The evolution of enzyme function in the isomerases

Multidomain chimeric enzymes as a promising alternative for biocatalysts improvement: a minireview

Searching for new and better biocatalysts is an area of study in constant development. In nature, mechanisms generally occurring in evolution, such as genetic duplication, recombination, and natural selection processes, produce various enzymes with different architectures and properties. The recombination of genes that code proteins produces multidomain chimeric enzymes that contain two or more domains that sometimes enhance their catalytic properties. Protein engineering has mimicked this process to enhance catalytic activity and the global stability of enzymes, searching for new and better biocatalysts. Here, we present and discuss examples from both natural and synthetic multidomain chimeric enzymes and how additional domains heighten their stability and catalytic activity. Moreover, we also describe progress in developing new biocatalysts using synthetic fusion enzymes and revise some methodological strategies to improve their biological fitness.

The Fate of Duplicated Enzymes in Prokaryotes: The Case of Isomerases

The isomerases are a unique enzymatic class of enzymes that carry out a great diversity of chemical reactions at the intramolecular level. This class comprises about 300 members, most of which are involved in carbohydrate and terpenoid/polyketide metabolism. Along with oxidoreductases and translocases, isomerases are one of the classes with the highest ratio of paralogous enzymes. Due to its relatively small number of members, it is plausible to explore it in greater detail to identify specific cases of gene duplication. Here, we present an analysis at the level of individual isomerases and identify different members that seem to be involved in duplication events in prokaryotes. As was suggested in a previous study, there is no homogeneous distribution of paralogs, but rather they accumulate into a few subcategories, some of which differ between Archaea and Bacteria. As expected, the metabolic processes with more paralogous isomerases have to do with carbohydrate metabolism but also with RNA modification (a particular case involving an rRNA-modifying isomerase is thoroughly discussed and analyzed in detail). Overall, our findings suggest that the most common fate for paralogous enzymes is the retention of the original enzymatic function, either associated with a dosage effect or with differential expression in response to changing environments, followed by subfunctionalization and, to a much lesser degree, neofunctionalization, which is consistent with what has been reported elsewhere.

Structural mechanism of a dual-functional enzyme DgpA/B/C as both a C-glycoside cleaving enzyme and an O- to C-glycoside isomerase

The C-glycosidic bond that connects the sugar moiety with aglycone is difficult to be broken or made due to its inert nature. The knowledge of C-glycoside breakdown and synthesis is very limited. Recently, the enzyme DgpA/B/C cascade from a human intestinal bacterium PUE was identified to specifically cleave the C-glycosidic bond of puerarin (daidzein-8-C-glucoside). Here we investigated how puerarin is recognized and oxidized by DgpA based on crystal structures of DgpA with or without substrate and biochemical characterization. More strikingly, we found that apart from being a C-glycoside cleaving enzyme, DgpA/B/C is capable of efficiently converting O- to C-glycoside showing the activity as a structure isomerase. A possible mechanistic model was proposed dependently of the simulated complex structure of DgpB/C with 3″-oxo-daidzin and structure-based mutagenesis. Our findings not only shed light on understanding the enzyme-mediated C-glycosidic bond breakage and formation, but also may help to facilitate stereospecific C-glycoside synthesis in pharmaceutical industry.

Bacterial oxidoreductive enzymes as molecular weapons for the degradation and metabolism of the toxic azo dyes in wastewater: a review

Azo dyes are extremely toxic and pose significant environmental and health risks. Consequently, mineralization and conversion to simple compounds are required to avoid their hazardous effects. A variety of enzymes from the bacterial system are thought to be involved in the degradation and metabolism of azo dyes. Bioremediation, a cost effective and eco-friendly biotechnology, involving bacteria is powered by bacterial enzymes. As mentioned, several enzymes from the bacterial system serve as molecular weapons in the degradation of these dyes. Among these enzymes, azoreductase, oxidoreductase, and laccase are of great interest for the degradation and decolorization of azo dyes. Combination of the oxidative and reductive enzymes is used for the removal of azo dyes from water. The aim of this review article is to provide information on the importance of bacterial enzymes. The review also discusses the genetically modified microorganisms in the biodegradation of azo dyes in polluted water.

Crystal structure and molecular mechanism of an E/F type bilin lyase-isomerase

Chromophore attachment of the light-harvesting apparatus represents one of the most important post-translational modifications in photosynthetic cyanobacteria. Extensive pigment diversity of cyanobacteria critically depends on bilin lyases that covalently attach chemically distinct chromophores to phycobiliproteins. However, how bilin lyases catalyze bilin ligation reactions and how some lyases acquire additional isomerase abilities remain elusive at the molecular level. Here, we report the crystal structure of a representative bilin lyase-isomerase MpeQ. This structure has revealed a "question-mark" protein architecture that unambiguously establishes the active site conserved among the E/F-type bilin lyases. Based on structural, mutational, and modeling data, we demonstrate that stereoselectivity of the active site plays a critical role in conferring the isomerase activity of MpeQ. We further advance a tyrosine-mediated reaction scheme unifying different types of bilin lyases. These results suggest that lyases and isomerase actions of bilin lyases arise from two coupled molecular events of distinct origin.

Nano-evolution and protein-based enzymatic evolution predicts novel types of natural product nanozymes of traditional Chinese medicine: cases of herbzymes of Taishan-Huangjing (Rhizoma polygonati) and Goji (Lycium chinense)

Nanozymes and natural product-derived herbzymes have been identified in different types of enzymes simulating the natural protein-based enzyme function. How to explore and predict enzyme types of novel nanozymes when synthesized remains elusive. An informed analysis might be useful for the prediction. Here, we applied a protein-evolution analysis method to predict novel types of enzymes with experimental validation. First, reported nanozymes were analyzed by chemical classification and nano-evolution. We found that nanozymes are predominantly classified as protein-based EC1 oxidoreductase. In comparison, we analyzed the evolution of protein-based natural enzymes by a phylogenetic tree and the most conserved enzymes were found to be peroxidase and lyase. Therefore, the natural products of Rhizoma polygonati and Goji herbs were analyzed to explore and test the potent new types of natural nanozymes/herbzymes using the simplicity simulation of natural protein enzyme evolution as they contain these conserved enzyme types. The experimental validation showed that the natural products from the total extract of nanoscale traditional Chinese medicine Huangjing (RP, Rhizoma polygonati) from Mount-Tai (Taishan) exhibit fructose-bisphosphate aldolase of lyase while nanoscale Goji (Lycium chinense) extract exhibits peroxidase activities. Thus, the bioinformatics analysis would provide an additional tool for the virtual discovery of natural product nanozymes.

A roadmap for metagenomic enzyme discovery

Covering: up to 2021Metagenomics has yielded massive amounts of sequencing data offering a glimpse into the biosynthetic potential of the uncultivated microbial majority. While genome-resolved information about microbial communities from nearly every environment on earth is now available, the ability to accurately predict biocatalytic functions directly from sequencing data remains challenging. Compared to primary metabolic pathways, enzymes involved in secondary metabolism often catalyze specialized reactions with diverse substrates, making these pathways rich resources for the discovery of new enzymology. To date, functional insights gained from studies on environmental DNA (eDNA) have largely relied on PCR- or activity-based screening of eDNA fragments cloned in fosmid or cosmid libraries. As an alternative, shotgun metagenomics holds underexplored potential for the discovery of new enzymes directly from eDNA by avoiding common biases introduced through PCR- or activity-guided functional metagenomics workflows. However, inferring new enzyme functions directly from eDNA is similar to searching for a 'needle in a haystack' without direct links between genotype and phenotype. The goal of this review is to provide a roadmap to navigate shotgun metagenomic sequencing data and identify new candidate biosynthetic enzymes. We cover both computational and experimental strategies to mine metagenomes and explore protein sequence space with a spotlight on natural product biosynthesis. Specifically, we compare in silico methods for enzyme discovery including phylogenetics, sequence similarity networks, genomic context, 3D structure-based approaches, and machine learning techniques. We also discuss various experimental strategies to test computational predictions including heterologous expression and screening. Finally, we provide an outlook for future directions in the field with an emphasis on meta-omics, single-cell genomics, cell-free expression systems, and sequence-independent methods.

The Role of Gene Duplication in the Divergence of Enzyme Function: A Comparative Approach

Gene duplication is a crucial process involved in the appearance of new genes and functions. It is thought to have played a major role in the growth of enzyme families and the expansion of metabolism at the biosphere's dawn and in recent times. Here, we analyzed paralogous enzyme content within each of the seven enzymatic classes for a representative sample of prokaryotes by a comparative approach. We found a high ratio of paralogs for three enzymatic classes: oxidoreductases, isomerases, and translocases, and within each of them, most of the paralogs belong to only a few subclasses. Our results suggest an intricate scenario for the evolution of prokaryotic enzymes, involving different fates for duplicated enzymes fixed in the genome, where around 20-40% of prokaryotic enzymes have paralogs. Intracellular organisms have a lesser ratio of duplicated enzymes, whereas free-living enzymes show the highest ratios. We also found that phylogenetically close phyla and some unrelated but with the same lifestyle share similar genomic and biochemical traits, which ultimately support the idea that gene duplication is associated with environmental adaptation.

Structure-function relationships in NDP-sugar active SDR enzymes: Fingerprints for functional annotation and enzyme engineering

Short-chain Dehydrogenase/Reductase enzymes that are active on nucleotide sugars (abbreviated as NS-SDR) are of paramount importance in the biosynthesis of rare sugars and glycosides. Some family members have already been extensively characterized due to their direct implication in metabolic disorders or in the biosynthesis of virulence factors. In this review, we combine the knowledge gathered from studies that typically focused only on one NS-SDR activity with an in-depth analysis and overview of all of the different NS-SDR families (169,076 enzyme sequences). Through this structure-based multiple sequence alignment of NS-SDRs retrieved from public databases, we could identify clear patterns in conservation and correlation of crucial residues. Supported by this analysis, we suggest updating and extending the UDP-galactose 4-epimerase "hexagonal box model" to an "heptagonal box model" for all NS-SDR enzymes. This specificity model consists of seven conserved regions surrounding the NDP-sugar substrate that serve as fingerprint for each specificity. The specificity fingerprints highlighted in this review will be beneficial for functional annotation of the large group of NS-SDR enzymes and form a guide for future enzyme engineering efforts focused on the biosynthesis of rare and specialty carbohydrates.

CATH: expanding the horizons of structure-based functional annotations for genome sequences

This article provides an update of the latest data and developments within the CATH protein structure classification database (http://www.cathdb.info). The resource provides two levels of release: CATH-B, a daily snapshot of the latest structural domain boundaries and superfamily assignments, and CATH+, which adds layers of derived data, such as predicted sequence domains, functional annotations and functional clustering (known as Functional Families or FunFams). The most recent CATH+ release (version 4.2) provides a huge update in the coverage of structural data. This release increases the number of fully- classified domains by over 40% (from 308 999 to 434 857 structural domains), corresponding to an almost two- fold increase in sequence data (from 53 million to over 95 million predicted domains) organised into 6119 superfamilies. The coverage of high-resolution, protein PDB chains that contain at least one assigned CATH domain is now 90.2% (increased from 82.3% in the previous release). A number of highly requested features have also been implemented in our web pages: allowing the user to view an alignment between their query sequence and a representative FunFam structure and providing tools that make it easier to view the full structural context (multi-domain architecture) of domains and chains.

To what extent do structural changes in catalytic metal sites affect enzyme function?

About half of known enzymatic reactions involve metals. Enzymes belonging to the same superfamily often evolve to catalyze different reactions on the same structural scaffold. The work presented here investigates how functional differentiation, within superfamilies that contain metalloenzymes, relates to structural changes at the catalytic metal site. In general, when the catalytic metal site is unchanged across the enzymes of a superfamily, the functional differentiation within the superfamily tends to be low and the mechanism conserved. Conversely, all types of structural changes in the metal binding site are observed for superfamilies with high functional differentiation. Overall, the catalytic role of the metal ions appears to be one of the most conserved features of the enzyme mechanism within metalloenzyme superfamilies. In particular, when the catalytic role of the metal ion does not involve a redox reaction (i.e. there is no exchange of electrons with the substrate), this role is almost always maintained even when the site undergoes significant structural changes. In these enzymes, functional diversification is most often associated with modifications in the surrounding protein matrix, which has changed so much that the enzyme chemistry is significantly altered. On the other hand, in more than 50% of the examples where the metal has a redox role in catalysis, changes at the metal site modify its catalytic role. Further, we find that there are no examples in our dataset where metal sites with a redox role are lost during evolution.

SYNOPSIS

In this paper we investigate how functional diversity within superfamilies of metalloenzymes relates to structural changes at the catalytic metal site. Evolution tends to strictly conserve the metal site. When changes occur, they do not modify the catalytic role of non-redox metals whereas they affect the role of redox-active metals.

Enzyme function and its evolution

With rapid increases over recent years in the determination of protein sequence and structure, alongside knowledge of thousands of enzyme functions and hundreds of chemical mechanisms, it is now possible to combine breadth and depth in our understanding of enzyme evolution. Phylogenetics continues to move forward, though determining correct evolutionary family trees is not trivial. Protein function prediction has spawned a variety of promising methods that offer the prospect of identifying enzymes across the whole range of chemical functions and over numerous species. This knowledge is essential to understand antibiotic resistance, as well as in protein re-engineering and de novo enzyme design.

The impacts of drift and selection on genomic evolution in insects

Genomes evolve through a combination of mutation, drift, and selection, all of which act heterogeneously across genes and lineages. This leads to differences in branch-length patterns among gene trees. Genes that yield trees with the same branch-length patterns can be grouped together into clusters. Here, we propose a novel phylogenetic approach to explain the factors that influence the number and distribution of these gene-tree clusters. We apply our method to a genomic dataset from insects, an ancient and diverse group of organisms. We find some evidence that when drift is the dominant evolutionary process, each cluster tends to contain a large number of fast-evolving genes. In contrast, strong negative selection leads to many distinct clusters, each of which contains only a few slow-evolving genes. Our work, although preliminary in nature, illustrates the use of phylogenetic methods to shed light on the factors driving rate variation in genomic evolution.

Assessing in silico the recruitment and functional spectrum of bacterial enzymes from secondary metabolism

BACKGROUND

Microbes, plants, and fungi synthesize an enormous number of metabolites exhibiting rich chemical diversity. For a high-level classification, metabolism is subdivided into primary (PM) and secondary (SM) metabolism. SM products are often not essential for survival of the organism and it is generally assumed that SM enzymes stem from PM homologs.

RESULTS

We wanted to assess evolutionary relationships and function of bona fide bacterial PM and SM enzymes. Thus, we analyzed the content of 1010 biosynthetic gene clusters (BGCs) from the MIBiG dataset; the encoded bacterial enzymes served as representatives of SM. The content of 15 bacterial genomes known not to harbor BGCs served as a representation of PM. Enzymes were categorized on their EC number and for these enzyme functions, frequencies were determined. The comparison of PM/SM frequencies indicates a certain preference for hydrolases (EC class 3) and ligases (EC class 6) in PM and of oxidoreductases (EC class 1) and lyases (EC class 4) in SM. Based on BLAST searches, we determined pairs of PM/SM homologs and their functional diversity. Oxidoreductases, transferases (EC class 2), lyases and isomerases (EC class 5) form a tightly interlinked network indicating that many protein folds can accommodate different functions in PM and SM. In contrast, the functional diversity of hydrolases and especially ligases is significantly limited in PM and SM. For the most direct comparison of PM/SM homologs, we restricted for each BGC the search to the content of the genome it comes from. For each homologous hit, the contribution of the genomic neighborhood to metabolic pathways was summarized in BGC-specific html-pages that are interlinked with KEGG; this dataset can be downloaded from https://www.bioinf.ur.de .

CONCLUSIONS

Only few reaction chemistries are overrepresented in bacterial SM and at least 55% of the enzymatic functions present in BGCs possess PM homologs. Many SM enzymes arose in PM and Nature utilized the evolvability of enzymes similarly to establish novel functions both in PM and SM. Future work aimed at the elucidation of evolutionary routes that have interconverted a PM enzyme into an SM homolog can profit from our BGC-specific annotations.

Reaction Decoder Tool (RDT): extracting features from chemical reactions

Summary: Extracting chemical features like Atom–Atom Mapping (AAM), Bond Changes (BCs) and Reaction Centres from biochemical reactions helps us understand the chemical composition of enzymatic reactions. Reaction Decoder is a robust command line tool, which performs this task with high accuracy. It supports standard chemical input/output exchange formats i.e. RXN/SMILES, computes AAM, highlights BCs and creates images of the mapped reaction. This aids in the analysis of metabolic pathways and the ability to perform comparative studies of chemical reactions based on these features.

Availability and implementation: This software is implemented in Java, supported on Windows, Linux and Mac OSX, and freely available at https://github.com/asad/ReactionDecoder

Contact: asad@ebi.ac.uk or s9asad@gmail.com

Characterising Complex Enzyme Reaction Data

The relationship between enzyme-catalysed reactions and the Enzyme Commission (EC) number, the widely accepted classification scheme used to characterise enzyme activity, is complex and with the rapid increase in our knowledge of the reactions catalysed by enzymes needs revisiting. We present a manual and computational analysis to investigate this complexity and found that almost one-third of all known EC numbers are linked to more than one reaction in the secondary reaction databases (e.g., KEGG). Although this complexity is often resolved by defining generic, alternative and partial reactions, we have also found individual EC numbers with more than one reaction catalysing different types of bond changes. This analysis adds a new dimension to our understanding of enzyme function and might be useful for the accurate annotation of the function of enzymes and to study the changes in enzyme function during evolution.

Exploring the chemistry and evolution of the isomerases

Isomerization reactions are fundamental in biology, and isomers usually differ in their biological role and pharmacological effects. In this study, we have cataloged the isomerization reactions known to occur in biology using a combination of manual and computational approaches. This method provides a robust basis for comparison and clustering of the reactions into classes. Comparing our results with the Enzyme Commission (EC) classification, the standard approach to represent enzyme function on the basis of the overall chemistry of the catalyzed reaction, expands our understanding of the biochemistry of isomerization. The grouping of reactions involving stereoisomerism is straightforward with two distinct types (racemases/epimerases and cis-trans isomerases), but reactions entailing structural isomerism are diverse and challenging to classify using a hierarchical approach. This study provides an overview of which isomerases occur in nature, how we should describe and classify them, and their diversity.

Promiscuity and electrostatic flexibility in the alkaline phosphatase superfamily

Catalytic promiscuity, that is, the ability of single enzymes to facilitate the turnover of multiple, chemically distinct substrates, is a widespread phenomenon that plays an important role in the evolution of enzyme function. Additionally, such pre-existing multifunctionality can be harnessed in artificial enzyme design. The members of the alkaline phosphatase superfamily have served extensively as both experimental and computational model systems for enhancing our understanding of catalytic promiscuity. In this Opinion, we present key recent computational studies into the catalytic activity of these highly promiscuous enzymes, highlighting the valuable insight they have provided into both the molecular basis for catalytic promiscuity in general, and its implications for the evolution of phosphatase activity.

Diversity in protein domain superfamilies

Whilst ∼93% of domain superfamilies appear to be relatively structurally and functionally conserved based on the available data from the CATH-Gene3D domain classification resource, the remainder are much more diverse. In this review, we consider how domains in some of the most ubiquitous and promiscuous superfamilies have evolved, in particular the plasticity in their functional sites and surfaces which expands the repertoire of molecules they interact with and actions performed on them. To what extent can we identify a core function for these superfamilies which would allow us to develop a ‘domain grammar of function’ whereby a protein's biological role can be proposed from its constituent domains? Clearly the first step is to understand the extent to which these components vary and how changes in their molecular make-up modifies function.

Identification of Alp1U and Lom6 as epoxy hydrolases and implications for kinamycin and lomaiviticin biosynthesis

The naturally occurring diazobenzofluorenes, kinamycins, fluostatins and lomaiviticins, possess highly oxygenated A-rings, via which the last forms a dimeric pharmacophore. However, neither the A-ring transformation nor the dimerization mechanisms have been explored thus far. Here we propose a unified biosynthetic logic for the three types of antibiotics and verify one key reaction via detailed genetic and enzymatic experiments. Alp1U and Lom6 from the kinamycin and lomaiviticin biosynthesis, respectively, are shown to catalyse epoxy hydrolysis on a substrate that is obtained by chemical deacetylation of a kinamycin-pathway-derived intermediate. Thus, our study provides the first evidence for the existence of an epoxy intermediate in lomaiviticin biosynthesis. Furthermore, our results suggest that the dimerization in the lomaiviticin biosynthesis proceeds after dehydration of a product generated by Lom6.

Kinamycins, fluostatins and lomaiviticins are naturally occurring antibiotics that possess unique diazofluorene structures and exhibit potent anti-tumour activity. Here the authors identify the epoxy hydrolases in the biosynthetic pathways of kinamycins and lomaiviticins, suggesting the existence of epoxy-intermediates in their biosynthesis.

The Classification and Evolution of Enzyme Function

Enzymes are the proteins responsible for the catalysis of life. Enzymes sharing a common ancestor as defined by sequence and structure similarity are grouped into families and superfamilies. The molecular function of enzymes is defined as their ability to catalyze biochemical reactions; it is manually classified by the Enzyme Commission and robust approaches to quantitatively compare catalytic reactions are just beginning to appear. Here, we present an overview of studies at the interface of the evolution and function of enzymes.

Modularity in protein structures: study on all-alpha proteins

Modularity is known as one of the most important features of protein's robust and efficient design. The architecture and topology of proteins play a vital role by providing necessary robust scaffolds to support organism's growth and survival in constant evolutionary pressure. These complex biomolecules can be represented by several layers of modular architecture, but it is pivotal to understand and explore the smallest biologically relevant structural component. In the present study, we have developed a component-based method, using protein's secondary structures and their arrangements (i.e. patterns) in order to investigate its structural space. Our result on all-alpha protein shows that the known structural space is highly populated with limited set of structural patterns. We have also noticed that these frequently observed structural patterns are present as modules or "building blocks" in large proteins (i.e. higher secondary structure content). From structural descriptor analysis, observed patterns are found to be within similar deviation; however, frequent patterns are found to be distinctly occurring in diverse functions e.g. in enzymatic classes and reactions. In this study, we are introducing a simple approach to explore protein structural space using combinatorial- and graph-based geometry methods, which can be used to describe modularity in protein structures. Moreover, analysis indicates that protein function seems to be the driving force that shapes the known structure space.

The enzymatic nature of an anonymous protein sequence cannot reliably be inferred from superfamily level structural information alone

As the largest fraction of any proteome does not carry out enzymatic functions, and in order to leverage 3D structural data for the annotation of increasingly higher volumes of sequence data, we wanted to assess the strength of the link between coarse grained structural data (i.e., homologous superfamily level) and the enzymatic versus non-enzymatic nature of protein sequences. To probe this relationship, we took advantage of 41 phylogenetically diverse (encompassing 11 distinct phyla) genomes recently sequenced within the GEBA initiative, for which we integrated structural information, as defined by CATH, with enzyme level information, as defined by Enzyme Commission (EC) numbers. This analysis revealed that only a very small fraction (about 1%) of domain sequences occurring in the analyzed genomes was found to be associated with homologous superfamilies strongly indicative of enzymatic function. Resorting to less stringent criteria to define enzyme versus non-enzyme biased structural classes or excluding highly prevalent folds from the analysis had only modest effect on this proportion. Thus, the low genomic coverage by structurally anchored protein domains strongly associated to catalytic activities indicates that, on its own, the power of coarse grained structural information to infer the general property of being an enzyme is rather limited.