Evolutionary potential of (beta/alpha)8-barrels: functional promiscuity produced by single substitutions in the enolase superfamily

Retracing the Rapid Evolution of an Herbicide-Degrading Enzyme by Protein Engineering

The mechanisms underlying the rapid evolution of novel enzymatic activities from promiscuous side activities are poorly understood. Recently emerged enzymes catalyzing the catabolic degradation of xenobiotic substances that have been spread out into the environment during the last decades provide an exquisite opportunity to study these mechanisms. A prominent example is the herbicide atrazine (2-chloro-4-ethylamino-6-isopropylamino-1,3,5-triazine), which is degraded through a number of enzymatic reactions constituting the Atz pathway. Here, we analyzed the evolution of the hydroxyatrazine ethylaminohydrolase AtzB, a Zn(II)-dependent metalloenzyme that adopts the amidohydrolase fold and catalyzes the second step of the Atz pathway. We searched for promiscuous side activities of AtzB, which might point to the identity of its progenitor. These investigations revealed that AtzB has low promiscuous guanine deaminase activity. Furthermore, we found that the two closest AtzB homologues, which have not been functionally annotated up to now, are guanine deaminases with modest promiscuous hydroxyatrazine hydrolase activity. Based on sequence comparisons with the closest AtzB homologues, the guanine deaminase activity of AtzB could be increased by three orders of magnitude through the introduction of only four active site mutations. Interestingly, introducing the inverse four mutations into the AtzB homologues significantly enhanced their hydroxyatrazine hydrolase activity, and in one case is even equivalent to that of wild-type AtzB. Molecular dynamics simulations elucidated the structural and molecular basis for the mutation-induced activity changes. The example of AtzB highlights how novel enzymes with high catalytic proficiency can evolve from low promiscuous side activities by only few mutational events within a short period of time.

Paracatalytic induction: Subverting specificity in hedgehog protein autoprocessing with small molecules

Paracatalytic inducers are antagonists that shift the specificity of biological catalysts, resulting in non-native transformations. In this Chapter we describe methods to discover paracatalytic inducers of Hedgehog (Hh) protein autoprocessing. Native autoprocessing uses cholesterol as a substrate nucleophile to assist in cleaving an internal peptide bond within a precursor form of Hh. This unusual reaction is brought about by HhC, an enzymatic domain that resides within the C-terminal region of Hh precursor proteins. Recently, we reported paracatalytic inducers as a novel class of Hh autoprocessing antagonists. These small molecules bind HhC and tilt the substrate specificity away from cholesterol in favor of solvent water. The resulting cholesterol-independent autoproteolysis of the Hh precursor generates a non-native Hh side product with substantially reduced biological signaling activity. Protocols are provided for in vitro FRET-based and in-cell bioluminescence assays to discover and characterize paracatalytic inducers of Drosophila and human hedgehog protein autoprocessing, respectively.

How to Recruit a Promiscuous Enzyme to Serve a New Function

Promiscuous enzymes can be recruited to serve new functions when a genetic or environmental change makes catalysis of a novel reaction important for fitness or even survival. Subsequently, gene duplication and divergence can lead to evolution of an efficient and specialized new enzyme. Every organism likely has thousands of promiscuous enzyme activities that provide a vast reservoir of catalytic potential. However, much of this potential may not be accessible. We compiled kinetic parameters for promiscuous reactions catalyzed by 108 enzymes. The median value of k_cat/K_M is a very modest 31 M^-1 s^-1. Based upon the fluxes through metabolic pathways in E. coli, we estimate that many, if not most, promiscuous activities are too inefficient to impact fitness. However, mutations can elevate the level of an insufficient promiscuous activity by increasing enzyme expression, improving k_cat/K_M, or altering concentrations of the promiscuous and native substrates and allosteric regulators. Particularly in large bacterial populations, stochastic mutations may provide a viable pathway for recruitment of even inefficient promiscuous activities.

Combined MD and QM/MM Calculations Reveal Allostery-Driven Promiscuity in Dipeptide Epimerases of Enolase Family

The adaptability of the active site to amplify the secondary function is supposed to be the fundamental cause of the promiscuity and the evolution of new functions in enzymes. In most cases, mutations occur close to the active site and/or in the catalytic site to change the active site plasticity to accommodate the non-native substrate. In the present study, using MD simulations and hybrid QM/MM calculations, we have shown a way to enhance the promiscuity, i. e., the allostery-driven promiscuity. Using a case study of the AEE enzyme where the capping loop recognizes the substrate, herein, we show that a single site mutation (D321G) far from the capping loop can induce a large conformational change in the capping loop to recognize different substrates for different functions. The QM/MM calculations for the WT and mutated enzyme provide a first validation of the mechanism of 1,1-proton transfer and dehydration by the AEE enzyme. Since AEE epimerase possesses a highly conserved TIM-barrel fold, we believe that our study provides a crucial lead to understanding the mechanism of emergence of secondary function which can be useful to repurpose ancient enzymes for modern usage.

The Birth of Genomic Enzymology: Discovery of the Mechanistically Diverse Enolase Superfamily

Enzymes are categorized into superfamilies by sequence, structural, and mechanistic similarities. The evolutionary implications can be profound. Until the mid-1990s, the approach was fragmented largely due to limited sequence and structural data. However, in 1996, Babbitt et al. published a paper in Biochemistry that demonstrated the potential power of mechanistically diverse superfamilies to identify common ancestry, predict function, and, in some cases, predict specificity. This Perspective describes the findings of the original work and reviews the current understanding of structure and mechanism in the founding family members. The outcomes of the genomic enzymology approach have reached far beyond the functional assignment of members of the enolase superfamily, inspiring the study of superfamilies and the adoption of sequence similarity networks and genome context and yielding fundamental insights into enzyme evolution.

The N-Acetyl Amino Acid Racemases (NAAARs); Native and evolved biocatalysts applied to the synthesis of canonical and non-canonical amino acids

Amino acids are one of the most important synthons employed in the biotechnology, pharmaceutical and agrochemical industries for the preparation of active agents. Recently, the emerging use of these compounds as tools for protein engineering, has also been reported. Numerous chemo- and biocatalytic strategies have been developed for the stereoselective synthesis of these compounds. One of the most efficient processes is the enzymatic dynamic kinetic resolution of N-acylated derivatives, where an N-acyl amino acid racemase (NAAAR) is coupled with an enantioselective, hydrolytic enzyme (aminoacylase), and used to convert a racemic mixture of starting materials to enantiopure products. Here we provide a brief overview of the structure and mechanism of NAAAR. We will also review the applications of this class of biocatalyst, as well as discussing the various strategies employed to obtain an efficient system for the synthesis of optically pure canonical and non-canonical amino acids.

Evolution of new enzymes by gene duplication and divergence

Thousands of new metabolic and regulatory enzymes have evolved by gene duplication and divergence since the dawn of life. New enzyme activities often originate from promiscuous secondary activities that have become important for fitness due to a change in the environment or a mutation. Mutations that make a promiscuous activity physiologically relevant can occur in the gene encoding the promiscuous enzyme itself, but can also occur elsewhere, resulting in increased expression of the enzyme or decreased competition between the native and novel substrates for the active site. If a newly useful activity is inefficient, gene duplication/amplification will set the stage for divergence of a new enzyme. Even a few mutations can increase the efficiency of a new activity by orders of magnitude. As efficiency increases, amplified gene arrays will shrink to provide two alleles, one encoding the original enzyme and one encoding the new enzyme. Ultimately, genomic rearrangements eliminate co-amplified genes and move newly evolved paralogs to a distant region of the genome.

Integrated structural and evolutionary analysis reveals common mechanisms underlying adaptive evolution in mammals

Understanding the molecular basis of adaptation to the environment is a central question in evolutionary biology, yet linking detected signatures of positive selection to molecular mechanisms remains challenging. Here we demonstrate that combining sequence-based phylogenetic methods with structural information assists in making such mechanistic interpretations on a genomic scale. Our integrative analysis shows that positively selected sites tend to colocalize on protein structures and that positively selected clusters are found in functionally important regions of proteins, indicating that positive selection can contravene the well-known principle of evolutionary conservation of functionally important regions. This unexpected finding, along with our discovery that positive selection acts on structural clusters, opens previously unexplored strategies for the development of better models of protein evolution. Remarkably, proteins where we detect the strongest evidence of clustering belong to just two functional groups: Components of immune response and metabolic enzymes. This gives a coherent picture of pathogens and xenobiotics as important drivers of adaptive evolution of mammals.

A strategy for large-scale comparison of evolutionary- and reaction-based classifications of enzyme function

Determining the molecular function of enzymes discovered by genome sequencing represents a primary foundation for understanding many aspects of biology. Historically, classification of enzyme reactions has used the enzyme nomenclature system developed to describe the overall reactions performed by biochemically characterized enzymes, irrespective of their associated sequences. In contrast, functional classification and assignment for the millions of protein sequences of unknown function now available is largely done in two computational steps, first by similarity-based assignment of newly obtained sequences to homologous groups, followed by transferring to them the known functions of similar biochemically characterized homologs. Due to the fundamental differences in their etiologies and practice, `how' these chemistry- and evolution-centric functional classification systems relate to each other has been difficult to explore on a large scale. To investigate this issue in a new way, we integrated two published ontologies that had previously described each of these classification systems independently. The resulting infrastructure was then used to compare the functional assignments obtained from each classification system for the well-studied and functionally diverse enolase superfamily. Mapping these function assignments to protein structure and reaction similarity networks shows a profound and complex disconnect between the homology- and chemistry-based classification systems. This conclusion mirrors previous observations suggesting that except for closely related sequences, facile annotation transfer from small numbers of characterized enzymes to the huge number uncharacterized homologs to which they are related is problematic. Our extension of these comparisons to large enzyme superfamilies in a computationally intelligent manner provides a foundation for new directions in protein function prediction for the huge proportion of sequences of unknown function represented in major databases. Interactive sequence, reaction, substrate and product similarity networks computed for this work for the enolase and two other superfamilies are freely available for download from the Structure Function Linkage Database Archive (http://sfld.rbvi.ucsf.edu).

Exploring the sequence, function, and evolutionary space of protein superfamilies using sequence similarity networks and phylogenetic reconstructions

Integrative computational methods can facilitate the discovery of new protein functions and enzymatic reactions by enabling the observation and investigation of complex sequence-structure-function and evolutionary relationships within protein superfamilies. Here, we highlight the use of sequence similarity networks (SSNs) and phylogenetic reconstructions to map the functional divergence and evolutionary history of protein superfamilies. We exemplify this approach using the nitroreductase (NTR) flavoenzyme superfamily, demonstrating that SSN investigations can provide a rapid and effective means to classify groups of proteins, expose sequence similarity relationships across the global scale of a protein superfamily, and efficiently support detailed phylogenetic analyses. Integration of such approaches with systematic experimental characterization will expand our understanding of the functional diversity of enzymes, their evolution, and their associated physiological roles.

New imine-reducing enzymes from β-hydroxyacid dehydrogenases by single amino acid substitutions

We report the exploration of the evolutionary relationship between imine reductases (IREDs) and other dehydrogenases. This approach is informed by the sequence similarity between these enzyme families and the recently described promiscuous activity of IREDs for the highly reactive carbonyl compound 2,2,2-trifluoroacetophenone. Using the structure of the R-selective IRED from Streptosporangium roseum (R-IRED-Sr) as a model, β-hydroxyacid dehydrogenases (βHADs) were identified as the dehydrogenases most similar to IREDs. To understand how active site differences in IREDs and βHADs enable the reduction of predominantly C = N or C = O bonds respectively, we substituted amino acid residues in βHADs with the corresponding residues from the R-IRED-Sr and were able to increase the promiscuous activity of βHADs for C = N functions by a single amino acid substitution. Variants βHADAt_K170D and βHADAt_K170F lost mainly their keto acid reduction activity and gained the ability to catalyze the reduction of imines. Moreover, the product enantiomeric purity for a bulky imine substrate could be increased from 23% ee (R-IRED-Sr) to 97% ee (βHADAt_K170D/F_F231A) outcompeting already described IRED selectivity.

Revealing Unexplored Sequence-Function Space Using Sequence Similarity Networks

The rapidly expanding number of protein sequences found in public databases can improve our understanding of how protein functions evolve. However, our current knowledge of protein function likely represents a small fraction of the diverse repertoire that exists in nature. Integrative computational methods can facilitate the discovery of new protein functions and enzymatic reactions through the observation and investigation of the complex sequence-structure-function relationships within protein superfamilies. Here, we highlight the use of sequence similarity networks (SSNs) to identify previously unexplored sequence and function space. We exemplify this approach using the nitroreductase (NTR) superfamily. We demonstrate that SSN investigations can provide a rapid and effective means to classify groups of proteins, therefore exposing experimentally unexplored sequences that may exhibit novel functionality. Integration of such approaches with systematic experimental characterization will expand our understanding of the functional diversity of enzymes and their associated physiological roles.

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.

On the networked architecture of genotype spaces and its critical effects on molecular evolution

Evolutionary dynamics is often viewed as a subtle process of change accumulation that causes a divergence among organisms and their genomes. However, this interpretation is an inheritance of a gradualistic view that has been challenged at the macroevolutionary, ecological and molecular level. Actually, when the complex architecture of genotype spaces is taken into account, the evolutionary dynamics of molecular populations becomes intrinsically non-uniform, sharing deep qualitative and quantitative similarities with slowly driven physical systems: nonlinear responses analogous to critical transitions, sudden state changes or hysteresis, among others. Furthermore, the phenotypic plasticity inherent to genotypes transforms classical fitness landscapes into multiscapes where adaptation in response to an environmental change may be very fast. The quantitative nature of adaptive molecular processes is deeply dependent on a network-of-networks multilayered structure of the map from genotype to function that we begin to unveil.

Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence-Function Space and Genome Context to Discover Novel Functions

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of “genomic enzymology” web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence–function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems.

Site-Directed Chemical Mutations on Abzymes: Large Rate Accelerations in the Catalysis by Exchanging the Functionalized Small Nonprotein Components

Taking advantage of antibody molecules to generate tailor-made binding sites, we propose a new class of protein modifications, termed as "site-directed chemical mutation." In this modification, chemically synthesized catalytic components with a variety of steric and electronic properties can be noncovalently and nongenetically incorporated into specific sites in antibody molecules to induce enzymatic activity. Two catalytic antibodies, 25E2 and 27C1, possess antigen-combining sites which bind catalytic components and act as apoproteins in catalytic reactions. By simply exchanging these components, antibodies 25E2 and 27C1 can catalyze a wide range of chemical transformations including acyl-transfer, β-elimination, aldol, and decarboxylation reactions. Although both antibodies were generated with the same hapten, phosphonate diester 1, they showed different catalytic activity. When phenylacetic acid 4 was used as the catalytic component, 25E2 efficiently catalyzed the elimination reaction of β-haloketone 2, whereas 27C1 showed no catalytic activity. In this work, we focused on the β-elimination reaction and examined the site-directed chemical mutation of 27C1 to induce activity and elucidate the catalytic mechanism. Molecular models showed that the cationic guanidyl group of Arg^H52 in 27C1 makes a hydrogen bond with the P═O oxygen in the hapten. This suggested that during β-elimination, Arg^H52 of 27C1 would form a salt bridge with the carboxylate of 4, thus destroying reactivity. Therefore, we utilized site-directed chemical mutation to change the charge properties of the catalytic components. When amine components 7-10 were used, 27C1 efficiently catalyzed the β-elimination reaction. It is noteworthy that chemical mutation with secondary amine 8 provided extremely high activity, with a rate acceleration [(k_cat/K_m 2)/k_uncat] of 1 000 000. This catalytic activity likely arises from the proximity effect, plus general-base catalysis associated the electrostatic interactions. In 27C1, the cationic guanidyl group of Arg^H52 is spatially close to the nitrogen of the amine components. In this microenvironment, the intrinsic pK_a of the amine is perturbed and shifts to a lower pK_a, which efficiently abstracts the α-proton during the reaction. This mechanism is consistent with the observed kinetic isotope effect (E2 or E1cB mechanism). Thus, site-directed chemical mutation provides a better understanding of enzyme functions and opens new avenues in biocatalyst research.

Mutations Closer to the Active Site Improve the Promiscuous Aldolase Activity of 4-Oxalocrotonate Tautomerase More Effectively than Distant Mutations

The enzyme 4-oxalocrotonate tautomerase (4-OT), which catalyzes enol-keto tautomerization as part of a degradative pathway for aromatic hydrocarbons, promiscuously catalyzes various carbon-carbon bond-forming reactions. These include the aldol condensation of acetaldehyde with benzaldehyde to yield cinnamaldehyde. Here, we demonstrate that 4-OT can be engineered into a more efficient aldolase for this condensation reaction, with a >5000-fold improvement in catalytic efficiency (kcat /Km ) and a >10(7) -fold change in reaction specificity, by exploring small libraries in which only "hotspots" are varied. The hotspots were identified by systematic mutagenesis (covering each residue), followed by a screen for single mutations that give a strong improvement in the desired aldolase activity. All beneficial mutations were near the active site of 4-OT, thus underpinning the notion that new catalytic activities of a promiscuous enzyme are more effectively enhanced by mutations close to the active site.

AAV ancestral reconstruction library enables selection of broadly infectious viral variants

Adeno-associated virus (AAV) vectors have achieved clinical efficacy in treating several diseases. However, enhanced vectors are required to extend these landmark successes to other indications and protein engineering approaches may provide the necessary vector improvements to address such unmet medical needs. To generate new capsid variants with potentially enhanced infectious properties and to gain insights into AAV's evolutionary history, we computationally designed and experimentally constructed a putative ancestral AAV library. Combinatorial variations at 32 amino acid sites were introduced to account for uncertainty in their identities. We then analyzed the evolutionary flexibility of these residues, the majority of which have not been previously studied, by subjecting the library to iterative selection on a representative cell line panel. The resulting variants exhibited transduction efficiencies comparable to the most efficient extant serotypes and, in general, ancestral libraries were broadly infectious across the cell line panel, indicating that they favored promiscuity over specificity. Interestingly, putative ancestral AAVs were more thermostable than modern serotypes and did not use sialic acids, galactose or heparan sulfate proteoglycans for cellular entry. Finally, variants mediated 19- to 31-fold higher gene expression in the muscle compared with AAV1, a clinically used serotype for muscle delivery, highlighting their promise for gene therapy.

A Single Enzyme Transforms a Carboxylic Acid into a Nitrile through an Amide Intermediate

The biosynthesis of nitriles is known to occur through specialized pathways involving multiple enzymes; however, in bacterial and archeal biosynthesis of 7-deazapurines, a single enzyme, ToyM, catalyzes the conversion of the carboxylic acid containing 7-carboxy-7-deazaguanine (CDG) into its corresponding nitrile, 7-cyano-7-deazaguanine (preQ0 ). The mechanism of this unusual direct transformation was shown to proceed via the adenylation of CDG, which activates it to form the newly discovered amide intermediate 7-amido-7-deazaguanine (ADG). This is subsequently dehydrated to form the nitrile in a process that consumes a second equivalent of ATP. The authentic amide intermediate is shown to be chemically and kinetically competent. The ability of ToyM to activate two different substrates, an acid and an amide, accounts for this unprecedented one-enzyme catalysis of nitrile synthesis, and the differential rates of these two half reactions suggest that this catalytic ability is derived from an amide synthetase that gained a new function.

Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST): A web tool for generating protein sequence similarity networks

The Enzyme Function Initiative, an NIH/NIGMS-supported Large-Scale Collaborative Project (EFI; U54GM093342; http://enzymefunction.org/), is focused on devising and disseminating bioinformatics and computational tools as well as experimental strategies for the prediction and assignment of functions (in vitro activities and in vivo physiological/metabolic roles) to uncharacterized enzymes discovered in genome projects. Protein sequence similarity networks (SSNs) are visually powerful tools for analyzing sequence relationships in protein families (H.J. Atkinson, J.H. Morris, T.E. Ferrin, and P.C. Babbitt, PLoS One 2009, 4, e4345). However, the members of the biological/biomedical community have not had access to the capability to generate SSNs for their "favorite" protein families. In this article we announce the EFI-EST (Enzyme Function Initiative-Enzyme Similarity Tool) web tool (http://efi.igb.illinois.edu/efi-est/) that is available without cost for the automated generation of SSNs by the community. The tool can create SSNs for the "closest neighbors" of a user-supplied protein sequence from the UniProt database (Option A) or of members of any user-supplied Pfam and/or InterPro family (Option B). We provide an introduction to SSNs, a description of EFI-EST, and a demonstration of the use of EFI-EST to explore sequence-function space in the OMP decarboxylase superfamily (PF00215). This article is designed as a tutorial that will allow members of the community to use the EFI-EST web tool for exploring sequence/function space in protein families.

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the 'search space' of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the 'best' amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.

Prediction of substrate specificity and preliminary kinetic characterization of the hypothetical protein PVX_123945 from Plasmodium vivax

Members of the haloacid dehalogenase (HAD) superfamily are emerging as an important group of enzymes by virtue of their role in diverse chemical reactions. In different Plasmodium species their number varies from 16 to 21. One of the HAD superfamily members, PVX_123945, a hypothetical protein from Plasmodium vivax, was selected for examining its substrate specificity. Based on distant homology searches and structure comparisons, it was predicted to be a phosphatase. Thirty-eight metabolites were screened to identify potential substrates. Further, to validate the prediction, biochemical and kinetic studies were carried out that showed that the protein was a monomer with high catalytic efficiency for β-glycerophosphate followed by pyridoxal 5'-phosphate. The enzyme also exhibited moderate catalytic efficiencies for α-glycerophosphate, xanthosine 5'-monophosphate and adenosine 5'-monophosphate. It also hydrolyzed the artificial substrate p-nitrophenyl phosphate (pNPP). Mg(2+) was the most preferred divalent cation and phosphate inhibited the enzyme activity. The study is the first attempt at understanding the substrate specificity of a hypothetical protein belonging to HAD superfamily from the malarial parasite P. vivax.

New insights about enzyme evolution from large scale studies of sequence and structure relationships

Understanding how enzymes have evolved offers clues about their structure-function relationships and mechanisms. Here, we describe evolution of functionally diverse enzyme superfamilies, each representing a large set of sequences that evolved from a common ancestor and that retain conserved features of their structures and active sites. Using several examples, we describe the different structural strategies nature has used to evolve new reaction and substrate specificities in each unique superfamily. The results provide insight about enzyme evolution that is not easily obtained from studies of one or only a few enzymes.

Rapid kinetic characterization of glycosyl hydrolases based on oxime derivatization and nanostructure-initiator mass spectrometry (NIMS)

Glycoside hydrolases (GHs) are critical to cycling of plant biomass in the environment, digestion of complex polysaccharides by the human gut microbiome, and industrial activities such as deployment of cellulosic biofuels. High-throughput sequencing methods show tremendous sequence diversity among GHs, yet relatively few examples from the over 150,000 unique domain arrangements containing GHs have been functionally characterized. Here, we show how cell-free expression, bioconjugate chemistry, and surface-based mass spectrometry can be used to study glycoside hydrolase reactions with plant biomass. Detection of soluble products is achieved by coupling a unique chemical probe to the reducing end of oligosaccharides in a stable oxime linkage, while the use of (13)C-labeled monosaccharide standards (xylose and glucose) allows quantitation of the derivatized glycans. We apply this oxime-based nanostructure-initiator mass spectrometry (NIMS) method to characterize the functional diversity of GHs secreted by Clostridium thermocellum, a model cellulolytic organism. New reaction specificities are identified, and differences in rates and yields of individual enzymes are demonstrated in reactions with biomass substrates. Numerical analyses of time series data suggests that synergistic combinations of mono- and multifunctional GHs can decrease the complexity of enzymes needed for the hydrolysis of plant biomass during the production of biofuels.

Connectivity between catalytic landscapes of the metallo-β-lactamase superfamily

The expansion of functions in an enzyme superfamily is thought to occur through recruitment of latent promiscuous functions within existing enzymes. Thus, the promiscuous activities of enzymes represent connections between different catalytic landscapes and provide an additional layer of evolutionary connectivity between functional families alongside their sequence and structural relationships. Functional connectivity has been observed between individual functional families; however, little is known about how catalytic landscapes are connected throughout a highly diverged superfamily. Here, we describe a superfamily-wide analysis of evolutionary and functional connectivity in the metallo-β-lactamase (MBL) superfamily. We investigated evolutionary connections between functional families and related evolutionary to functional connectivity; 24 enzymes from 15 distinct functional families were challenged against 10 catalytically distinct reactions. We revealed that enzymes of this superfamily are generally promiscuous, as each enzyme catalyzes on average 1.5 reactions in addition to its native one. Catalytic landscapes in the MBL superfamily overlap substantially; each reaction is connected on average to 3.7 other reactions whereas some connections appear to be unrelated to recent evolutionary events and occur between chemically distinct reactions. These findings support the idea that the highly distinct reactions in the MBL superfamily could have evolved from a common ancestor traversing a continuous network via promiscuous enzymes. Several functional connections (e.g., the lactonase/phosphotriesterase and phosphonatase/phosphodiesterase/arylsulfatase reactions) are also observed in structurally and evolutionary distinct superfamilies, suggesting that these catalytic landscapes are substantially connected. Our results show that new enzymatic functions could evolve rapidly from the current diversity of enzymes and range of promiscuous activities.

Improvement of biocatalysts for industrial and environmental purposes by saturation mutagenesis

Laboratory evolution techniques are becoming increasingly widespread among protein engineers for the development of novel and designed biocatalysts. The palette of different approaches ranges from complete randomized strategies to rational and structure-guided mutagenesis, with a wide variety of costs, impacts, drawbacks and relevance to biotechnology. A technique that convincingly compromises the extremes of fully randomized vs. rational mutagenesis, with a high benefit/cost ratio, is saturation mutagenesis. Here we will present and discuss this approach in its many facets, also tackling the issue of randomization, statistical evaluation of library completeness and throughput efficiency of screening methods. Successful recent applications covering different classes of enzymes will be presented referring to the literature and to research lines pursued in our group. The focus is put on saturation mutagenesis as a tool for designing novel biocatalysts specifically relevant to production of fine chemicals for improving bulk enzymes for industry and engineering technical enzymes involved in treatment of waste, detoxification and production of clean energy from renewable sources.

Protein design in systems metabolic engineering for industrial strain development

Accelerating the process of industrial bacterial host strain development, aimed at increasing productivity, generating new bio-products or utilizing alternative feedstocks, requires the integration of complementary approaches to manipulate cellular metabolism and regulatory networks. Systems metabolic engineering extends the concept of classical metabolic engineering to the systems level by incorporating the techniques used in systems biology and synthetic biology, and offers a framework for the development of the next generation of industrial strains. As one of the most useful tools of systems metabolic engineering, protein design allows us to design and optimize cellular metabolism at a molecular level. Here, we review the current strategies of protein design for engineering cellular synthetic pathways, metabolic control systems and signaling pathways, and highlight the challenges of this subfield within the context of systems metabolic engineering.

Computational enzyme design

Recent developments in computational chemistry and biology have come together in the "inside-out" approach to enzyme engineering. Proteins have been designed to catalyze reactions not previously accelerated in nature. Some of these proteins fold and act as catalysts, but the success rate is still low. The achievements and limitations of the current technology are highlighted and contrasted to other protein engineering techniques. On its own, computational "inside-out" design can lead to the production of catalytically active and selective proteins, but their kinetic performances fall short of natural enzymes. When combined with directed evolution, molecular dynamics simulations, and crowd-sourced structure-prediction approaches, however, computational designs can be significantly improved in terms of binding, turnover, and thermal stability.

Fundamental challenges in mechanistic enzymology: progress toward understanding the rate enhancements of enzymes

Enzymes are remarkable catalysts that lie at the heart of biology, accelerating chemical reactions to an astounding extent with extraordinary specificity. Enormous progress in understanding the chemical basis of enzymatic transformations and the basic mechanisms underlying rate enhancements over the past decades is apparent. Nevertheless, it has been difficult to achieve a quantitative understanding of how the underlying mechanisms account for the energetics of catalysis, because of the complexity of enzyme systems and the absence of underlying energetic additivity. We review case studies from our own work that illustrate the power of precisely defined and clearly articulated questions when dealing with such complex and multifaceted systems, and we also use this approach to evaluate our current ability to design enzymes. We close by highlighting a series of questions that help frame some of what remains to be understood, and we encourage the reader to define additional questions and directions that will deepen and broaden our understanding of enzymes and their catalysis.

Substrate ambiguity among the nudix hydrolases: biologically significant, evolutionary remnant, or both?

Many members of the nudix hydrolase family exhibit considerable substrate multispecificity and ambiguity, which raises significant issues when assessing their functions in vivo and gives rise to errors in database annotation. Several display low antimutator activity when expressed in bacterial tester strains as well as some degree of activity in vitro towards mutagenic, oxidized nucleotides such as 8-oxo-dGTP. However, many of these show greater activity towards other nucleotides such as ADP-ribose or diadenosine tetraphosphate (Ap(4)A). The antimutator activities have tended to gain prominence in the literature, whereas they may in fact represent the residual activity of an ancestral antimutator enzyme that has become secondary to the more recently evolved major activity after gene duplication. Whether any meaningful antimutagenic function has also been retained in vivo requires very careful assessment. Then again, other examples of substrate ambiguity may indicate as yet unexplored regulatory systems. For example, bacterial Ap(4)A hydrolases also efficiently remove pyrophosphate from the 5' termini of mRNAs, suggesting a potential role for Ap(4)A in the control of bacterial mRNA turnover, while the ability of some eukaryotic mRNA decapping enzymes to degrade IDP and dIDP or diphosphoinositol polyphosphates (DIPs) may also be indicative of new regulatory networks in RNA metabolism. DIP phosphohydrolases also degrade diadenosine polyphosphates and inorganic polyphosphates, suggesting further avenues for investigation. This article uses these and other examples to highlight the need for a greater awareness of the possible significance of substrate ambiguity among the nudix hydrolases as well as the need to exert caution when interpreting incomplete analyses.

Mechanistic diversity in the RuBisCO superfamily: RuBisCO from Rhodospirillum rubrum is not promiscuous for reactions catalyzed by RuBisCO-like proteins

d-Ribulose 1,5-bisphosphate carboxylase/oxygenases (RuBisCOs) are promiscuous, catalyzing not only carboxylation and oxygenation of d-ribulose 1,5-bisphosphate but also other promiscuous, presumably nonphysiological, reactions initiated by abstraction of the 3-proton of d-ribulose 1,5-bisphosphate. Also, RuBisCO has homologues that do not catalyze carboxylation; these are designated RuBisCO-like proteins or RLPs. Members of the two families of RLPs catalyze reactions in the recycling of 5'-methylthioadenosine (MTA) generated by polyamine synthesis: (1) the 2,3-diketo-5-methylthiopentane 1-phosphate (DK-MTP 1-P) "enolase" reaction in the well-known "methionine salvage" pathway in Bacillus sp. and (2) the 5-methylthio-d-ribulose 1-phosphate (MTRu 1-P) 1,3-isomerase reaction in the recently discovered "MTA-isoprenoid shunt" that generates 1-deoxy-d-xylulose 5-phosphate for nonmevalonate isoprene synthesis in Rhodospirillum rubrum. We first studied the structure and reactivity of DK-MTP 1-P that was reported to decompose rapidly [Ashida, H., Saito, Y., Kojima, C., and Yokota, A. (2008) Biosci., Biotechnol., Biochem. 72, 959-967]. The 2-carbonyl group of DK-MTP 1-P is rapidly hydrated and can undergo enolization both nonenzymatically and enzymatically via the small amount of unhydrated material that is present. We then examined the ability of RuBisCO from R. rubrum to catalyze both of the RLP-catalyzed reactions. Contrary to a previous report [Ashida, H., Saito, Y., Kojima, C., Kobayashi, K., Ogasawara, N., and Yokota, A. (2003) Science 302, 286-290], we were unable to confirm that this RuBisCO catalyzes the DK-MTP 1-P "enolase" reaction either in vitro or in vivo. We also determined that this RuBisCO does not catalyze the MTRu 1-P 1,3-isomerase reaction in vitro. Thus, although RuBisCOs can be functionally promiscuous, RuBisCO from R. rubrum is not promiscuous for either of the known RLP-catalyzed reactions.

SABER: a computational method for identifying active sites for new reactions

A software suite, SABER (Selection of Active/Binding sites for Enzyme Redesign), has been developed for the analysis of atomic geometries in protein structures, using a geometric hashing algorithm (Barker and Thornton, Bioinformatics 2003;19:1644-1649). SABER is used to explore the Protein Data Bank (PDB) to locate proteins with a specific 3D arrangement of catalytic groups to identify active sites that might be redesigned to catalyze new reactions. As a proof-of-principle test, SABER was used to identify enzymes that have the same catalytic group arrangement present in o-succinyl benzoate synthase (OSBS). Among the highest-scoring scaffolds identified by the SABER search for enzymes with the same catalytic group arrangement as OSBS were L-Ala D/L-Glu epimerase (AEE) and muconate lactonizing enzyme II (MLE), both of which have been redesigned to become effective OSBS catalysts, demonstrated by experiments. Next, we used SABER to search for naturally existing active sites in the PDB with catalytic groups similar to those present in the designed Kemp elimination enzyme KE07. From over 2000 geometric matches to the KE07 active site, SABER identified 23 matches that corresponded to residues from known active sites. The best of these matches, with a 0.28 Å catalytic atom RMSD to KE07, was then redesigned to be compatible with the Kemp elimination using RosettaDesign. We also used SABER to search for potential Kemp eliminases using a theozyme predicted to provide a greater rate acceleration than the active site of KE07, and used Rosetta to create a design based on the proteins identified.

Efficient, crosswise catalytic promiscuity among enzymes that catalyze phosphoryl transfer

The observation that one enzyme can accelerate several chemically distinct reactions was at one time surprising because the enormous efficiency of catalysis was often seen as inextricably linked to specialization for one reaction. Originally underreported, and considered a quirk rather than a fundamental property, enzyme promiscuity is now understood to be important as a springboard for adaptive evolution. Owing to the large number of promiscuous enzymes that have been identified over the last decade, and the increased appreciation for promiscuity's evolutionary importance, the focus of research has shifted to developing a better understanding of the mechanistic basis for promiscuity and the origins of tolerant or restrictive specificity. We review the evidence for widespread crosswise promiscuity amongst enzymes that catalyze phosphoryl transfer, including several members of the alkaline phosphatase superfamily, where large rate accelerations between 10(6) and 10(17) are observed for both native and multiple promiscuous reactions. This article is part of a Special Issue entitled: Chemistry and mechanism of phosphatases, diesterases and triesterases.

Residues required for activity in Escherichia coli o-succinylbenzoate synthase (OSBS) are not conserved in all OSBS enzymes

Understanding how enzyme specificity evolves will provide guiding principles for protein engineering and function prediction. The o-succinylbenzoate synthase (OSBS) family is an excellent model system for elucidating these principles because it has many highly divergent amino acid sequences that are <20% identical, and some members have evolved a second function. The OSBS family belongs to the enolase superfamily, members of which use a set of conserved residues to catalyze a wide variety of reactions. These residues are the only conserved residues in the OSBS family, so they are not sufficient to determine reaction specificity. Some enzymes in the OSBS family catalyze another reaction, N-succinylamino acid racemization (NSAR). NSARs cannot be segregated into a separate family because their sequences are highly similar to those of known OSBSs, and many of them have both OSBS and NSAR activities. To determine how such divergent enzymes can catalyze the same reaction and how NSAR activity evolved, we divided the OSBS family into subfamilies and compared the divergence of their active site residues. Correlating sequence conservation with the effects of mutations in Escherichia coli OSBS identified two nonconserved residues (R159 and G288) at which mutations decrease efficiency ≥200-fold. These residues are not conserved in the subfamily that includes NSAR enzymes. The OSBS/NSAR subfamily binds the substrate in a different orientation, eliminating selective pressure to retain arginine and glycine at these positions. This supports the hypothesis that specificity-determining residues have diverged in the OSBS family and provides insight into the sequence changes required for the evolution of NSAR activity.

The use of evolutionary patterns in protein annotation

With genomic data skyrocketing, their biological interpretation remains a serious challenge. Diverse computational methods address this problem by pointing to the existence of recurrent patterns among sequence, structure, and function. These patterns emerge naturally from evolutionary variation, natural selection, and divergence--the defining features of biological systems--and they identify molecular events and shapes that underlie specificity of function and allosteric communication. Here we review these methods, and the patterns they identify in case studies and in proteome-wide applications, to infer and rationally redesign function.

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

In order to understand the evolution of enzyme reactions and to gain an overview of biological catalysis we have combined sequence and structural data to generate phylogenetic trees in an analysis of 276 structurally defined enzyme superfamilies, and used these to study how enzyme functions have evolved. We describe in detail the analysis of two superfamilies to illustrate different paradigms of enzyme evolution. Gathering together data from all the superfamilies supports and develops the observation that they have all evolved to act on a diverse set of substrates, whilst the evolution of new chemistry is much less common. Despite that, by bringing together so much data, we can provide a comprehensive overview of the most common and rare types of changes in function. Our analysis demonstrates on a larger scale than previously studied, that modifications in overall chemistry still occur, with all possible changes at the primary level of the Enzyme Commission (E.C.) classification observed to a greater or lesser extent. The phylogenetic trees map out the evolutionary route taken within a superfamily, as well as all the possible changes within a superfamily. This has been used to generate a matrix of observed exchanges from one enzyme function to another, revealing the scale and nature of enzyme evolution and that some types of exchanges between and within E.C. classes are more prevalent than others. Surprisingly a large proportion (71%) of all known enzyme functions are performed by this relatively small set of 276 superfamilies. This reinforces the hypothesis that relatively few ancient enzymatic domain superfamilies were progenitors for most of the chemistry required for life.

Enzymes, as biological catalysts, are crucial to life. Understanding how enzymes have evolved to perform the wide variety of reactions found across all kingdoms of life is fundamental to a broad range of biological studies, especially those leading to new therapeutics. To unravel the evolution of novel enzyme function requires combining information on protein structure, sequence, phylogeny and chemistry (in terms of interacting small molecules and reaction mechanisms). We have developed a protocol for integrating this wide range of data, which we have applied to a relatively large number of families comprising some very diverse relatives. This has permitted us to present an initial overview of the evolution of novel enzyme functions, in which we observe that some changes in function between relatives are more common than others, with most of the functionality observed in nature confined to relatively few families. Moreover, we are able to identify the evolutionary route taken within a superfamily to change the enzyme function from one reaction to another. This information may help in predicting the function of an enzyme that has yet to be experimentally characterised as well as in designing new enzymes for industrial and medical purposes.