variability in sites with non-significantly different MATs, the broadest range of enzyme thermal behaviour and the highest growth plasticity of the enriched heterotrophic bacteria occur in samples with the widest annual thermal variability. These results indicate that temperature-driven enzyme selection shapes microbiome thermal plasticity and that thermal variability finely tunes such processes and should be considered alongside MAT in forecasting microbial community thermal response.

The Mobility of the Cap Domain Is Essential for the Substrate Promiscuity of a Family IV Esterase from Sorghum Rhizosphere Microbiome

Metagenomics offers the possibility to screen for versatile biocatalysts. In this study, the microbial community of the Sorghum bicolor rhizosphere was spiked with technical cashew nut shell liquid, and after incubation, the environmental DNA (eDNA) was extracted and subsequently used to build a metagenomic library. We report the biochemical features and crystal structure of a novel esterase from the family IV, EH₀, retrieved from an uncultured sphingomonad after a functional screen in tributyrin agar plates. EH₀ (optimum temperature [T_opt], 50°C; melting temperature [T_m], 55.7°C; optimum pH [pH_opt], 9.5) was stable in the presence of 10 to 20% (vol/vol) organic solvents and exhibited hydrolytic activity against p-nitrophenyl esters from acetate to palmitate, preferably butyrate (496 U mg^-1), and a large battery of 69 structurally different esters (up to 30.2 U mg^-1), including bis(2-hydroxyethyl)-terephthalate (0.16 ± 0.06 U mg^-1). This broad substrate specificity contrasts with the fact that EH₀ showed a long and narrow catalytic tunnel, whose access appears to be hindered by a tight folding of its cap domain. We propose that this cap domain is a highly flexible structure whose opening is mediated by unique structural elements, one of which is the presence of two contiguous proline residues likely acting as possible hinges, which together allow for the entrance of the substrates. Therefore, this work provides a new role for the cap domain, which until now was thought to be an immobile element that contained hydrophobic patches involved in substrate prerecognition and in turn substrate specificity within family IV esterases. IMPORTANCE A better understanding of structure-function relationships of enzymes allows revelation of key structural motifs or elements. Here, we studied the structural basis of the substrate promiscuity of EH₀, a family IV esterase, isolated from a sample of the Sorghum bicolor rhizosphere microbiome exposed to technical cashew nut shell liquid. The analysis of EH₀ revealed the potential of the sorghum rhizosphere microbiome as a source of enzymes with interesting properties, such as pH and solvent tolerance and remarkably broad substrate promiscuity. Its structure resembled those of homologous proteins from mesophilic Parvibaculum and Erythrobacter spp. and hyperthermophilic Pyrobaculum and Sulfolobus spp. and had a very narrow, single-entry access tunnel to the active site, with access controlled by a capping domain that includes a number of nonconserved proline residues. These structural markers, distinct from those of other substrate-promiscuous esterases, can help in tuning substrate profiles beyond tunnel and active site engineering.

Hydrolysis-Resistant Ester-Based Linkers for Development of Activity-Based NIR Bioluminescence Probes

Activity-based sensing (ABS) probes equipped with a NIR bioluminescence readout are promising chemical tools to study cancer biomarkers owing to their high sensitivity and deep tissue compatibility. Despite the demand, there is a dearth of such probes because NIR substrates (e.g., BL660 (a NIR luciferin analog)) are not equipped with an appropriate attachment site for ABS trigger installation. For instance, our attempts to mask the carboxylic acid moiety with standard self-immolative benzyl linkers resulted in significant background signals owing to undesirable ester hydrolysis. In this study, we overcame this longstanding challenge by rationally designing a new hydrolysis-resistant ester-based linker featuring an isopropyl shielding arm. Compared to the parent, the new design is 140.5-fold and 67.8-fold more resistant toward spontaneous and esterase-mediated hydrolysis, respectively. Likewise, we observed minimal cleavage of the ester moiety when incubated with a panel of enzymes possessing ester-hydrolyzing activity. These impressive in vitro results were corroborated through a series of key experiments in live cells. Further, we showcased the utility of this technology by developing the first NIR bioluminescent probe for nitroreductase (NTR) activity and applied it to visualize elevated NTR expression in oxygen deficient lung cancer cells and in a murine model of non-small cell lung cancer. The ability to monitor the activity of this key biomarker in a deep tissue context is critical because it is associated with tumor hypoxia, which in turn is linked to drug resistance and aggressive cancer phenotypes.

Ultrahigh-Throughput Directed Evolution of a Metal-Free α/β-Hydrolase with a Cys-His-Asp Triad into an Efficient Phosphotriesterase

Finding new mechanistic solutions for biocatalytic challenges is key in the evolutionary adaptation of enzymes, as well as in devising new catalysts. The recent release of man-made substances into the environment provides a dynamic testing ground for observing biocatalytic innovation at play. Phosphate triesters, used as pesticides, have only recently been introduced into the environment, where they have no natural counterpart. Enzymes have rapidly evolved to hydrolyze phosphate triesters in response to this challenge, converging onto the same mechanistic solution, which requires bivalent cations as a cofactor for catalysis. In contrast, the previously identified metagenomic promiscuous hydrolase P91, a homologue of acetylcholinesterase, achieves slow phosphotriester hydrolysis mediated by a metal-independent Cys-His-Asp triad. Here, we probe the evolvability of this new catalytic motif by subjecting P91 to directed evolution. By combining a focused library approach with the ultrahigh throughput of droplet microfluidics, we increase P91's activity by a factor of ≈360 (to a k_cat/K_M of ≈7 × 10⁵ M^-1 s^-1) in only two rounds of evolution, rivaling the catalytic efficiencies of naturally evolved, metal-dependent phosphotriesterases. Unlike its homologue acetylcholinesterase, P91 does not suffer suicide inhibition; instead, fast dephosphorylation rates make the formation of the covalent adduct rather than its hydrolysis rate-limiting. This step is improved by directed evolution, with intermediate formation accelerated by 2 orders of magnitude. Combining focused, combinatorial libraries with the ultrahigh throughput of droplet microfluidics can be leveraged to identify and enhance mechanistic strategies that have not reached high efficiency in nature, resulting in alternative reagents with novel catalytic machineries.

Tuning Selectivity in CalA Lipase: Beyond Tunnel Engineering

Engineering studies of Candida (Pseudozyma) antarctica lipase A (CalA) have demonstrated the potential of this enzyme in the selective hydrolysis of fatty acid esters of different chain lengths. CalA has been shown to bind substrates preferentially through an acyl-chain binding tunnel accessed via the hydrolytic active site; it has also been shown that selectivity for substrates of longer or shorter chain length can be tuned, for instance by modulating steric hindrance within the tunnel. Here we demonstrate that, whereas the tunnel region is certainly of paramount importance for substrate recognition, residues in distal regions of the enzyme can also modulate substrate selectivity. To this end, we investigate variants that carry one or more substitutions within the substrate tunnel as well as in distal regions. Combining experimental determination of the substrate selectivity using natural and synthetic substrates with computational characterization of protein dynamics and of tunnels, we deconvolute the effect of key substitutions and demonstrate that epistatic interactions contribute to procuring selectivity toward either long-chain or short/medium-chain fatty acid esters. We demonstrate that various mechanisms contribute to the diverse selectivity profiles, ranging from reshaping tunnel morphology and tunnel stabilization to obstructing the main substrate-binding tunnel, highlighting the dynamic nature of the substrate-binding region. This work provides important insights into the versatility of this robust lipase toward diverse applications.

Wide substrate range for a candidate bioremediation enzyme isolated from Nocardioides sp. strain SG-4 G

Narrow substrate ranges can impact heavily on the range of applications and hence commercial viability of candidate bioremediation enzymes. Here we show that an ester hydrolase from Nocardioides strain SG-4 G has potential as a bioremediation agent against various pollutants that can be detoxified by hydrolytic cleavage of some carboxylester, carbamate, or amide linkages. Previously we showed that a radiation-killed, freeze-dried preparation (ZimA) of this strain can rapidly degrade the benzimidazole fungicide carbendazim due to the activity of a specific ester hydrolase, MheI. Here, we report that ZimA also has substantial hydrolytic activity against phthalate diesters (dimethyl, dibutyl, and dioctyl phthalate), anilide (propanil and monalide), and carbamate ester (chlorpropham) herbicides under laboratory conditions. The reaction products are substantially less toxic, or inactive as herbicides, than the parent compounds. Tests of strain SG-4 G and Escherichia coli expressing MheI found they were also able to hydrolyse dimethyl phthalate, propanil, and chlorpropham, indicating that MheI is principally responsible for the above activities.

Assigning Functions of Unknown Enzymes by High-Throughput Enzyme Characterization

The discovery of new enzymes is strongly enabled by the implementation of high-throughput screening methods to detect enzymatic activity in single organisms or clone expression libraries, or to benchmark their performances against known prototypes. In this chapter, a number of methods, applicable at high-throughput scale, are described that allow the screening and characterization of enzymes relevant to biotechnology, particularly, ester-hydrolases (esterases, lipases, phospholipases, and polyester hydrolases).

Temperature and pH Profiling of Extracellular Amylase from Antarctic and Arctic Soil Microfungi

While diversity studies and screening for enzyme activities are important elements of understanding fungal roles in the soil ecosystem, extracting and purifying the target enzyme from the fungal cellular system is also required to characterize the enzyme. This is, in particular, necessary before developing the enzyme for industrial-scale production. In the present study, partially purified α-amylase was obtained from strains of Pseudogymnoascus sp. obtained from Antarctic and Arctic locations. Partially purified α-amylases from these polar fungi exhibited very similar characteristics, including being active at 15 °C, although having a small difference in optimum pH. Both fungal taxa are good candidates for the potential application of cold-active enzymes in biotechnological industries, and further purification and characterization steps are now required. The α-amylases from polar fungi are attractive in terms of industrial development because they are active at lower temperatures and acidic pH, thus potentially creating energy and cost savings. Furthermore, they prevent the production of maltulose, which is an undesirable by-product often formed under alkaline conditions. Psychrophilic amylases from the polar Pseudogymnoascus sp. investigated in the present study could provide a valuable future contribution to biotechnological applications.

Adaptive evolvability through direct selection instead of indirect, second-order selection

Can evolvability itself be the product of adaptive evolution? To answer this question is challenging, because any DNA mutation that alters only evolvability is subject to indirect, "second order" selection on the future effects of this mutation. Such indirect selection is weaker than "first-order" selection on mutations that alter fitness, in the sense that it can operate only under restrictive conditions. Here I discuss a route to adaptive evolvability that overcomes this challenge. Specifically, a recent evolution experiment showed that some mutations can enhance both fitness and evolvability through a combination of direct and indirect selection. Unrelated evidence from gene duplication and the evolution of gene regulation suggests that mutations with such dual effects may not be rare. Through such mutations, evolvability may increase at least in part because it provides an adaptive advantage. These observations suggest a research program on the adaptive evolution of evolvability, which aims to identify such mutations and to disentangle their direct fitness effects from their indirect effects on evolvability. If evolvability is itself adaptive, Darwinian evolution may have created more than life's diversity. It may also have helped create the very conditions that made the success of Darwinian evolution possible.

Crystal structure of a family VIII β-lactamase fold hydrolase reveals the molecular mechanism for its broad substrate scope

Family VIII esterases present similarities to class C β-lactamases, which show nucleophilic serines located at the S-X-X-K motif instead of the G-X-S-X-G or G-D-S-(L) motif shown by other carboxylesterase families. Here, we report the crystal structure of a novel family VIII (subfamily VIII. I) esterase (EH₇ ; denaturing temperature, 52.6 ± 0.3 °C; pH optimum 7.0-9.0) to deepen its broad substrate range. Indeed, the analysis of the substrate specificity revealed its capacity to hydrolyse nitrocefin as a model chromogenic cephalosporin substrate (40.4 ± 11.4 units·g^-1 ), and a large battery of 66 structurally different esters (up to 1730 min^-1 ), including bis(2-hydroxyethyl)-terephthalate (241.7 ± 8.5 units·g^-1 ) and the mycotoxin T-2 (1220 ± 52 units·g^-1 ). It also showed acyltransferase activity through the synthesis of benzyl 3-oxobutanoate (40.4 ± 11.4 units·g^-1 ) from benzyl alcohol and vinyl acetoacetate. Such a broad substrate scope is rare among family VIII esterases and lipolytic enzymes. Structural analyses of free and substrate-bound forms of this homooctamer esterase suggest that EH₇ presents a more opened and exposed S1 site having no steric hindrance for the entrance of substrates to the active site, more flexible R1, R2 and R3 regions allowing for the binding of a wide spectrum of substrates into the active site, and small residues in the conserved motif Y-X-X containing the catalytic Tyr enabling the entrance of large substrates. These unique structural elements in combination with docking experiments allowed us to gain valuable insights into the substrate specificity of this esterase and possible others belonging to family VIII.

EP-Pred: A Machine Learning Tool for Bioprospecting Promiscuous Ester Hydrolases

When bioprospecting for novel industrial enzymes, substrate promiscuity is a desirable property that increases the reusability of the enzyme. Among industrial enzymes, ester hydrolases have great relevance for which the demand has not ceased to increase. However, the search for new substrate promiscuous ester hydrolases is not trivial since the mechanism behind this property is greatly influenced by the active site’s structural and physicochemical characteristics. These characteristics must be computed from the 3D structure, which is rarely available and expensive to measure, hence the need for a method that can predict promiscuity from sequence alone. Here we report such a method called EP-pred, an ensemble binary classifier, that combines three machine learning algorithms: SVM, KNN, and a Linear model. EP-pred has been evaluated against the Lipase Engineering Database together with a hidden Markov approach leading to a final set of ten sequences predicted to encode promiscuous esterases. Experimental results confirmed the validity of our method since all ten proteins were found to exhibit a broad substrate ambiguity.

Microbial enzymes will offer limited solutions to the global plastic pollution crisis

Global economies depend on the use of fossil-fuel-based polymers with 360-400 million metric tons of synthetic polymers being produced per year. Unfortunately, an estimated 60% of the global production is disposed into the environment. Within this framework, microbiologists have tried to identify plastic-active enzymes over the past decade. Until now, this research has largely failed to deliver functional biocatalysts acting on the commodity polymers such as polyethylene (PE), polypropylene (PP), polyvinylchloride (PVC), ether-based polyurethane (PUR), polyamide (PA), polystyrene (PS) and synthetic rubber (SR). However, few enzymes are known to act on low-density and low-crystalline (amorphous) polyethylene terephthalate (PET) and ester-based PUR. These above-mentioned polymers represent >95% of all synthetic plastics produced. Therefore, the main challenge microbiologists are currently facing is in finding polymer-active enzymes targeting the majority of fossil-fuel-based plastics. However, identifying plastic-active enzymes either to implement them in biotechnological processes or to understand their potential role in nature is an emerging research field. The application of these enzymes is still in its infancy. Here, we summarize the current knowledge on microbial plastic-active enzymes, their global distribution and potential impact on plastic degradation in industrial processes and nature. We further outline major challenges in finding novel plastic-active enzymes, optimizing known ones by synthetic approaches and problems arising through falsely annotated and unfiltered use of database entries. Finally, we highlight potential biotechnological applications and possible re- and upcycling concepts using microorganisms.

A Plurizyme with Transaminase and Hydrolase Activity Catalyzes Cascade Reactions

Engineering dual‐function single polypeptide catalysts with two abiotic or biotic catalytic entities (or combinations of both) supporting cascade reactions is becoming an important area of enzyme engineering and catalysis. Herein we present the development of a PluriZyme, TR₂E₂, with efficient native transaminase (k_cat: 69.49±1.77 min⁻¹) and artificial esterase (k_cat: 3908–0.41 min⁻¹) activities integrated into a single scaffold, and evaluate its utility in a cascade reaction. TR₂E₂ (pH_opt: 8.0–9.5; T_opt: 60–65 °C) efficiently converts methyl 3‐oxo‐4‐(2,4,5‐trifluorophenyl)butanoate into 3‐(R)‐amino‐4‐(2,4,5‐trifluorophenyl)butanoic acid, a crucial intermediate for the synthesis of antidiabetic drugs. The reaction proceeds through the conversion of the β‐keto ester into the β‐keto acid at the hydrolytic site and subsequently into the β‐amino acid (e.e. >99 %) at the transaminase site. The catalytic power of the TR₂E₂PluriZyme was proven with a set of β‐keto esters, demonstrating the potential of such designs to address bioinspired cascade reactions.

Glucose oxidase converted into a general sugar-oxidase

Entrapment of glucose oxidase (GOx) within metallic gold converts this widely used enzyme into a general saccharide oxidase. The following sugar molecules were oxidized by the entrapped enzyme (in addition to D-glucose): fructose, xylose, L-glucose, glucose-6-phosphate, sucrose, lactose, methylglucoside, and the tri-saccharide raffinose. With the exception of raffinose, none of these sugars have a natural specific oxidase. The origin of this generalization of activity is attributed to the strong protein-gold 3D interactions and to the strong interactions of the co-entrapped CTAB with both the gold, and the protein. It is proposed that these interactions induce conformational changes in the channel leading to the active site, which is located at the interface between the two units of the dimeric GOx protein. The observations are compatible with affecting the specific conformation change of pulling apart and opening this gate-keeper, rendering the active site accessible to a variety of substrates. The entrapment methodology was also found to increase the thermal stability of GOx up to 100 °C and to allow its convenient reuse, two features of practical importance.

A review on the immobilization of pepsin: A Lys-poor enzyme that is unstable at alkaline pH values

Pepsin is a protease used in many different applications, and in many instances, it is utilized in an immobilized form to prevent contamination of the reaction product. This enzyme has two peculiarities that make its immobilization complex. The first one is related to the poor presence of primary amino groups on its surface (just one Lys and the terminal amino group). The second one is its poor stability at alkaline pH values. Both features make the immobilization of this enzyme to be considered a complicated goal, as most of the immobilization protocols utilize primary amino groups for immobilization. This review presents some of the attempts to get immobilized pepsin biocatalyst and their applications. The high density of anionic groups (Asp and Glu) make the anion exchange of the enzyme simpler, but this makes many of the strategies utilized to immobilize the enzyme (e.g., amino-glutaraldehyde supports) more related to a mixed ion exchange/hydrophobic adsorption than to real covalent immobilization. Finally, we propose some possibilities that can permit not only the covalent immobilization of this enzyme, but also their stabilization via multipoint covalent attachment.

Metagenomic Mining for Esterases in the Microbial Community of Los Rueldos Acid Mine Drainage Formation

Acid mine drainage (AMD) systems are extremely acidic and are metal-rich formations inhabited by relatively low-complexity communities of acidophiles whose enzymes remain mostly uncharacterized. Indeed, enzymes from only a few AMD sites have been studied. The low number of available cultured representatives and genome sequences of acidophiles inhabiting AMDs makes it difficult to assess the potential of these environments for enzyme bioprospecting. In this study, using naïve and in silico metagenomic approaches, we retrieved 16 esterases from the α/β-hydrolase fold superfamily with the closest match from uncultured acidophilic Acidobacteria, Actinobacteria (Acidithrix, Acidimicrobium, and Ferrimicrobium), Acidiphilium, and other Proteobacteria inhabiting the Los Rueldos site, which is a unique AMD formation in northwestern Spain with a pH of ∼2. Within this set, only two polypeptides showed high homology (99.4%), while for the rest, the pairwise identities ranged between 4 and 44.9%, suggesting that the diversity of active polypeptides was dominated not by a particular type of protein or highly similar clusters of proteins, but by diverse non-redundant sequences. The enzymes exhibited amino acid sequence identities ranging from 39 to 99% relative to homologous proteins in public databases, including those from other AMDs, thus indicating the potential novelty of proteins associated with a specialized acidophilic community. Ten of the 16 hydrolases were successfully expressed in Escherichia coli. The pH for optimal activity ranged from 7.0 to 9.0, with the enzymes retaining 33–68% of their activities at pH 5.5, which was consistent with the relative frequencies of acid residues (from 54 to 67%). The enzymes were the most active at 30–65°C, retaining 20–61% of their activity under the thermal conditions characterizing Los Rueldos (13.8 ± 0.6°C). The analysis of the substrate specificity revealed the capacity of six hydrolases to efficiently degrade (up to 1,652 ± 75 U/g at pH 8.0 and 30°C) acrylic- and terephthalic-like [including bis(2-hydroxyethyl)-terephthalate, BHET] esters, and these enzymes could potentially be of use for developing plastic degradation strategies yet to be explored. Our assessment uncovers the novelty and potential biotechnological interest of enzymes present in the microbial populations that inhibit the Los Rueldos AMD system.

Design of Artificial Enzymes Bearing Several Active Centers: New Trends, Opportunities and Problems

Harnessing enzymes which possess several catalytic activities is a topic where intense research has been carried out, mainly coupled with the development of cascade reactions. This review tries to cover the different possibilities to reach this goal: enzymes with promiscuous activities, fusion enzymes, enzymes + metal catalysts (including metal nanoparticles or site-directed attached organometallic catalyst), enzymes bearing non-canonical amino acids + metal catalysts, design of enzymes bearing a second biological but artificial active center (plurizymes) by coupling enzyme modelling and directed mutagenesis and plurizymes that have been site directed modified in both or in just one active center with an irreversible inhibitor attached to an organometallic catalyst. Some examples of cascade reactions catalyzed by the enzymes bearing several catalytic activities are also described. Finally, some foreseen problems of the use of these multi-activity enzymes are described (mainly related to the balance of the catalytic activities, necessary in many instances, or the different operational stabilities of the different catalytic activities). The design of new multi-activity enzymes (e.g., plurizymes or modified plurizymes) seems to be a topic with unarguable interest, as this may link biological and non-biological activities to establish new combo-catalysis routes.

A flexible kinetic assay efficiently sorts prospective biocatalysts for PET plastic subunit hydrolysis

Esterase enzymes catalyze diverse hydrolysis reactions with important biological, commercial, and biotechnological applications. For the improvement of these biocatalysts, there is a need for widely accessible, inexpensive, and adaptable activity screening assays that identify enzymes with particular substrate specificities. Natural systems for biopolymer bioconversion, and likely those designed to mimic them, depend on cocktails of enzymes, each of which specifically targets the intact material as well as water-soluble subunits of varying size. In this work, we have adapted a UV/visible assay using pH-sensitive sulfonphthalein dyes for the real-time quantification of ester hydrolysis of bis-(2-hydroxyethyl) terephthalate (BHET), a subunit of polyethylene terephthalate (PET) plastic. We applied this method to a diverse set of known PET hydrolases and commercial esterases in a microplate format. The approach identified four PET hydrolases and one commercial esterase with high levels of specificity for BHET hydrolysis. Five additional PET hydrolases and three commercial esterases, including a thermophilic enzyme, effectively hydrolyzed both BHET and its monoester product MHET (mono-(2-hydroxyethyl) terephthalate). Specific activities were discernible within one hour and reactions reached an unequivocal endpoint well within 24 hours. The results from the UV/visible method correlated well with conventional HPLC analysis of the reaction products. We examined the suitability of the method toward variable pH, temperature, enzyme preparation method, mono- and multi-ester substrate type, and level of sensitivity versus stringency, finding the assay to be easily adaptable to diverse screening conditions and kinetic measurements. This method offers an accurate, easily accessible, and cost-effective route towards high-throughput library screening to support the discovery, directed evolution, and protein engineering of these critical biocatalysts.

Machine learning modeling of family wide enzyme-substrate specificity screens

Biocatalysis is a promising approach to sustainably synthesize pharmaceuticals, complex natural products, and commodity chemicals at scale. However, the adoption of biocatalysis is limited by our ability to select enzymes that will catalyze their natural chemical transformation on non-natural substrates. While machine learning and in silico directed evolution are well-posed for this predictive modeling challenge, efforts to date have primarily aimed to increase activity against a single known substrate, rather than to identify enzymes capable of acting on new substrates of interest. To address this need, we curate 6 different high-quality enzyme family screens from the literature that each measure multiple enzymes against multiple substrates. We compare machine learning-based compound-protein interaction (CPI) modeling approaches from the literature used for predicting drug-target interactions. Surprisingly, comparing these interaction-based models against collections of independent (single task) enzyme-only or substrate-only models reveals that current CPI approaches are incapable of learning interactions between compounds and proteins in the current family level data regime. We further validate this observation by demonstrating that our no-interaction baseline can outperform CPI-based models from the literature used to guide the discovery of kinase inhibitors. Given the high performance of non-interaction based models, we introduce a new structure-based strategy for pooling residue representations across a protein sequence. Altogether, this work motivates a principled path forward in order to build and evaluate meaningful predictive models for biocatalysis and other drug discovery applications.

Predicting interactions between compounds and proteins represents a long-standing dream of drug discovery and protein engineering. Robust models of enzyme-substrate scope would dramatically advance our ability to design synthetic routes involving enzymatic catalysis. However, the lack of standardization between compound-protein interaction studies makes it difficult to evaluate the generalizability of such models. In this work we take a critical step forward by standardizing high-quality datasets measuring enzyme-substrate interactions, outlining rigorous evaluations, and proposing a new way to integrate structural information into protein representations. In testing previous modeling approaches, we highlight a surprising inability of existing models to effectively leverage compound-protein interactions to improve generalization, which challenges a perception in the literature. This establishes future opportunities for model development and integration of enzyme-substrate scope models into computer-aided synthesis planning software.

Microorganisms harbor keys to a circular bioeconomy making them useful tools in fighting plastic pollution and rising CO2 levels

The major global and man-made challenges of our time are the fossil fuel-driven climate change a global plastic pollution and rapidly emerging plant, human and animal infections. To meet the necessary global changes, a dramatic transformation must take place in science and society. This transformation will involve very intense and forward oriented industrial and basic research strongly focusing on (bio)technology and industrial bioprocesses developments towards engineering a zero-carbon sustainable bioeconomy. Within this transition microorganisms-and especially extremophiles-will play a significant and global role as technology drivers. They harbor the keys and blueprints to a sustainable biotechnology in their genomes. Within this article, we outline urgent and important areas of microbial research and technology advancements and that will ultimately make major contributions during the transition from a linear towards a circular bioeconomy.

Mechanism and Structural Insights Into a Novel Esterase, E53, Isolated From Erythrobacter longus

Esterases are a class of enzymes that split esters into an acid and an alcohol in a chemical reaction with water, having high potential in pharmaceutical, food and biofuel industrial applications. To advance the understanding of esterases, we have identified and characterized E53, an alkalophilic esterase from a marine bacterium Erythrobacter longus. The crystal structures of wild type E53 and three variants were solved successfully using the X-ray diffraction method. Phylogenetic analysis classified E53 as a member of the family IV esterase. The enzyme showed highest activity against p-nitrophenyl butyrate substrate at pH 8.5-9.5 and 40°C. Based on the structural feature, the catalytic pocket was defined as R1 (catalytic center), R2 (pocket entrance), and R3 (end area of pocket) regions. Nine variants were generated spanning R1-R3 and thorough functional studies were performed. Detailed structural analysis and the results obtained from the mutagenesis study revealed that mutations in the R1 region could regulate the catalytic reaction in both positive and negative directions; expanding the bottleneck in R2 region has improved the enzymatic activity; and R3 region was associated with the determination of the pH pattern of E53. N166A in R3 region showed reduced activity only under alkaline conditions, and structural analysis indicated the role of N166 in stabilizing the loop by forming a hydrogen bond with L193 and G233. In summary, the systematic studies on E53 performed in this work provide structural and functional insights into alkaliphilic esterases and further our knowledge of these enzymes.

Computational Enzyme Design at Zymvol

Directed evolution is the most recognized methodology for enzyme engineering. The main drawback resides in its random nature and in the limited sequence exploration; both require screening of thousands (if not millions) of variants to achieve a target function. Computer-driven approaches can limit laboratorial screening to a few hundred candidates, enabling and accelerating the development of industrial enzymes. In this book chapter, the technology adopted at Zymvol is described. An overview of the current development and future directions in the company is also provided.

Calm and Frenzy: marine obligate hydrocarbonoclastic bacteria sustain ocean wellness

According to current estimates, the annual volume of crude oil entering the ocean due to both anthropogenic activities and naturally occurring seepages reaches approximately 8.3 million metric tons. Huge discharges from accidents have caused large-scale environmental disasters with extensive damage to the marine ecosystem. The natural clean-up of petroleum spills in marine environments is carried out primarily by naturally occurring obligate hydrocarbonoclastic bacteria (OHCB). The natural hosts of OHCB include a range of marine primary producers, unicellular photosynthetic eukaryotes and cyanobacteria, which have been documented as both, suppliers of hydrocarbon-like compounds that fuel the 'cryptic' hydrocarbon cycle and as a source of isolation of new OHCB. A very new body of evidence suggests that OHCB are not only the active early stage colonizers of plastics and hence the important component of the ocean's 'plastisphere' but also encode an array of enzymes experimentally proven to act on petrochemical and bio-based polymers.

Predicting drug targets by homology modelling of Pseudomonas aeruginosa proteins of unknown function

The efficacy of antibiotics to treat bacterial infections declines rapidly due to antibiotic resistance. This problem has stimulated the development of novel antibiotics, but most attempts have failed. Consequently, the idea of mining uncharacterized genes of pathogens to identify potential targets for entirely new classes of antibiotics was proposed. Without knowing the biochemical function of a protein, it is difficult to validate its potential for drug targeting; therefore, the functional characterization of bacterial proteins of unknown function must be accelerated. Here, we present a paradigm for comprehensively predicting the biochemical functions of a large set of proteins encoded by hypothetical genes in human pathogens to identify candidate drug targets. A high-throughput approach based on homology modelling with ten templates per target protein was applied to the set of 2103 P. aeruginosa proteins encoded by hypothetical genes. The >21000 homology modelling results obtained and available biological and biochemical information about several thousand templates were scrutinized to predict the function of reliably modelled proteins of unknown function. This approach resulted in assigning one or often multiple putative functions to hundreds of enzymes, ligand-binding proteins and transporters. New biochemical functions were predicted for 41 proteins whose essential or virulence-related roles in P. aeruginosa were already experimentally demonstrated. Eleven of them were shortlisted as promising drug targets that participate in essential pathways (maintaining genome and cell wall integrity), virulence-related processes (adhesion, cell motility, host recognition) or antibiotic resistance, which are general drug targets. These proteins are conserved in other WHO priority pathogens but not in humans; therefore, they represent high-potential targets for preclinical studies. These and many more biochemical functions assigned to uncharacterized proteins of P. aeruginosa, made available as PaPUF database, may guide the design of experimental screening of inhibitors, which is a crucial step towards the validation of the highest-potential targets for the development of novel drugs against P. aeruginosa and other high-priority pathogens.

Environmental role of aromatic carboxylesterases

The carboxylesterases (EC 3.1.1.x) are widely distributed and form an important yet diverse group of hydrolases catalysing the ester bond cleavage in a variety of substrates. Besides acting on plant cell wall components like cutin, tannin and feruloyl esters, they are often the first line of defence to metabolize drugs, xenobiotics, pesticides, insecticides and plastic. But for the promiscuity of some carboxylesterases and cutinases, very few enzymes act exclusively on aromatic carboxylic acid esters. Infrequent occurrence of aromatic carboxylesterases suggests that aromatic carboxylesters are inherently more difficult to hydrolyse than the regular carboxylesters because of both steric and polar effects. Naturally occurring aromatic carboxylesters were rare before the anthropogenic activity augmented their environmental presence and diversity. An appraisal of the literature shows that the hydrolysis of aromatic carboxylic esters is a uniquely difficult endeavour and hence deserves special attention. Enzymes to hydrolyse such esters are evolving rapidly in nature. Very few such enzymes are known and they often display much lower catalytic efficiencies. Obviously, the esters of aromatic carboxylic acids, including polyethylene terephthalate waste, pose an environmental challenge. In this review, we highlight the uniqueness of aromatic carboxylesters and then underscore the importance of relevant carboxylesterases.

Combinatorial Assembly of Modular Glucosides via Carboxylesterases Regulates C. elegans Starvation Survival

The recently discovered modular glucosides (MOGLs) form a large metabolite library derived from combinatorial assembly of moieties from amino acid, neurotransmitter, and lipid metabolism in the model organism C. elegans. Combining CRISPR-Cas9 genome editing, comparative metabolomics, and synthesis, we show that the carboxylesterase homologue Cel-CEST-1.2 is responsible for specific 2-O-acylation of diverse glucose scaffolds with a wide variety of building blocks, resulting in more than 150 different MOGLs. We further show that this biosynthetic role is conserved for the closest homologue of Cel-CEST-1.2 in the related nematode species C. briggsae, Cbr-CEST-2. Expression of Cel-cest-1.2 and MOGL biosynthesis are strongly induced by starvation conditions in C. elegans, one of the premier model systems for mechanisms connecting nutrition and physiology. Cel-cest-1.2-deletion results in early death of adult animals under starvation conditions, providing first insights into the biological functions of MOGLs.

Enhanced Production of (S)-2-arylpropionic Acids by Protein Engineering and Whole-Cell Catalysis

Esterases are important biocatalysts for chemical synthesis. Several bHSL family esterases have been used to prepare (S)-2-arylpropionic acids with stronger anti-inflammatory effects via kinetic resolution. Here, we presented the discovery of key residues that controlled the enantioselectivity of bHSL family esterases to ethyl 2-arylpropionates, through careful analysis of the structural information and molecular docking. A new bHSL family esterase, Est924, was identified as a promising catalyst for kinetic resolution of racemic ethyl 2-arylpropionates with slight (R)-stereopreference. Using Est924 as the starting enzyme, protein engineering was conducted at hotspots, and the substitution of A203 was proved to enhance the enantioselectivity. The stereopreference of the mutant M1 (A203W) was inverted to ethyl (S)-2-arylpropionates, and this stereopreference was further improved in variant M3 (I202F/A203W/G208F). In addition, the optimal variant, M3, was also suitable for the resolution of ibuprofen ethyl ester and ketoprofen ethyl ester, and their efficient (S)-isomers were synthesized. Next, the whole-cell catalyst harboring M3 was used to prepare (S)-ketoprofen. (S)-ketoprofen with 86%ee was produced by whole-cell catalyst with a single freeze-thaw cycle, and the cells could be reused for at least five cycles. Our results suggested that Est924 variants could kinetically resolve economically important racemates for industrial production and further offer the opportunity for the rational design of enzyme enantioselectivity. Moreover, it is an economical process to prepare optically pure (S)-ketoprofen and (S)-naproxen by using an engineered strain harboring M3 as the catalyst.

Structural-Based Modeling in Protein Engineering. A Must Do

Biotechnological solutions will be a key aspect in our immediate future society, where optimized enzymatic processes through enzyme engineering might be an important solution for waste transformation, clean energy production, biodegradable materials, and green chemistry, for example. Here we advocate the importance of structural-based bioinformatics and molecular modeling tools in such developments. We summarize our recent experiences indicating a great prediction/success ratio, and we suggest that an early in silico phase should be performed in enzyme engineering studies. Moreover, we demonstrate the potential of a new technique combining Rosetta and PELE, which could provide a faster and more automated procedure, an essential aspect for a broader use.