Exploring the evolution of novel enzyme functions within structurally defined protein superfamilies

Noncanonical Amino Acids: Bringing New-to-Nature Functionalities to Biocatalysis

Biocatalysis has become an important component of modern organic chemistry, presenting an efficient and environmentally friendly approach to synthetic transformations. Advances in molecular biology, computational modeling, and protein engineering have unlocked the full potential of enzymes in various industrial applications. However, the inherent limitations of the natural building blocks have sparked a revolutionary shift. In vivo genetic incorporation of noncanonical amino acids exceeds the conventional 20 amino acids, opening new avenues for innovation. This review provides a comprehensive overview of applications of noncanonical amino acids in biocatalysis. We aim to examine the field from multiple perspectives, ranging from their impact on enzymatic reactions to the creation of novel active sites, and subsequent catalysis of new-to-nature reactions. Finally, we discuss the challenges, limitations, and promising opportunities within this dynamic research domain.

Conformational Modulation of a Mobile Loop Controls Catalysis in the (βα)8-Barrel Enzyme of Histidine Biosynthesis HisF

The overall significance of loop motions for enzymatic activity is generally accepted. However, it has largely remained unclear whether and how such motions can control different steps of catalysis. We have studied this problem on the example of the mobile active site β1α1-loop (loop1) of the (βα)8-barrel enzyme HisF, which is the cyclase subunit of imidazole glycerol phosphate synthase. Loop1 variants containing single mutations of conserved amino acids showed drastically reduced rates for the turnover of the substrates N'-[(5'-phosphoribulosyl) formimino]-5-aminoimidazole-4-carboxamide ribonucleotide (PrFAR) and ammonia to the products imidazole glycerol phosphate (ImGP) and 5-aminoimidazole-4-carboxamide-ribotide (AICAR). A comprehensive mechanistic analysis including stopped-flow kinetics, X-ray crystallography, NMR spectroscopy, and molecular dynamics simulations detected three conformations of loop1 (open, detached, closed) whose populations differed between wild-type HisF and functionally affected loop1 variants. Transient stopped-flow kinetic experiments demonstrated that wt-HisF binds PrFAR by an induced-fit mechanism whereas catalytically impaired loop1 variants bind PrFAR by a simple two-state mechanism. Our findings suggest that PrFAR-induced formation of the closed conformation of loop1 brings active site residues in a productive orientation for chemical turnover, which we show to be the rate-limiting step of HisF catalysis. After the cyclase reaction, the closed loop conformation is destabilized, which favors the formation of detached and open conformations and hence facilitates the release of the products ImGP and AICAR. Our data demonstrate how different conformations of active site loops contribute to different catalytic steps, a finding that is presumably of broad relevance for the reaction mechanisms of (βα)8-barrel enzymes and beyond.

A method for the systematic selection of enzyme panel candidates by solving the maximum diversity problem

Enzymes are being increasingly exploited for their potential as industrial biocatalysts. Establishing a portfolio of useful biocatalysts from large and diverse protein family is challenging and a systematic method for candidate selection promises to aid in this task. Moreover, accurate enzyme functional annotation can only be confidently guaranteed through experimental characterisation in the laboratory. The selection of catalytically diverse enzyme panels for experimental characterisation is also an important step for shedding light on the currently unannotated proteins in enzyme families. Current selection methods often lack efficiency and scalability, and are usually non-systematic. We present a novel algorithm for the automatic selection of subsets from enzyme families. A tabu search algorithm solving the maximum diversity problem for sequence identity was designed and implemented, and applied to three diverse enzyme families. We show that this approach automatically selects panels of enzymes that contain high richness and relative abundance of the known catalytic functions, and outperforms other methods such as k-medoids.

Biochemical and molecular characterization of a novel glycerol dehydratase from Klebsiella pneumoniae 2e with high tolerance against crude glycerol impurities

BACKGROUND

The direct bioconversion of crude glycerol, a byproduct of biodiesel production, into 1,3-propanediol by microbial fermentation constitutes a remarkably promising value-added applications. However, the low activity of glycerol dehydratase, which is the key and rate-limiting enzyme in the 1,3-propanediol synthetic pathway, caused by crude glycerol impurities is one of the main factors affecting the 1,3-propanediol yield. Hence, the exploration of glycerol dehydratase resources suitable for crude glycerol bioconversion is required for the development of 1,3-propanediol-producing engineered strains.

RESULTS

In this study, the novel glycerol dehydratase 2eGDHt, which has a tolerance against crude glycerol impurities from Klebsiella pneumoniae 2e, was characterized. The 2eGDHt exhibited the highest activity toward glycerol, with Km and Vm values of 3.42 mM and 58.15 nkat mg-1, respectively. The optimum pH and temperature for 2eGDHt were 7.0 and 37 °C, respectively. 2eGDHt displayed broader pH stability than other reported glycerol dehydratases. Its enzymatic activity was increased by Fe2+ and Tween-20, with 294% and 290% relative activities, respectively. The presence of various concentrations of the crude glycerol impurities, including NaCl, methanol, oleic acid, and linoleic acid, showed limited impact on the 2eGDHt activity. In addition, the enzyme activity was almost unaffected by the presence of an impurity mixture that mimicked the crude glycerol environment. Structural analyses revealed that 2eGDHt possesses more coil structures than reported glycerol dehydratases. Moreover, molecular dynamics simulations and site-directed mutagenesis analyses implied that the existence of unique Val744 from one of the increased coil regions played a key role in the tolerance characteristic by increasing the protein flexibility.

CONCLUSIONS

This study provides insight into the mechanism for enzymatic action and the tolerance against crude glycerol impurities, of a novel glycerol dehydratase 2eGDHt, which is a promising glycerol dehydratase candidate for biotechnological conversion of crude glycerol into 1,3-PDO.

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.

Using mechanism similarity to understand enzyme evolution

Enzyme reactions take place in the active site through a series of catalytic steps, which are collectively termed the enzyme mechanism. The catalytic step is thereby the individual unit to consider for the purposes of building new enzyme mechanisms - i.e. through the mix and match of individual catalytic steps, new enzyme mechanisms and reactions can be conceived. In the case of natural evolution, it has been shown that new enzyme functions have emerged through the tweaking of existing mechanisms by the addition, removal, or modification of some catalytic steps, while maintaining other steps of the mechanism intact. Recently, we have extracted and codified the information on the catalytic steps of hundreds of enzymes in a machine-readable way, with the aim of automating this kind of evolutionary analysis. In this paper, we illustrate how these data, which we called the "rules of enzyme catalysis", can be used to identify similar catalytic steps across enzymes that differ in their overall function and/or structural folds. A discussion on a set of three enzymes that share part of their mechanism is used as an exemplar to illustrate how this approach can reveal divergent and convergent evolution of enzymes at the mechanistic level.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-022-01022-9.

Uniform binding and negative catalysis at the origin of enzymes

Enzymes are well known for their catalytic abilities, some even reaching "catalytic perfection" in the sense that the reaction they catalyze has reached the physical bound of the diffusion rate. However, our growing understanding of enzyme superfamilies has revealed that only some share a catalytic chemistry while others share a substrate-handle binding motif, for example, for a particular phosphate group. This suggests that some families emerged through a "substrate-handle-binding-first" mechanism ("binding-first" for brevity) instead of "chemistry-first" and we are, therefore, left to wonder what the role of non-catalytic binders might have been during enzyme evolution. In the last of their eight seminal, back-to-back articles from 1976, John Albery and Jeremy Knowles addressed the question of enzyme evolution by arguing that the simplest mode of enzyme evolution is what they defined as "uniform binding" (parallel stabilization of all enzyme-bound states to the same degree). Indeed, we show that a uniform-binding proto-catalyst can accelerate a reaction, but only when catalysis is already present, that is, when the transition state is already stabilized to some degree. Thus, we sought an alternative explanation for the cases where substrate-handle-binding preceded any involvement of a catalyst. We find that evolutionary starting points that exhibit negative catalysis can redirect the reaction's course to a preferred product without need for rate acceleration or product release; that is, if they do not stabilize, or even destabilize, the transition state corresponding to an undesired product. Such a mechanism might explain the emergence of "binding-first" enzyme families like the aldolase superfamily.

Phthalate hydrolase: distribution, diversity and molecular evolution

The alpha/beta-fold superfamily of hydrolases is rapidly becoming one of the largest groups of structurally related enzymes with diverse catalytic functions. In this superfamily of enzymes, esterase deserves special attention because of their wide distribution in biological systems and importance towards environmental and industrial applications. Among various esterases, phthalate hydrolases are the key alpha/beta enzymes involved in the metabolism of structurally diverse estrogenic phthalic acid esters, ubiquitously distributed synthetic chemicals, used as plasticizer in plastic manufacturing processes. Although they vary both at the sequence and functional levels, these hydrolases use a similar acid-base-nucleophile catalytic mechanism to catalyse reactions on structurally different substrates. The current review attempts to present insights on phthalate hydrolases, describing their sources, structural diversities, phylogenetic affiliations and catalytically different types or classes of enzymes, categorized as diesterase, monoesterase and diesterase-monoesterase, capable of hydrolysing phthalate diester, phthalate monoester and both respectively. Furthermore, available information on in silico analyses and site-directed mutagenesis studies revealing structure-function integrity and altered enzyme kinetics have been highlighted along with the possible scenario of their evolution at the molecular level.

A combination of bioinformatics analysis and rational design strategies to enhance keratinase thermostability for efficient biodegradation of feathers

Keratinase has shown great significance and application potentials in the biodegradation and recycle of keratin waste due to its unique and efficient hydrolysis ability. However, the inherent instability of the enzyme limits its practical utilization. Herein, we obtained a thermostability-enhanced keratinase based on a combination of bioinformatics analysis and rational design strategies for the efficient biodegradation of feathers. A systematical in silico analysis combined with filtering of virtual libraries derived a smart library for experimental validation. Synergistic mutations around the highly flexible loop, the calcium binding site and the non-consensus amino acids generated a dominant mutant which increased the optimal temperature of keratinase from 40 °C to 60 °C, and the half-life at 60 °C was increased from 17.3 min to 66.1 min. The mutant could achieve more than 66% biodegradation of 50 g/L feathers to high-valued keratin product with a major molecular weight of 36 kDa. Collectively, this work provided a promising keratinase variant with enhanced thermostability for efficient conversion of keratin wastes to valuable products. It also generated a general strategy to facilitate enzyme thermostability design which is more targeted and predictable.

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.

Surface charged amino acid-based strategy for rational engineering of kinetic stability and specific activity of enzymes: Linking experiments with computational modeling

A rational workflow for engineering kinetically stable enzymes with good specific activity by surface charged amino acids engineering was proposed based on systematically analyzing the results of mutating 44 negatively charged surface amino acids of a thermophilic β-mannanase (ManAK). Computational data, combined with experimental results indicated that percentage side-chain solvent accessibility (PSSA), changes in Gibbs free energy of unfolding (∆∆G_mut) and root-mean-square fluctuations (RMSF) could be suitable for screening kinetically stable mutants. A combinational standard (∆∆G_mut < -0.5 kJ/mol and RMSF >0.68 Å) resulted a decrease in the proportion of destabilizing mutants to 12.5%. The perturbations of substrate affinity and specific activity caused by mutation were weakened as the shortest distance from C_α of mutated site to C_α of catalytic sites (Ds_Cα-Cα) increased. Results indicated that hotspot zones contributing to the local stability and integrity of catalytic motif at elevated temperatures might be widely distributed across spatial structure of the protein, while the mutation perturbation on enzyme specific activity demonstrated a gradually weakening trend from the catalytic core to the protein surface. These findings further our understanding of the structural-functional relationships of protein and highlight a deduced workflow to engineering industrially useful enzymes.

Enhancement of the Isomerization Activity and Thermostability of Cellobiose 2-Epimerase from Caldicellulosiruptor saccharolyticus by Exchange of a Flexible Loop

Cellobiose 2-epimerase (CE) offers a promising enzymatic approach to produce lactulose. However, its application is limited by the unsatisfactory isomerization activity and thermostability. Our study attempted to optimize the catalytic performances of CEs by flexible loop exchange, for which four mutants were constructed using CsCE (CE from Caldicellulosiruptor saccharolyticus) as a template. As a result, all mutants maintained the same catalytic directions as the templates. Mutant RmC displayed a 2.2- and 1.34-fold increase in the isomerization activity and catalytic efficiency, respectively. According to the results of molecular dynamics (MD) simulations, it was revealed that the loop exchange in RmC enlarged the entrance of the active site for substrate binding and benefited proton transfer involved in the isomerization process. Besides, the t_1/2 of mutant StC at 70 °C was increased from 29.07 to 38.29 h, owing to the abundance of rigid residues (proline) within the flexible loop of StC. Our work demonstrated that the isomerization activity and thermostability of CEs were closely related to the flexible loop surrounding the active site, which provides a new perspective to engineer CEs for higher lactulose production.

Evolutionary aspects and enzymology of metazoan carotenoid cleavage oxygenases

The carotenoids are terpenoid fat-soluble pigments produced by plants, algae, and several bacteria and fungi. They are ubiquitous components of animal diets. Carotenoid cleavage oxygenase (CCO) superfamily members are involved in carotenoid metabolism and are present in all kingdoms of life. Throughout the animal kingdom, carotenoid oxygenases are widely distributed and they are completely absent only in two unicellular organisms, Monosiga and Leishmania. Mammals have three paralogs 15,15'-β-carotene oxygenase (BCO1), 9',10'-β-carotene oxygenase (BCO2) and RPE65. The first two enzymes are classical carotenoid oxygenases: they cleave carbon‑carbon double bonds and incorporate two atoms of oxygen in the substrate at the site of cleavage. The third, RPE65, is an unusual family member, it is the retinoid isomerohydrolase in the visual cycle that converts all-trans-retinyl ester into 11-cis-retinol. Here we discuss evolutionary aspects of the carotenoid cleavage oxygenase superfamily and their enzymology to deduce what insight we can obtain from their evolutionary conservation.

A flavin-dependent monooxygenase catalyzes the initial step in cyanogenic glycoside synthesis in ferns

Cyanogenic glycosides form part of a binary plant defense system that, upon catabolism, detonates a toxic hydrogen cyanide bomb. In seed plants, the initial step of cyanogenic glycoside biosynthesis-the conversion of an amino acid to the corresponding aldoxime-is catalyzed by a cytochrome P450 from the CYP79 family. An evolutionary conundrum arises, as no CYP79s have been identified in ferns, despite cyanogenic glycoside occurrence in several fern species. Here, we report that a flavin-dependent monooxygenase (fern oxime synthase; FOS1), catalyzes the first step of cyanogenic glycoside biosynthesis in two fern species (Phlebodium aureum and Pteridium aquilinum), demonstrating convergent evolution of biosynthesis across the plant kingdom. The FOS1 sequence from the two species is near identical (98%), despite diversifying 140 MYA. Recombinant FOS1 was isolated as a catalytic active dimer, and in planta, catalyzes formation of an N-hydroxylated primary amino acid; a class of metabolite not previously observed in plants.

Effect of sequence padding on the performance of deep learning models in archaeal protein functional prediction

The use of raw amino acid sequences as input for deep learning models for protein functional prediction has gained popularity in recent years. This scheme obliges to manage proteins with different lengths, while deep learning models require same-shape input. To accomplish this, zeros are usually added to each sequence up to a established common length in a process called zero-padding. However, the effect of different padding strategies on model performance and data structure is yet unknown. We propose and implement four novel types of padding the amino acid sequences. Then, we analysed the impact of different ways of padding the amino acid sequences in a hierarchical Enzyme Commission number prediction problem. Results show that padding has an effect on model performance even when there are convolutional layers implied. Contrastingly to most of deep learning works which focus mainly on architectures, this study highlights the relevance of the deemed-of-low-importance process of padding and raises awareness of the need to refine it for better performance. The code of this analysis is publicly available at https://github.com/b2slab/padding_benchmark .

Selective Modulation of Dynamic Protein Complexes

Dynamic proteins perform critical roles in cellular machines, including those that control proteostasis, transcription, translation, and signaling. Thus, dynamic proteins are prime candidates for chemical probe and drug discovery but difficult targets because they do not conform to classical rules of design and screening. Selectivity is pivotal for candidate probe molecules due to the extensive interaction network of these dynamic hubs. Recognition that the traditional rules of probe discovery are not necessarily applicable to dynamic proteins and their complexes, as well as technological advances in screening, have produced remarkable results in the last 2-4 years. Particularly notable are the improvements in target selectivity for small-molecule modulators of dynamic proteins, especially with techniques that increase the discovery likelihood of allosteric regulatory mechanisms. We focus on approaches to small-molecule screening that appear to be more suitable for highly dynamic targets and have the potential to streamline identification of selective modulators.

The physical basis and practical consequences of biological promiscuity

Proteins interact with metabolites, nucleic acids, and other proteins to orchestrate the myriad catalytic, structural and regulatory functions that support life from the simplest microbes to the most complex multicellular organisms. These molecular interactions are often exquisitely specific, but never perfectly so. Adventitious "promiscuous" interactions are ubiquitous due to the thousands of macromolecules and small molecules crowded together in cells. Such interactions may perturb protein function at the molecular level, but as long as they do not compromise organismal fitness, they will not be removed by natural selection. Although promiscuous interactions are physiologically irrelevant, they are important because they can provide a vast reservoir of potential functions that can provide the starting point for evolution of new functions, both in nature and in the laboratory.

Emerging Frontiers in the Study of Molecular Evolution

A collection of the editors of Journal of Molecular Evolution have gotten together to pose a set of key challenges and future directions for the field of molecular evolution. Topics include challenges and new directions in prebiotic chemistry and the RNA world, reconstruction of early cellular genomes and proteins, macromolecular and functional evolution, evolutionary cell biology, genome evolution, molecular evolutionary ecology, viral phylodynamics, theoretical population genomics, somatic cell molecular evolution, and directed evolution. While our effort is not meant to be exhaustive, it reflects research questions and problems in the field of molecular evolution that are exciting to our editors.

The “Green” FMOs: Diversity, Functionality and Application of Plant Flavoproteins

Flavin-dependent monooxygenases (FMOs) are ancient enzymes present in all kingdoms of life. FMOs typically catalyze the incorporation of an oxygen atom from molecular oxygen into small molecules. To date, the majority of functional characterization studies have been performed on mammalian, fungal and bacterial FMOs, showing that they play fundamental roles in drug and xenobiotic metabolism. By contrast, our understanding of FMOs across the plant kingdom is very limited, despite plants possessing far greater FMO diversity compared to both bacteria and other multicellular organisms. Here, we review the progress of plant FMO research, with a focus on FMO diversity and functionality. Significantly, of the FMOs characterized to date, they all perform oxygenation reactions that are crucial steps within hormone metabolism, pathogen resistance, signaling and chemical defense. This demonstrates the fundamental role FMOs have within plant metabolism, and presents significant opportunities for future research pursuits and downstream applications.

A global analysis of function and conservation of catalytic residues in enzymes

The catalytic residues of an enzyme comprise the amino acids located in the active center responsible for accelerating the enzyme-catalyzed reaction. These residues lower the activation energy of reactions by performing several catalytic functions. Decades of enzymology research has established general themes regarding the roles of specific residues in these catalytic reactions, but it has been more difficult to explore these roles in a more systematic way. Here, we review the data on the catalytic residues of 648 enzymes, as annotated in the Mechanism and Catalytic Site Atlas (M-CSA), and compare our results with those in previous studies. We structured this analysis around three key properties of the catalytic residues: amino acid type, catalytic function, and sequence conservation in homologous proteins. As expected, we observed that catalysis is mostly accomplished by a small set of residues performing a limited number of catalytic functions. Catalytic residues are typically highly conserved, but to a smaller degree in homologues that perform different reactions or are nonenzymes (pseudoenzymes). Cross-analysis yielded further insights revealing which residues perform particular functions and how often. We obtained more detailed specificity rules for certain functions by identifying the chemical group upon which the residue acts. Finally, we show the mutation tolerance of the catalytic residues based on their roles. The characterization of the catalytic residues, their functions, and conservation, as presented here, is key to understanding the impact of mutations in evolution, disease, and enzyme design. The tools developed for this analysis are available at the M-CSA website and allow for user specific analysis of the same data.

Computational classification of MocR transcriptional regulators into subgroups as a support for experimental and functional characterization

MocR bacterial transcriptional regulators are a subfamily within the GntR family. The MocR proteins possess an N-terminal domain containing the winged Helix-Turn-Helix (wHTH) motif and a C-terminal domain whose architecture is homologous to the fold type-I pyridoxal 5'-phosphate (PLP) dependent enzymes and whose archetypical protein is aspartate aminotransferase (AAT). The ancestor of the fold type-I PLP dependent super-family is considered one of the earliest enzymes. The members of this super-family are the product of evolution which resulted in a diversified protein population able to catalyze a set of reactions on substrates often containing amino groups. The MocR regulators are activators or repressors of gene control within many metabolic pathways often involving PLP enzymes. This diversity implies that MocR specifically responds to different classes of effector molecules. Therefore, it is of interest to compare the AAT domains of MocR from six bacteria phyla. Multi dimensional scaling and cluster analyses suggested that at least three subgroups exist within the population that reflects functional specialization rather than taxonomic origin. The AAT-domains of the three clusters display variable degree of similarity to different fold type-I PLP enzyme families. The results support the hypothesis that independent fusion events generated at least three different MocR subgroups.

Exploring Enzyme Evolution from Changes in Sequence, Structure, and Function

The goal of our research is to increase our understanding of how biology works at the molecular level, with a particular focus on how enzymes evolve their functions through adaptations to generate new specificities and mechanisms. FunTree (Sillitoe and Furnham, Nucleic Acids Res 44:D317-D323, 2016) is a resource that brings together sequence, structure, phylogenetic, and chemical and mechanistic information for 2340 CATH superfamilies (Sillitoe et al., Nucleic Acids Res 43:D376-D381, 2015) (which all contain at least one enzyme) to allow evolution to be investigated within a structurally defined superfamily.We will give an overview of FunTree's use of sequence and structural alignments to cluster proteins within a superfamily into structurally similar groups (SSGs) and generate phylogenetic trees augmented by ancestral character estimations (ACE). This core information is supplemented with new measures of functional similarity (Rahman et al., Nat Methods 11:171-174, 2014) to compare enzyme reactions based on overall bond changes, reaction centers (the local environment atoms involved in the reaction), and the structural similarities of the metabolites involved in the reaction. These trees are also decorated with taxonomic and Enzyme Commission (EC) code and GO annotations, forming the basis of a comprehensive web interface that can be found at http://www.funtree.info . In this chapter, we will discuss the various analyses and supporting computational tools in more detail, describing the steps required to extract information.

Atlas of the Radical SAM Superfamily: Divergent Evolution of Function Using a "Plug and Play" Domain

The radical SAM superfamily contains over 100,000 homologous enzymes that catalyze a remarkably broad range of reactions required for life, including metabolism, nucleic acid modification, and biogenesis of cofactors. While the highly conserved SAM-binding motif responsible for formation of the key 5'-deoxyadenosyl radical intermediate is a key structural feature that simplifies identification of superfamily members, our understanding of their structure-function relationships is complicated by the modular nature of their structures, which exhibit varied and complex domain architectures. To gain new insight about these relationships, we classified the entire set of sequences into similarity-based subgroups that could be visualized using sequence similarity networks. This superfamily-wide analysis reveals important features that had not previously been appreciated from studies focused on one or a few members. Functional information mapped to the networks indicates which members have been experimentally or structurally characterized, their known reaction types, and their phylogenetic distribution. Despite the biological importance of radical SAM chemistry, the vast majority of superfamily members have never been experimentally characterized in any way, suggesting that many new reactions remain to be discovered. In addition to 20 subgroups with at least one known function, we identified additional subgroups made up entirely of sequences of unknown function. Importantly, our results indicate that even general reaction types fail to track well with our sequence similarity-based subgroupings, raising major challenges for function prediction for currently identified and new members that continue to be discovered. Interactive similarity networks and other data from this analysis are available from the Structure-Function Linkage Database.

Highly active enzymes by automated combinatorial backbone assembly and sequence design

Automated design of enzymes with wild-type-like catalytic properties has been a long-standing but elusive goal. Here, we present a general, automated method for enzyme design through combinatorial backbone assembly. Starting from a set of homologous yet structurally diverse enzyme structures, the method assembles new backbone combinations and uses Rosetta to optimize the amino acid sequence, while conserving key catalytic residues. We apply this method to two unrelated enzyme families with TIM-barrel folds, glycoside hydrolase 10 (GH10) xylanases and phosphotriesterase-like lactonases (PLLs), designing 43 and 34 proteins, respectively. Twenty-one GH10 and seven PLL designs are active, including designs derived from templates with <25% sequence identity. Moreover, four designs are as active as natural enzymes in these families. Atomic accuracy in a high-activity GH10 design is further confirmed by crystallographic analysis. Thus, combinatorial-backbone assembly and design may be used to generate stable, active, and structurally diverse enzymes with altered selectivity or activity.

Computationally designed enzymes often show lower activity or stability than their natural counterparts. Here, the authors present an evolution-inspired method for automated enzyme design, creating stable enzymes with accurate active site architectures and wild-type-like activities.

Evolutionary repurposing of a sulfatase: A new Michaelis complex leads to efficient transition state charge offset

The recruitment and evolutionary optimization of promiscuous enzymes is key to the rapid adaptation of organisms to changing environments. Our understanding of the precise mechanisms underlying enzyme repurposing is, however, limited: What are the active-site features that enable the molecular recognition of multiple substrates with contrasting catalytic requirements? To gain insights into the molecular determinants of adaptation in promiscuous enzymes, we performed the laboratory evolution of an arylsulfatase to improve its initially weak phenylphosphonate hydrolase activity. The evolutionary trajectory led to a 100,000-fold enhancement of phenylphosphonate hydrolysis, while the native sulfate and promiscuous phosphate mono- and diester hydrolyses were only marginally affected (≤50-fold). Structural, kinetic, and in silico characterizations of the evolutionary intermediates revealed that two key mutations, T50A and M72V, locally reshaped the active site, improving access to the catalytic machinery for the phosphonate. Measured transition state (TS) charge changes along the trajectory suggest the creation of a new Michaelis complex (E•S, enzyme-substrate), with enhanced leaving group stabilization in the TS for the promiscuous phosphonate (β_leavinggroup from -1.08 to -0.42). Rather than altering the catalytic machinery, evolutionary repurposing was achieved by fine-tuning the molecular recognition of the phosphonate in the Michaelis complex, and by extension, also in the TS. This molecular scenario constitutes a mechanistic alternative to adaptation solely based on enzyme flexibility and conformational selection. Instead, rapid functional transitions between distinct chemical reactions rely on the high reactivity of permissive active-site architectures that allow multiple substrate binding modes.

Improving the thermostability of Serratia marcescens B4A chitinase via G191V site-directed mutagenesis

Chitinases with high thermostability are important for many industrial and biotechnological applications. This study was conducted to enhance the stability of Serratia marcescens B4A chitinase by site directed mutagenesis of G191 V. Further characterization showed that the thermal stability of the mutant showed marked increase of about 5 and 15 fold at 50 and 60 °C respectively, while the optimum temperature and pH was retained. Kinetic analysis showed decreased K_m and V_max of the mutant in comparison with the wild type chitinase of about 1.3 and 3 fold, respectively. Based on structural prediction, it was speculated that this replacement shortened an important loop concomitant with the extension of adjacent β sheets. Accordingly, a higher thermostability of G191 V up to 90 °C supporting the decreased flexibility of unfolded state was also indicated. Finally, a practical proof of kinetic and thermal stabilization of chitinase was provided through decreased flexibility and entropic stabilization of its surface loops.

Evolution of enzymes with new specificity by high-throughput screening using DmpR-based genetic circuits and multiple flow cytometry rounds

Genetic circuit-based biosensors are useful in detecting target metabolites or in vivo enzymes using transcription factors (Tx) as a molecular switch to express reporter signals, such as cellular fluorescence and antibiotic resistance. Herein, a phenol-detecting Tx (DmpR) was employed as a critical tool for enzyme engineering, specifically for the rapid analysis of numerous mutants with multiple mutations at the active site of tryptophan-indole lyase (TIL, EC 4.1.99.1). Cellular fluorescence was monitored cell-by-cell using flow cytometry to detect the creation of phenolic compounds by a new tyrosine-phenol-lyase (TPL, EC 4.1.99.2). In the TIL scaffold, target amino acids near the indole ring (Asp¹³⁷, Phe³⁰⁴, Val³⁹⁴, Ile³⁹⁶ and His⁴⁶³) were mutated randomly to construct a large diversity of specificity variations. Collection of candidate positives by cell sorting using flow cytometry and subsequent shuffling of beneficial mutations identified a critical hit with four mutations (D137P, F304D, V394L, and I396R) in the TIL sequence. The variant displayed one-thirteenth the level of TPL activity, compared with native TPLs, and completely lost the original TIL activity. The findings demonstrate that hypersensitive, Tx-based biosensors could be useful critically to generate new activity from a related template, which would alleviate the current burden to high-throughput screening.

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.

The Classification of Protein Domains

The significant expansion in protein sequence and structure data that we are now witnessing brings with it a pressing need to bring order to the protein world. Such order enables us to gain insights into the evolution of proteins, their function and the extent to which the functional repertoire can vary across the three kingdoms of life. This has lead to the creation of a wide range of protein family classifications that aim to group proteins based upon their evolutionary relationships.In this chapter we discuss the approaches and methods that are frequently used in the classification of proteins, with a specific emphasis on the classification of protein domains. The construction of both domain sequence and domain structure databases is considered and we show how the use of domain family annotations to assign structural and functional information is enhancing our understanding of genomes.

Resolving protein structure-function-binding site relationships from a binding site similarity network perspective

Functional annotation is seldom straightforward with complexities arising due to functional divergence in protein families or functional convergence between non-homologous protein families, leading to mis-annotations. An enzyme may contain multiple domains and not all domains may be involved in a given function, adding to the complexity in function annotation. To address this, we use binding site information from bound cognate ligands and catalytic residues, since it can help in resolving fold-function relationships at a finer level and with higher confidence. A comprehensive database of 2,020 fold-function-binding site relationships has been systematically generated. A network-based approach is employed to capture the complexity in these relationships, from which different types of associations are deciphered, that identify versatile protein folds performing diverse functions, same function associated with multiple folds and one-to-one relationships. Binding site similarity networks integrated with fold, function, and ligand similarity information are generated to understand the depth of these relationships. Apart from the observed continuity in the functional site space, network properties of these revealed versatile families with topologically different or dissimilar binding sites and structural families that perform very similar functions. As a case study, subtle changes in the active site of a set of evolutionarily related superfamilies are studied using these networks. Tracing of such similarities in evolutionarily related proteins provide clues into the transition and evolution of protein functions. Insights from this study will be helpful in accurate and reliable functional annotations of uncharacterized proteins, poly-pharmacology, and designing enzymes with new functional capabilities. Proteins 2017; 85:1319-1335. © 2017 Wiley Periodicals, Inc.

Two strategies to engineer flexible loops for improved enzyme thermostability

Flexible sites are potential targets for engineering the stability of enzymes. Nevertheless, the success rate of the rigidifying flexible sites (RFS) strategy is still low due to a limited understanding of how to determine the best mutation candidates. In this study, two parallel strategies were applied to identify mutation candidates within the flexible loops of Escherichia coli transketolase (TK). The first was a “back to consensus mutations” approach, and the second was computational design based on ΔΔG calculations in Rosetta. Forty-nine single variants were generated and characterised experimentally. From these, three single-variants I189H, A282P, D143K were found to be more thermostable than wild-type TK. The combination of A282P with H192P, a variant constructed previously, resulted in the best all-round variant with a 3-fold improved half-life at 60 °C, 5-fold increased specific activity at 65 °C, 1.3-fold improved k_cat and a T_m increased by 5 °C above that of wild type. Based on a statistical analysis of the stability changes for all variants, the qualitative prediction accuracy of the Rosetta program reached 65.3%. Both of the two strategies investigated were useful in guiding mutation candidates to flexible loops, and had the potential to be used for other enzymes.

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.

Functional Trade-Offs in Promiscuous Enzymes Cannot Be Explained by Intrinsic Mutational Robustness of the Native Activity

The extent to which an emerging new function trades off with the original function is a key characteristic of the dynamics of enzyme evolution. Various cases of laboratory evolution have unveiled a characteristic trend; a large increase in a new, promiscuous activity is often accompanied by only a mild reduction of the native, original activity. A model that associates weak trade-offs with “evolvability” was put forward, which proposed that enzymes possess mutational robustness in the native activity and plasticity in promiscuous activities. This would enable the acquisition of a new function without compromising the original one, reducing the benefit of early gene duplication and therefore the selection pressure thereon. Yet, to date, no experimental study has examined this hypothesis directly. Here, we investigate the causes of weak trade-offs by systematically characterizing adaptive mutations that occurred in two cases of evolutionary transitions in enzyme function: (1) from phosphotriesterase to arylesterase, and (2) from atrazine chlorohydrolase to melamine deaminase. Mutational analyses in various genetic backgrounds revealed that, in contrast to the prevailing model, the native activity is less robust to mutations than the promiscuous activity. For example, in phosphotriesterase, the deleterious effect of individual mutations on the native phosphotriesterase activity is much larger than their positive effect on the promiscuous arylesterase activity. Our observations suggest a revision of the established model: weak trade-offs are not caused by an intrinsic robustness of the native activity and plasticity of the promiscuous activity. We propose that upon strong adaptive pressure for the new activity without selection against the original one, selected mutations will lead to the largest possible increases in the new function, but whether and to what extent they decrease the old function is irrelevant, creating a bias towards initially weak trade-offs and the emergence of generalist enzymes.

Understanding how enzymes evolve is a fundamental question that can help us decipher not only the mechanisms of evolution on a higher level, i.e., whole organisms, but also advances our knowledge of sequence-structure-function relationships as a guide to artificial evolution in the test tube. An important yet unexplained phenomenon occurs during the evolution of a new enzymatic function; it has been observed that new and ancestral functions often trade-off only weakly, meaning the original native activity is initially maintained at a high level despite drastic improvement of the new promiscuous activity. It has previously been proposed that weak trade-offs occur because the native activity is robust to mutations while the promiscuous activity is not. However, the present work contradicts this hypothesis, based on the detailed characterization of mutational effects on both activities in two examples of enzyme evolution. We propose an alternative explanation: the weak activity trade-off is consistent with being a by-product of strong selection for the new activity rather than an intrinsic property of the native activity.

Structuring evolution: biochemical networks and metabolic diversification in birds

Background

Recurrence and predictability of evolution are thought to reflect the correspondence between genomic and phenotypic dimensions of organisms, and the connectivity in deterministic networks within these dimensions. Direct examination of the correspondence between opportunities for diversification imbedded in such networks and realized diversity is illuminating, but is empirically challenging because both the deterministic networks and phenotypic diversity are modified in the course of evolution. Here we overcome this problem by directly comparing the structure of a “global” carotenoid network – comprising of all known enzymatic reactions among naturally occurring carotenoids – with the patterns of evolutionary diversification in carotenoid-producing metabolic networks utilized by birds.

Results

We found that phenotypic diversification in carotenoid networks across 250 species was closely associated with enzymatic connectivity of the underlying biochemical network – compounds with greater connectivity occurred the most frequently across species and were the hotspots of metabolic pathway diversification. In contrast, we found no evidence for diversification along the metabolic pathways, corroborating findings that the utilization of the global carotenoid network was not strongly influenced by history in avian evolution.

Conclusions

The finding that the diversification in species-specific carotenoid networks is qualitatively predictable from the connectivity of the underlying enzymatic network points to significant structural determinism in phenotypic evolution.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-016-0731-z) contains supplementary material, which is available to authorized users.

Chopping and Changing: the Evolution of the Flavin-dependent Monooxygenases

Flavin-dependent monooxygenases play a variety of key physiological roles and are also very powerful biotechnological tools. These enzymes have been classified into eight different classes (A–H) based on their sequences and biochemical features. By combining structural and sequence analysis, and phylogenetic inference, we have explored the evolutionary history of classes A, B, E, F, and G and demonstrate that their multidomain architectures reflect their phylogenetic relationships, suggesting that the main evolutionary steps in their divergence are likely to have arisen from the recruitment of different domains. Additionally, the functional divergence within in each class appears to have been the result of other mechanisms such as a complex set of single-point mutations. Our results reinforce the idea that a main constraint on the evolution of cofactor-dependent enzymes is the functional binding of the cofactor. Additionally, a remarkable feature of this family is that the sequence of the key flavin adenine dinucleotide-binding domain is split into at least two parts in all classes studied here. We propose a complex set of evolutionary events that gave rise to the origin of the different classes within this family.

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Changes in domain architectures reflect the phylogeny of flavin monooxygenases.

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Recruitment of different domains has been the main force driving its evolution.

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A notable feature of flavin monooxygenases is that the flavin adenine dinucleotide-binding domain is split.

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Classes of monooxygenases emerged from an ancestral domain by structural changes.

The Amaryllidaceae alkaloids: biosynthesis and methods for enzyme discovery

Amaryllidaceae alkaloids are an example of the vast diversity of secondary metabolites with great therapeutic promise. The identification of novel compounds in this group with over 300 known structures continues to be an area of active study. The recent identification of norbelladine 4'-O-methyltransferase (N4OMT), an Amaryllidaceae alkaloid biosynthetic enzyme, and the assembly of transcriptomes for Narcissus sp. aff. pseudonarcissus and Lycoris aurea highlight the potential for discovery of Amaryllidaceae alkaloid biosynthetic genes with new technologies. Recent technical advances of interest include those in enzymology, next generation sequencing, genetic modification, nuclear magnetic resonance spectroscopy (NMR), and mass spectrometry (MS).

Comparative analyses of quaternary arrangements in homo-oligomeric proteins in superfamilies: Functional implications

A comprehensive analysis of the quaternary features of distantly related homo-oligomeric proteins is the focus of the current study. This study has been performed at the levels of quaternary state, symmetry, and quaternary structure. Quaternary state and quaternary structure refers to the number of subunits and spatial arrangements of subunits, respectively. Using a large dataset of available 3D structures of biologically relevant assemblies, we show that only 53% of the distantly related homo-oligomeric proteins have the same quaternary state. Considering these homologous homo-oligomers with the same quaternary state, conservation of quaternary structures is observed only in 38% of the pairs. In 36% of the pairs of distantly related homo-oligomers with different quaternary states the larger assembly in a pair shows high structural similarity with the entire quaternary structure of the related protein with lower quaternary state and it is referred as "Russian doll effect." The differences in quaternary state and structure have been suggested to contribute to the functional diversity. Detailed investigations show that even though the gross functions of many distantly related homo-oligomers are the same, finer level differences in molecular functions are manifested by differences in quaternary states and structures. Comparison of structures of biological assemblies in distantly and closely related homo-oligomeric proteins throughout the study differentiates the effects of sequence divergence on the quaternary structures and function. Knowledge inferred from this study can provide insights for improved protein structure classification and function prediction of homo-oligomers. Proteins 2016; 84:1190-1202. © 2016 Wiley Periodicals, Inc.

Substrate Binding Mode and Molecular Basis of a Specificity Switch in Oxalate Decarboxylase

Oxalate decarboxylase (OxDC) catalyzes the conversion of oxalate into formate and carbon dioxide in a remarkable reaction that requires manganese and dioxygen. Previous studies have shown that replacing an active-site loop segment Ser¹⁶¹-Glu¹⁶²-Asn¹⁶³-Ser¹⁶⁴ in the N-terminal domain of OxDC with the cognate residues Asp¹⁶¹-Ala¹⁶²-Ser-¹⁶³-Asn¹⁶⁴ of an evolutionarily related, Mn-dependent oxalate oxidase gives a chimeric variant (DASN) that exhibits significantly increased oxidase activity. The mechanistic basis for this change in activity has now been investigated using membrane inlet mass spectrometry (MIMS) and isotope effect (IE) measurements. Quantitative analysis of the reaction stoichiometry as a function of oxalate concentration, as determined by MIMS, suggests that the increased oxidase activity of the DASN OxDC variant is associated with only a small fraction of the enzyme molecules in solution. In addition, IE measurements show that C–C bond cleavage in the DASN OxDC variant proceeds via the same mechanism as in the wild-type enzyme, even though the Glu¹⁶² side chain is absent. Thus, replacement of the loop residues does not modulate the chemistry of the enzyme-bound Mn(II) ion. Taken together, these results raise the possibility that the observed oxidase activity of the DASN OxDC variant arises from an increased level of access of the solvent to the active site during catalysis, implying that the functional role of Glu¹⁶² is to control loop conformation. A 2.6 Å resolution X-ray crystal structure of a complex between oxalate and the Co(II)-substituted ΔE162 OxDC variant, in which Glu¹⁶² has been deleted from the active site loop, reveals the likely mode by which the substrate coordinates the catalytically active Mn ion prior to C–C bond cleavage. The “end-on” conformation of oxalate observed in the structure is consistent with the previously published V/K IE data and provides an empty coordination site for the dioxygen ligand that is thought to mediate the formation of Mn(III) for catalysis upon substrate binding.

Design of Self-Assembling Protein-Polymer Conjugates

Protein-polymer conjugates are of particular interest for nanobiotechnology applications because of the various and complementary roles that each component may play in composite hybrid-materials. This chapter focuses on the design principles and applications of self-assembling protein-polymer conjugate materials. We address the general design methodology, from both synthetic and genetic perspective, conjugation strategies, protein vs. polymer driven self-assembly and finally, emerging applications for conjugate materials. By marrying proteins and polymers into conjugated bio-hybrid materials, materials scientists, chemists, and biologists alike, have at their fingertips a vast toolkit for material design. These inherently hierarchical structures give rise to useful patterning, mechanical and transport properties that may help realize new, more efficient materials for energy generation, catalysis, nanorobots, etc.

FunTree: advances in a resource for exploring and contextualising protein function evolution

FunTree is a resource that brings together protein sequence, structure and functional information, including overall chemical reaction and mechanistic data, for structurally defined domain superfamilies. Developed in tandem with the CATH database, the original FunTree contained just 276 superfamilies focused on enzymes. Here, we present an update of FunTree that has expanded to include 2340 superfamilies including both enzymes and proteins with non-enzymatic functions annotated by Gene Ontology (GO) terms. This allows the investigation of how novel functions have evolved within a structurally defined superfamily and provides a means to analyse trends across many superfamilies. This is done not only within the context of a protein's sequence and structure but also the relationships of their functions. New measures of functional similarity have been integrated, including for enzymes comparisons of overall reactions based on overall bond changes, reaction centres (the local environment atoms involved in the reaction) and the sub-structure similarities of the metabolites involved in the reaction and for non-enzymes semantic similarities based on the GO. To identify and highlight changes in function through evolution, ancestral character estimations are made and presented. All this is accessible through a new re-designed web interface that can be found at http://www.funtree.info.

Large-Scale Analysis Exploring Evolution of Catalytic Machineries and Mechanisms in Enzyme Superfamilies

Enzymes, as biological catalysts, form the basis of all forms of life. How these proteins have evolved their functions remains a fundamental question in biology. Over 100 years of detailed biochemistry studies, combined with the large volumes of sequence and protein structural data now available, means that we are able to perform large-scale analyses to address this question. Using a range of computational tools and resources, we have compiled information on all experimentally annotated changes in enzyme function within 379 structurally defined protein domain superfamilies, linking the changes observed in functions during evolution to changes in reaction chemistry. Many superfamilies show changes in function at some level, although one function often dominates one superfamily. We use quantitative measures of changes in reaction chemistry to reveal the various types of chemical changes occurring during evolution and to exemplify these by detailed examples. Additionally, we use structural information of the enzymes active site to examine how different superfamilies have changed their catalytic machinery during evolution. Some superfamilies have changed the reactions they perform without changing catalytic machinery. In others, large changes of enzyme function, in terms of both overall chemistry and substrate specificity, have been brought about by significant changes in catalytic machinery. Interestingly, in some superfamilies, relatives perform similar functions but with different catalytic machineries. This analysis highlights characteristics of functional evolution across a wide range of superfamilies, providing insights that will be useful in predicting the function of uncharacterised sequences and the design of new synthetic enzymes.

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Examining how enzyme function evolves using sequence, structure, and reaction mechanism data.

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Quantifying changes in reaction mechanisms reveals how function has diverged in many superfamilies.

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Homologous domains frequently use different catalytic residues, which sometimes perform the same enzyme chemistry.

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This large-scale analysis has significance in protein function prediction and enzyme design.

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.

The value of protein structure classification information-Surveying the scientific literature

The Structural Classification of Proteins (SCOP) and Class, Architecture, Topology, Homology (CATH) databases have been valuable resources for protein structure classification for over 20 years. Development of SCOP (version 1) concluded in June 2009 with SCOP 1.75. The SCOPe (SCOP-extended) database offers continued development of the classic SCOP hierarchy, adding over 33,000 structures. We have attempted to assess the impact of these two decade old resources and guide future development. To this end, we surveyed recent articles to learn how structure classification data are used. Of 571 articles published in 2012-2013 that cite SCOP, 439 actually use data from the resource. We found that the type of use was fairly evenly distributed among four top categories: A) study protein structure or evolution (27% of articles), B) train and/or benchmark algorithms (28% of articles), C) augment non-SCOP datasets with SCOP classification (21% of articles), and D) examine the classification of one protein/a small set of proteins (22% of articles). Most articles described computational research, although 11% described purely experimental research, and a further 9% included both. We examined how CATH and SCOP were used in 158 articles that cited both databases: while some studies used only one dataset, the majority used data from both resources. Protein structure classification remains highly relevant for a diverse range of problems and settings.

The history of the CATH structural classification of protein domains

This article presents a historical review of the protein structure classification database CATH. Together with the SCOP database, CATH remains comprehensive and reasonably up-to-date with the now more than 100,000 protein structures in the PDB. We review the expansion of the CATH and SCOP resources to capture predicted domain structures in the genome sequence data and to provide information on the likely functions of proteins mediated by their constituent domains. The establishment of comprehensive function annotation resources has also meant that domain families can be functionally annotated allowing insights into functional divergence and evolution within protein families.

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We present a historical review of the protein structure database CATH.

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We review the expansion of the CATH and SCOP resources with sequence data and functional annotations.

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How functional annotation resources allow insights into functional divergence and evolution within protein families.

The Origin and Evolution of Baeyer-Villiger Monooxygenases (BVMOs): An Ancestral Family of Flavin Monooxygenases

The Baeyer-Villiger Monooxygenases (BVMOs) are enzymes belonging to the "Class B" of flavin monooxygenases and are capable of performing exquisite selective oxidations. These enzymes have been studied from a biotechnological perspective, but their physiological substrates and functional roles are widely unknown. Here, we investigated the origin, taxonomic distribution and evolutionary history of the BVMO genes. By using in silico approaches, 98 BVMO encoding genes were detected in the three domains of life: Archaea, Bacteria and Eukarya. We found evidence for the presence of these genes in Metazoa (Hydra vulgaris, Oikopleura dioica and Adineta vaga) and Haptophyta (Emiliania huxleyi) for the first time. Furthermore, a search for other "Class B" monooxygenases (flavoprotein monooxygenases--FMOs--and N-hydroxylating monooxygenases--NMOs) was conducted. These sequences were also found in the three domains of life. Phylogenetic analyses of all "Class B" monooxygenases revealed that NMOs and BVMOs are monophyletic, whereas FMOs form a paraphyletic group. Based on these results, we propose that BVMO genes were already present in the last universal common ancestor (LUCA) and their current taxonomic distribution is the result of differential duplication and loss of paralogous genes.

Protein function from its emergence to diversity in contemporary proteins

The goal of this work is to learn from nature the rules that govern evolution and the design of protein function. The fundamental laws of physics lie in the foundation of the protein structure and all stages of the protein evolution, determining optimal sizes and shapes at different levels of structural hierarchy. We looked back into the very onset of the protein evolution with a goal to find elementary functions (EFs) that came from the prebiotic world and served as building blocks of the first enzymes. We defined the basic structural and functional units of biochemical reactions-elementary functional loops. The diversity of contemporary enzymes can be described via combinations of a limited number of elementary chemical reactions, many of which are performed by the descendants of primitive prebiotic peptides/proteins. By analyzing protein sequences we were able to identify EFs shared by seemingly unrelated protein superfamilies and folds and to unravel evolutionary relations between them. Binding and metabolic processing of the metal- and nucleotide-containing cofactors and ligands are among the most abundant ancient EFs that became indispensable in many natural enzymes. Highly designable folds provide structural scaffolds for many different biochemical reactions. We show that contemporary proteins are built from a limited number of EFs, making their analysis instrumental for establishing the rules for protein design. Evolutionary studies help us to accumulate the library of essential EFs and to establish intricate relations between different folds and functional superfamilies. Generalized sequence-structure descriptors of the EF will become useful in future design and engineering of desired enzymatic functions.