The Moderately Efficient Enzyme: Evolutionary and Physicochemical Trends Shaping Enzyme Parameters

Glycolytic strategy as a tradeoff between energy yield and protein cost

Contrary to the textbook portrayal of glycolysis as a single pathway conserved across all domains of life, not all sugar-consuming organisms use the canonical Embden-Meyerhoff-Parnass (EMP) glycolytic pathway. Prokaryotic glucose metabolism is particularly diverse, including several alternative glycolytic pathways, the most common of which is the Entner-Doudoroff (ED) pathway. The prevalence of the ED pathway is puzzling as it produces only one ATP per glucose--half as much as the EMP pathway. We argue that the diversity of prokaryotic glucose metabolism may reflect a tradeoff between a pathway's energy (ATP) yield and the amount of enzymatic protein required to catalyze pathway flux. We introduce methods for analyzing pathways in terms of thermodynamics and kinetics and show that the ED pathway is expected to require several-fold less enzymatic protein to achieve the same glucose conversion rate as the EMP pathway. Through genomic analysis, we further show that prokaryotes use different glycolytic pathways depending on their energy supply. Specifically, energy-deprived anaerobes overwhelmingly rely upon the higher ATP yield of the EMP pathway, whereas the ED pathway is common among facultative anaerobes and even more common among aerobes. In addition to demonstrating how protein costs can explain the use of alternative metabolic strategies, this study illustrates a direct connection between an organism's environment and the thermodynamic and biochemical properties of the metabolic pathways it employs.

Integrating the protein and metabolic engineering toolkits for next-generation chemical biosynthesis

Through microbial engineering, biosynthesis has the potential to produce thousands of chemicals used in everyday life. Metabolic engineering and synthetic biology are fields driven by the manipulation of genes, genetic regulatory systems, and enzymatic pathways for developing highly productive microbial strains. Fundamentally, it is the biochemical characteristics of the enzymes themselves that dictate flux through a biosynthetic pathway toward the product of interest. As metabolic engineers target sophisticated secondary metabolites, there has been little recognition of the reduced catalytic activity and increased substrate/product promiscuity of the corresponding enzymes compared to those of central metabolism. Thus, fine-tuning these enzymatic characteristics through protein engineering is paramount for developing high-productivity microbial strains for secondary metabolites. Here, we describe the importance of protein engineering for advancing metabolic engineering of secondary metabolism pathways. This pathway integrated enzyme optimization can enhance the collective toolkit of microbial engineering to shape the future of chemical manufacturing.

Rational engineering of plasticity residues of sesquiterpene synthases from Artemisia annua: product specificity and catalytic efficiency

Most TPSs (terpene synthases) contain plasticity residues that are responsible for diversified terpene products and functional evolution, which provide a potential for improving catalytic efficiency. Artemisinin, a sesquiterpene lactone from Artemisia annua L., is widely used for malaria treatment and progress has been made in engineering the production of artemisinin or its precursors. In the present paper, we report a new sesquiterpene synthase from A. annua, AaBOS (A. annua α-bisabolol synthase), which has high sequence identity with AaADS (A. annua amorpha-4,11-diene synthase), a key enzyme in artemisinin biosynthesis. Comparative analysis of the two enzymes by domain-swapping and structure-based mutagenesis led to the identification of several plasticity residues, whose alteration changed the product profile of AaBOS to include γ-humulene as the major product. To elucidate the underlying mechanisms, we solved the crystal structures of AaBOS and a γ-humulene-producing AaBOS mutant (termed AaBOS-M2). Among the plasticity residues, position 399, located in the substrate-binding pocket, is crucial for both enzymes. In AaBOS, substitution of threonine for leucine (AaBOSL339T) is required for γ-humulene production; whereas in AaADS, replacing the threonine residue with serine (AaADST399S) resulted in a substantial increase in the activity of amorpha-4,11-diene production, probably as a result of accelerated product release. The present study demonstrates that substitution of plasticity residues has potential for improving catalytic efficiency of the enzyme.

Biochemical characteristics of a novel vegetative tissue geraniol acetyltransferase from a monoterpene oil grass (Palmarosa, Cymbopogon martinii var. Motia) leaf

Plants synthesize volatile alcohol esters on environmental insult or as metabolic induction during flower/fruit development. However, essential oil plants constitutively produce them as the oil constituents. Their synthesis is catalyzed by BAHD family enzymes called alcohol acyltransferases (AATs). However, no AAT has been characterized from plant foliage synthesizing acyclic monoterpenoids containing essential oils. Therefore, we have purified and biochemically characterized a geraniol: acetyl coenzyme A acetyltransferase (GAAT) from Palmarosa aroma grass (Cymbopogon martinii) leaf. MALDI-assisted proteomic study of the 43kDa monomeric enzyme revealed its sequence motif novelties e.g. relaxed conservation at Phe and Trp in DFGWG'. This suggests permissiveness of variations in the conserved motif without loss of catalytic ability. Also, some new conserved/semi-conserved motifs of AATs were recognized. The GAAT k(cat)/K(m) values (300-700M(-1)s(-1)) were low (a generic characteristic for secondary metabolism enzyme) but higher than those of some floral AATs. Wide substrate acceptability for catalyzing acetylation of diverse primary alcohols (chain of ≥C(6)) implied its catalytic description as a 'primary aliphatic alcohol acetyltransferase'. It signifies metabolic ability to deliver diverse aroma esters, should the acceptor alcohols be available in planta. To our knowledge, this is the first report of detailed kinetics of a vegetal monoterpenol acyltransferase.

Metabolite damage and its repair or pre-emption

It is increasingly evident that metabolites suffer various kinds of damage, that such damage happens in all organisms and that cells have dedicated systems for damage repair and containment. First, chemical biology is demonstrating that diverse metabolites are damaged by side reactions of 'promiscuous' enzymes or by spontaneous chemical reactions, that the products are useless or toxic and that the unchecked buildup of these products can be devastating. Second, genetic and genomic evidence from prokaryotes and eukaryotes is implicating a network of new, conserved enzymes that repair damaged metabolites or somehow pre-empt damage. Metabolite (that is, small-molecule) repair is analogous to macromolecule (DNA and protein) repair and seems from comparative genomic evidence to be equally widespread. Comparative genomics also implies that metabolite repair could be the function of many conserved protein families lacking known activities. How--and how well--cells deal with metabolite damage affects fields ranging from medical genetics to metabolic engineering.

The dynamics of hybrid metabolic-genetic oscillators

The synthetic construction of intracellular circuits is frequently hindered by a poor knowledge of appropriate kinetics and precise rate parameters. Here, we use generalized modeling (GM) to study the dynamical behavior of topological models of a family of hybrid metabolic-genetic circuits known as "metabolators." Under mild assumptions on the kinetics, we use GM to analytically prove that all explicit kinetic models which are topologically analogous to one such circuit, the "core metabolator," cannot undergo Hopf bifurcations. Then, we examine more detailed models of the metabolator. Inspired by the experimental observation of a Hopf bifurcation in a synthetically constructed circuit related to the core metabolator, we apply GM to identify the critical components of the synthetically constructed metabolator which must be reintroduced in order to recover the Hopf bifurcation. Next, we study the dynamics of a re-wired version of the core metabolator, dubbed the "reverse" metabolator, and show that it exhibits a substantially richer set of dynamical behaviors, including both local and global oscillations. Prompted by the observation of relaxation oscillations in the reverse metabolator, we study the role that a separation of genetic and metabolic time scales may play in its dynamics, and find that widely separated time scales promote stability in the circuit. Our results illustrate a generic pipeline for vetting the potential success of a circuit design, simply by studying the dynamics of the corresponding generalized model.

Hyperstability and substrate promiscuity in laboratory resurrections of Precambrian β-lactamases

We report a sequence reconstruction analysis targeting several Precambrian nodes in the evolution of class-A β-lactamases and the preparation and experimental characterization of their encoded proteins. Despite extensive sequence differences with the modern enzymes (~100 amino acid differences), the proteins resurrected in the laboratory properly fold into the canonical lactamase structure. The encoded proteins from 2-3 billion years (Gyr)-old β-lactamase sequences undergo cooperative two-state thermal denaturation and display very large denaturation temperature enhancements (~35 °C) relative to modern β-lactamases. They degrade different antibiotics in vitro with catalytic efficiencies comparable to that of an average modern enzyme. This enhanced substrate promiscuity is not accompanied by significant changes in the active-site region as seen in static X-ray structures, suggesting a plausible role for dynamics in the evolution of function in these proteins. Laboratory resurrections of 2-3 Gyr-old β-lactamases also endowed modern microorganisms with significant levels of resistance toward a variety of antibiotics, opening up the possibility of performing laboratory replays of the molecular tape of lactamase evolution. Overall, these results support the notions that Precambrian life was thermophilic and that proteins can evolve from substrate-promiscuous generalists into specialists during the course of natural evolution. They also highlight the biotechnological potential of laboratory resurrection of Precambrian proteins, as both high stability and enhanced promiscuity (likely contributors to high evolvability) are advantageous features in protein scaffolds for molecular design and laboratory evolution.

HDAC8 substrates: Histones and beyond

The lysine deacetylase family of enzymes (HDACs) was first demonstrated to catalyze deacetylation of acetyllysine residues on histones. In subsequent years, HDACs have been shown to recognize a large pool of acetylated nonhistone proteins as substrates. Recently, thousands of acetylated proteins have been discovered, yet in most cases, the HDAC that catalyzes deacetylation in vivo has not been identified. This gap has created the need for better in vivo, in vitro, and in silico approaches for determining HDAC substrates. While HDAC8 is the best kinetically and structurally characterized HDAC, few efficient substrates have yet been substantiated in vivo. In this review, we delineate factors that may be important for determining HDAC8 substrate recognition and catalytic activity, including structure, complex formation, and post-translational modifications. This summary provides insight into the challenges of identifying in vivo substrates for HDAC8, and provides a good vantage point for understanding the variables important for predicting HDAC substrate recognition.

Protein conformational disorder and enzyme catalysis

Though lacking a well-defined three-dimensional structure, intrinsically unstructured proteins are ubiquitous in nature. These molecules play crucial roles in many cellular processes, especially signaling and regulation. Surprisingly, even enzyme catalysis can tolerate substantial disorder. This observation contravenes conventional wisdom but is relevant to an understanding of how protein dynamics modulates enzyme function. This chapter reviews properties and characteristics of disordered proteins, emphasizing examples of enzymes that lack defined structures, and considers implications of structural disorder for catalytic efficiency and evolution.

Molecular cloning and catalytic characterization of a recombinant tropine biosynthetic tropinone reductase from Withania coagulans leaf

Tropinone reductases (TRs) are small proteins belonging to the SDR (short chain dehydrogenase/reductase) family of enzymes. TR-I and TR-II catalyze the conversion of tropinone into tropane alcohols (tropine and pseudotropine, respectively). The steps are intermediary enroute to biosynthesis of tropane esters of medicinal importance, hyoscyamine/scopolamine, and calystegins, respectively. Biosynthesis of tropane alkaloids has been proposed to occur in roots. However, in the present report, a tropine forming tropinone reductase (TR-I) cDNA was isolated from the aerial tissue (leaf) of a medicinal plant, Withania coagulans. The ORF was deduced to encode a polypeptide of 29.34 kDa. The complete cDNA (WcTRI) was expressed in E. coli and the recombinant His-tagged protein was purified for functional characterization. The enzyme had a narrow pH range of substantial activity with maxima at 6.6. Relatively superior thermostability of the enzyme (30% retention of activity at 60 °C) was catalytic novelty in consonance with the desert area restricted habitat of the plant. The in vitro reaction kinetics predominantly favoured the forward reaction. The enzyme had wide substrate specificity but did not cover the substrates of other well-known plant SDR related to menthol metabolism. To our knowledge, this pertains to be the first report on any gene and enzyme of secondary metabolism from the commercially and medicinally important vegetable rennet species.

Identification of novel interacting partners of Sirtuin6

SIRT6 is a member of the Sirtuin family of histone deacetylases that has been implicated in inflammatory, aging and metabolic pathways. Some of its actions have been suggested to be via physical interaction with NFκB and HIF1α and transcriptional regulation through its histone deacetylase activity. Our previous studies have investigated the histone deacetylase activity of SIRT6 and explored its ability to regulate the transcriptional responses to an inflammatory stimulus such as TNFα. In order to develop a greater understanding of SIRT6 function we have sought to identify SIRT6 interacting proteins by both yeast-2-hybrid and co-immunoprecipitation studies. We report a number of interacting partners which strengthen previous findings that SIRT6 functions in base excision repair (BER), and novel interactors which suggest a role in nucleosome and chromatin remodeling, the cell cycle and NFκB biology.

One substrate, five products: reactions catalyzed by the dihydroneopterin aldolase from Mycobacterium tuberculosis

Tetrahydrofolate cofactors are required for one carbon transfer reaction involved in the synthesis of purines, amino acids, and thymidine. Inhibition of tetrahydrofolate biosynthesis is a powerful therapeutic strategy in the treatment of several diseases, and the possibility of using antifolates to inhibit enzymes from Mycobacterium tuberculosis has been explored. This work focuses on the study of the first enzyme in tetrahydrofolate biosynthesis that is unique to bacteria, dihydroneopterin aldolase (MtDHNA). This enzyme requires no metals or cofactors and does not form a protein-mediated Schiff base with the substrate, unlike most aldolases. Here, we were able to demonstrate that the reaction catalyzed by MtDHNA generates three different pterin products, one of which is not produced by other wild-type DHNAs. The enzyme-substrate complex partitions 51% in the first turnover to form the aldolase products, 24% to the epimerase product and 25% to the oxygenase products. The aldolase reaction is strongly pH dependent, and apparent pK(a) values were obtained for the first time for this class of enzyme. Furthermore, chemistry is rate limiting for the aldolase reaction, and the analysis of solvent kinetic isotope effects in steady-state and pre-steady-state conditions, combined with proton inventory studies, revealed that two protons and a likely solvent contribution are involved in formation and breakage of a common intermediate. This study provides information about the plasticity required from a catalyst that possesses high substrate specificity while being capable of utilizing two distinct epimers with the same efficiency to generate five distinct products.

Engineering specialized metabolic pathways--is there a room for enzyme improvements?

Recent advances in enzyme engineering enable dramatic improvements in catalytic efficiency and/or selectivity, as well as de novo engineering of enzymes to catalyze reactions where natural enzymes are not available. Can these capabilities be utilized to transform biosynthesis pathways? Metabolic engineering is traditionally based on combining existing enzymes to give new, or modified, pathways, within a new context and/or organism. How efficient, however, are the individual enzyme components? Is there room to improve pathway performance by enzyme engineering? We discuss the differences between enzymes in central versus specialized, or secondary metabolism and highlight unique features of specialized metabolism enzymes participating in the synthesis of natural products. We argue that, for the purpose of metabolic engineering, the catalytic efficiency and selectivity of many enzymes can be improved with the aim of achieving higher rates, yields and product purities. We also note the relative abundance of spontaneous reactions in specialized metabolism, and the potential advantage of engineering enzymes that will catalyze these steps. Specialized metabolism therefore offers new opportunities to integrate enzyme and pathway engineering, thereby achieving higher metabolic efficiencies, enhanced production rates and improved product purities.

Computational protein engineering: bridging the gap between rational design and laboratory evolution

Enzymes are tremendously proficient catalysts, which can be used as extracellular catalysts for a whole host of processes, from chemical synthesis to the generation of novel biofuels. For them to be more amenable to the needs of biotechnology, however, it is often necessary to be able to manipulate their physico-chemical properties in an efficient and streamlined manner, and, ideally, to be able to train them to catalyze completely new reactions. Recent years have seen an explosion of interest in different approaches to achieve this, both in the laboratory, and in silico. There remains, however, a gap between current approaches to computational enzyme design, which have primarily focused on the early stages of the design process, and laboratory evolution, which is an extremely powerful tool for enzyme redesign, but will always be limited by the vastness of sequence space combined with the low frequency for desirable mutations. This review discusses different approaches towards computational enzyme design and demonstrates how combining newly developed screening approaches that can rapidly predict potential mutation “hotspots” with approaches that can quantitatively and reliably dissect the catalytic step can bridge the gap that currently exists between computational enzyme design and laboratory evolution studies.

Network context and selection in the evolution to enzyme specificity

Enzymes are thought to have evolved highly specific catalytic activities from promiscuous ancestral proteins. By analyzing a genome-scale model of Escherichia coli metabolism, we found that 37% of its enzymes act on a variety of substrates and catalyze 65% of the known metabolic reactions. However, it is not apparent why these generalist enzymes remain. Here, we show that there are marked differences between generalist enzymes and specialist enzymes, known to catalyze a single chemical reaction on one particular substrate in vivo. Specialist enzymes (i) are frequently essential, (ii) maintain higher metabolic flux, and (iii) require more regulation of enzyme activity to control metabolic flux in dynamic environments than do generalist enzymes. Furthermore, these properties are conserved in Archaea and Eukarya. Thus, the metabolic network context and environmental conditions influence enzyme evolution toward high specificity.

Achieving diversity in the face of constraints: lessons from metabolism

Metabolic engineering of plants can reduce the cost and environmental impact of agriculture while providing for the needs of a growing population. Although our understanding of plant metabolism continues to increase at a rapid pace, relatively few plant metabolic engineering projects with commercial potential have emerged, in part because of a lack of principles for the rational manipulation of plant phenotype. One underexplored approach to identifying such design principles derives from analysis of the dominant constraints on plant fitness, and the evolutionary innovations in response to those constraints, that gave rise to the enormous diversity of natural plant metabolic pathways.

Over expression of wild type or a catalytically dead mutant of Sirtuin 6 does not influence NFκB responses

SIRT6 is involved in inflammation, aging and metabolism potentially by modulating the functions of both NFκB and HIF1α. Since it is possible to make small molecule activators and inhibitors of Sirtuins we wished to establish biochemical and cellular assays both to assist in drug discovery efforts and to validate whether SIRT6 represents a valid drug target for these indications. We confirmed in cellular assays that SIRT6 can deacetylate acetylated-histone H3 lysine 9 (H3K9Ac), however this deacetylase activity is unusually low in biochemical assays. In an effort to develop alternative assay formats we observed that SIRT6 overexpression had no influence on TNFα induced nuclear translocation of NFκB, nor did it have an effect on nuclear mobility of RelA/p65. In an effort to identify a gene expression profile that could be used to identify a SIRT6 readout we conducted genome-wide expression studies. We observed that overexpression of SIRT6 had little influence on NFκB-dependent genes, but overexpression of the catalytically inactive mutant affected gene expression in developmental pathways.

Prediction of microbial growth rate versus biomass yield by a metabolic network with kinetic parameters

Identifying the factors that determine microbial growth rate under various environmental and genetic conditions is a major challenge of systems biology. While current genome-scale metabolic modeling approaches enable us to successfully predict a variety of metabolic phenotypes, including maximal biomass yield, the prediction of actual growth rate is a long standing goal. This gap stems from strictly relying on data regarding reaction stoichiometry and directionality, without accounting for enzyme kinetic considerations. Here we present a novel metabolic network-based approach, MetabOlic Modeling with ENzyme kineTics (MOMENT), which predicts metabolic flux rate and growth rate by utilizing prior data on enzyme turnover rates and enzyme molecular weights, without requiring measurements of nutrient uptake rates. The method is based on an identified design principle of metabolism in which enzymes catalyzing high flux reactions across different media tend to be more efficient in terms of having higher turnover numbers. Extending upon previous attempts to utilize kinetic data in genome-scale metabolic modeling, our approach takes into account the requirement for specific enzyme concentrations for catalyzing predicted metabolic flux rates, considering isozymes, protein complexes, and multi-functional enzymes. MOMENT is shown to significantly improve the prediction accuracy of various metabolic phenotypes in E. coli, including intracellular flux rates and changes in gene expression levels under different growth rates. Most importantly, MOMENT is shown to predict growth rates of E. coli under a diverse set of media that are correlated with experimental measurements, markedly improving upon existing state-of-the art stoichiometric modeling approaches. These results support the view that a physiological bound on cellular enzyme concentrations is a key factor that determines microbial growth rate.

While current genome-scale metabolic modeling approaches enable us to successfully predict a variety of metabolic phenotypes, identifying the factors that determine microbial growth rate and the prediction of growth rates under various conditions is still an open challenge. Here we present a metabolic network-based approach, MetabOlic Modeling with ENzyme kineTics (MOMENT), which predicts growth rates by integrating standard stoichiometric modeling with prior data on enzyme turnover rates and enzyme molecular weights, considering a physiological bound on total enzymes' concentration. The method is based on a finding that enzymes catalyzing high flux reactions tend to be more efficient in terms of having higher turnover numbers. MOMENT predicts growth rates of E. coli across a set of 24 different media that are significantly correlated with experimental measurements, while existing state-of-the art stoichiometric modeling approaches fail to do so. These results suggest that a bound on cellular enzyme concentrations is a key factor that determines microbial growth rate.

The Rise of Chemodiversity in Plants

Plants possess multifunctional and rapidly evolving specialized metabolic enzymes. Many metabolites do not appear to be immediately required for survival; nonetheless, many may contribute to maintaining population fitness in fluctuating and geographically dispersed environments. Others may serve no contemporary function but are produced inevitably as minor products by single enzymes with varying levels of catalytic promiscuity. The dominance of the terrestrial realm by plants likely mirrored expansion of specialized metabolism originating from primary metabolic pathways. Compared with their evolutionarily constrained counterparts in primary metabolism, specialized metabolic enzymes may be more tolerant to mutations normally considered destabilizing to protein structure and function. If this is true, permissiveness may partially explain the pronounced chemodiversity of terrestrial plants.

Probing the mutational interplay between primary and promiscuous protein functions: a computational-experimental approach

Protein promiscuity is of considerable interest due its role in adaptive metabolic plasticity, its fundamental connection with molecular evolution and also because of its biotechnological applications. Current views on the relation between primary and promiscuous protein activities stem largely from laboratory evolution experiments aimed at increasing promiscuous activity levels. Here, on the other hand, we attempt to assess the main features of the simultaneous modulation of the primary and promiscuous functions during the course of natural evolution. The computational/experimental approach we propose for this task involves the following steps: a function-targeted, statistical coupling analysis of evolutionary data is used to determine a set of positions likely linked to the recruitment of a promiscuous activity for a new function; a combinatorial library of mutations on this set of positions is prepared and screened for both, the primary and the promiscuous activities; a partial-least-squares reconstruction of the full combinatorial space is carried out; finally, an approximation to the Pareto set of variants with optimal primary/promiscuous activities is derived. Application of the approach to the emergence of folding catalysis in thioredoxin scaffolds reveals an unanticipated scenario: diverse patterns of primary/promiscuous activity modulation are possible, including a moderate (but likely significant in a biological context) simultaneous enhancement of both activities. We show that this scenario can be most simply explained on the basis of the conformational diversity hypothesis, although alternative interpretations cannot be ruled out. Overall, the results reported may help clarify the mechanisms of the evolution of new functions. From a different viewpoint, the partial-least-squares-reconstruction/Pareto-set-prediction approach we have introduced provides the computational basis for an efficient directed-evolution protocol aimed at the simultaneous enhancement of several protein features and should therefore open new possibilities in the engineering of multi-functional enzymes.

Interpretations of evolutionary processes at the molecular level have been determined to a significant extent by the concept of “trade-off”, the idea that improving a given feature of a protein molecule by mutation will likely bring about deterioration in other features. For instance, if a protein is able to carry out two different molecular tasks based on the same functional site (competing tasks), optimization for one task could be naively expected to impair its performance for the other task. In this work, we report a computational/experimental approach to assess the potential patterns of modulation of two competing molecular tasks in the course of natural evolution. Contrary to the naïve expectation, we find that diverse modulation patterns are possible, including the simultaneous optimization of the two tasks. We show, however, that this simultaneous optimization is not in conflict with the trade-offs expected for two competing tasks: using the language of the theory of economic efficiency, trade-offs are realized in the Pareto set of optimal variants for the two tasks, while most protein variants do not belong to such Pareto set. That is, most protein variants are not Pareto-efficient and can potentially be improved in terms of several features.

Intrinsic noise analyzer: a software package for the exploration of stochastic biochemical kinetics using the system size expansion

The accepted stochastic descriptions of biochemical dynamics under well-mixed conditions are given by the Chemical Master Equation and the Stochastic Simulation Algorithm, which are equivalent. The latter is a Monte-Carlo method, which, despite enjoying broad availability in a large number of existing software packages, is computationally expensive due to the huge amounts of ensemble averaging required for obtaining accurate statistical information. The former is a set of coupled differential-difference equations for the probability of the system being in any one of the possible mesoscopic states; these equations are typically computationally intractable because of the inherently large state space. Here we introduce the software package intrinsic Noise Analyzer (iNA), which allows for systematic analysis of stochastic biochemical kinetics by means of van Kampen's system size expansion of the Chemical Master Equation. iNA is platform independent and supports the popular SBML format natively. The present implementation is the first to adopt a complementary approach that combines state-of-the-art analysis tools using the computer algebra system Ginac with traditional methods of stochastic simulation. iNA integrates two approximation methods based on the system size expansion, the Linear Noise Approximation and effective mesoscopic rate equations, which to-date have not been available to non-expert users, into an easy-to-use graphical user interface. In particular, the present methods allow for quick approximate analysis of time-dependent mean concentrations, variances, covariances and correlations coefficients, which typically outperforms stochastic simulations. These analytical tools are complemented by automated multi-core stochastic simulations with direct statistical evaluation and visualization. We showcase iNA's performance by using it to explore the stochastic properties of cooperative and non-cooperative enzyme kinetics and a gene network associated with circadian rhythms. The software iNA is freely available as executable binaries for Linux, MacOSX and Microsoft Windows, as well as the full source code under an open source license.

Bridging the gaps in design methodologies by evolutionary optimization of the stability and proficiency of designed Kemp eliminase KE59

Computational design is a test of our understanding of enzyme catalysis and a means of engineering novel, tailor-made enzymes. While the de novo computational design of catalytically efficient enzymes remains a challenge, designed enzymes may comprise unique starting points for further optimization by directed evolution. Directed evolution of two computationally designed Kemp eliminases, KE07 and KE70, led to low to moderately efficient enzymes (k(cat)/K(m) values of ≤ 5 10(4) M(-1)s(-1)). Here we describe the optimization of a third design, KE59. Although KE59 was the most catalytically efficient Kemp eliminase from this design series (by k(cat)/K(m), and by catalyzing the elimination of nonactivated benzisoxazoles), its impaired stability prevented its evolutionary optimization. To boost KE59's evolvability, stabilizing consensus mutations were included in the libraries throughout the directed evolution process. The libraries were also screened with less activated substrates. Sixteen rounds of mutation and selection led to > 2,000-fold increase in catalytic efficiency, mainly via higher k(cat) values. The best KE59 variants exhibited k(cat)/K(m) values up to 0.6 10(6) M(-1)s(-1), and k(cat)/k(uncat) values of ≤ 10(7) almost regardless of substrate reactivity. Biochemical, structural, and molecular dynamics (MD) simulation studies provided insights regarding the optimization of KE59. Overall, the directed evolution of three different designed Kemp eliminases, KE07, KE70, and KE59, demonstrates that computational designs are highly evolvable and can be optimized to high catalytic efficiencies.

Thermodynamic constraints shape the structure of carbon fixation pathways

Thermodynamics impose a major constraint on the structure of metabolic pathways. Here, we use carbon fixation pathways to demonstrate how thermodynamics shape the structure of pathways and determine the cellular resources they consume. We analyze the energetic profile of prototypical reactions and show that each reaction type displays a characteristic change in Gibbs energy. Specifically, although carbon fixation pathways display a considerable structural variability, they are all energetically constrained by two types of reactions: carboxylation and carboxyl reduction. In fact, all adenosine triphosphate (ATP) molecules consumed by carbon fixation pathways - with a single exception - are used, directly or indirectly, to power one of these unfavorable reactions. When an indirect coupling is employed, the energy released by ATP hydrolysis is used to establish another chemical bond with high energy of hydrolysis, e.g. a thioester. This bond is cleaved by a downstream enzyme to energize an unfavorable reaction. Notably, many pathways exhibit reduced ATP requirement as they couple unfavorable carboxylation or carboxyl reduction reactions to exergonic reactions other than ATP hydrolysis. In the most extreme example, the reductive acetyl coenzyme A (acetyl-CoA) pathway bypasses almost all ATP-consuming reactions. On the other hand, the reductive pentose phosphate pathway appears to be the least ATP-efficient because it is the only carbon fixation pathway that invests ATP in metabolic aims other than carboxylation and carboxyl reduction. Altogether, our analysis indicates that basic thermodynamic considerations accurately predict the resource investment required to support a metabolic pathway and further identifies biochemical mechanisms that can decrease this requirement.

Rethinking glycolysis: on the biochemical logic of metabolic pathways

Metabolic pathways may seem arbitrary and unnecessarily complex. In many cases, a chemist might devise a simpler route for the biochemical transformation, so why has nature chosen such complex solutions? In this review, we distill lessons from a century of metabolic research and introduce new observations suggesting that the intricate structure of metabolic pathways can be explained by a small set of biochemical principles. Using glycolysis as an example, we demonstrate how three key biochemical constraints--thermodynamic favorability, availability of enzymatic mechanisms and the physicochemical properties of pathway intermediates--eliminate otherwise plausible metabolic strategies. Considering these constraints, glycolysis contains no unnecessary steps and represents one of the very few pathway structures that meet cellular demands. The analysis presented here can be applied to metabolic engineering efforts for the rational design of pathways that produce a desired product while satisfying biochemical constraints.

Out of fuzzy chemistry: from prebiotic chemistry to metabolic networks

The origin of life on Earth was a chemical affair. So how did primitive biochemical systems originate from geochemical and cosmochemical processes on the young planet? Contemporary research into the origins of life subscribes to the Darwinian principle of material causes operating in an evolutionary context, as advocated by A. I. Oparin and J. B. S. Haldane in the 1920s. In its simplest form (e.g., a bacterial cell) extant biological complexity relies on the functional integration of metabolic networks and replicative genomes inside a lipid boundary. Different research programmes have explored the prebiotic plausibility of each of these autocatalytic subsystems and combinations thereof: self-maintained networks of small molecules, template chemistry, and self-reproductive vesicles. This tutorial review focuses on the debates surrounding the origin of metabolism and offers a brief overview of current studies on the evolution of metabolic networks. I suggest that a leitmotif in the origin and evolution of metabolism is the role played by catalysers' substrate ambiguity and multifunctionality.

Communication: limitations of the stochastic quasi-steady-state approximation in open biochemical reaction networks

It is commonly believed that, whenever timescale separation holds, the predictions of reduced chemical master equations obtained using the stochastic quasi-steady-state approximation are in very good agreement with the predictions of the full master equations. We use the linear noise approximation to obtain a simple formula for the relative error between the predictions of the two master equations for the Michaelis-Menten reaction with substrate input. The reduced approach is predicted to overestimate the variance of the substrate concentration fluctuations by as much as 30%. The theoretical results are validated by stochastic simulations using experimental parameter values for enzymes involved in proteolysis, gluconeogenesis, and fermentation.

A survey of carbon fixation pathways through a quantitative lens

While the reductive pentose phosphate cycle is responsible for the fixation of most of the carbon in the biosphere, it has several natural substitutes. In fact, due to the characterization of three new carbon fixation pathways in the last decade, the diversity of known metabolic solutions for autotrophic growth has doubled. In this review, the different pathways are analysed and compared according to various criteria, trying to connect each of the different metabolic alternatives to suitable environments or metabolic goals. The different roles of carbon fixation are discussed; in addition to sustaining autotrophic growth it can also be used for energy conservation and as an electron sink for the recycling of reduced electron carriers. Our main focus in this review is on thermodynamic and kinetic aspects, including thermodynamically challenging reactions, the ATP requirement of each pathway, energetic constraints on carbon fixation, and factors that are expected to limit the rate of the pathways. Finally, possible metabolic structures of yet unknown carbon fixation pathways are suggested and discussed.

A measure of the promiscuity of proteins and characteristics of residues in the vicinity of the catalytic site that regulate promiscuity

Promiscuity, the basis for the evolution of new functions through 'tinkering' of residues in the vicinity of the catalytic site, is yet to be quantitatively defined. We present a computational method Promiscuity Indices Estimator (PROMISE)--based on signatures derived from the spatial and electrostatic properties of the catalytic residues, to estimate the promiscuity (PromIndex) of proteins with known active site residues and 3D structure. PromIndex reflects the number of different active site signatures that have congruent matches in close proximity of its native catalytic site, the quality of the matches and difference in the enzymatic activity. Promiscuity in proteins is observed to follow a lognormal distribution (μ = 0.28, σ = 1.1 reduced chi-square = 3.0E-5). The PROMISE predicted promiscuous functions in any protein can serve as the starting point for directed evolution experiments. PROMISE ranks carboxypeptidase A and ribonuclease A amongst the more promiscuous proteins. We have also investigated the properties of the residues in the vicinity of the catalytic site that regulates its promiscuity. Linear regression establishes a weak correlation (R(2)∼0.1) between certain properties of the residues (charge, polar, etc) in the neighborhood of the catalytic residues and PromIndex. A stronger relationship states that most proteins with high promiscuity have high percentages of charged and polar residues within a radius of 3 Å of the catalytic site, which is validated using one-tailed hypothesis tests (P-values∼0.05). Since it is known that these characteristics are key factors in catalysis, their relationship with the promiscuity index cross validates the methodology of PROMISE.

Increased Diels-Alderase activity through backbone remodeling guided by Foldit players

Computational enzyme design holds promise for the production of renewable fuels, drugs and chemicals. De novo enzyme design has generated catalysts for several reactions, but with lower catalytic efficiencies than naturally occurring enzymes. Here we report the use of game-driven crowdsourcing to enhance the activity of a computationally designed enzyme through the functional remodeling of its structure. Players of the online game Foldit were challenged to remodel the backbone of a computationally designed bimolecular Diels-Alderase to enable additional interactions with substrates. Several iterations of design and characterization generated a 24-residue helix-turn-helix motif, including a 13-residue insertion, that increased enzyme activity >18-fold. X-ray crystallography showed that the large insertion adopts a helix-turn-helix structure positioned as in the Foldit model. These results demonstrate that human creativity can extend beyond the macroscopic challenges encountered in everyday life to molecular-scale design problems.

Structural analyses of covalent enzyme-substrate analog complexes reveal strengths and limitations of de novo enzyme design

We report the cocrystal structures of a computationally designed and experimentally optimized retro-aldol enzyme with covalently bound substrate analogs. The structure with a covalently bound mechanism-based inhibitor is similar to, but not identical with, the design model, with an RMSD of 1.4 Å over active-site residues and equivalent substrate atoms. As in the design model, the binding pocket orients the substrate through hydrophobic interactions with the naphthyl moiety such that the oxygen atoms analogous to the carbinolamine and β-hydroxyl oxygens are positioned near a network of bound waters. However, there are differences between the design model and the structure: the orientation of the naphthyl group and the conformation of the catalytic lysine are slightly different; the bound water network appears to be more extensive; and the bound substrate analog exhibits more conformational heterogeneity than typical native enzyme-inhibitor complexes. Alanine scanning of the active-site residues shows that both the catalytic lysine and the residues around the binding pocket for the substrate naphthyl group make critical contributions to catalysis. Mutating the set of water-coordinating residues also significantly reduces catalytic activity. The crystal structure of the enzyme with a smaller substrate analog that lacks naphthyl ring shows the catalytic lysine to be more flexible than in the naphthyl-substrate complex; increased preorganization of the active site would likely improve catalysis. The covalently bound complex structures and mutagenesis data highlight the strengths and weaknesses of the de novo enzyme design strategy.

The Enzyme Function Initiative

The Enzyme Function Initiative (EFI) was recently established to address the challenge of assigning reliable functions to enzymes discovered in bacterial genome projects; in this Current Topic, we review the structure and operations of the EFI. The EFI includes the Superfamily/Genome, Protein, Structure, Computation, and Data/Dissemination Cores that provide the infrastructure for reliably predicting the in vitro functions of unknown enzymes. The initial targets for functional assignment are selected from five functionally diverse superfamilies (amidohydrolase, enolase, glutathione transferase, haloalkanoic acid dehalogenase, and isoprenoid synthase), with five superfamily specific Bridging Projects experimentally testing the predicted in vitro enzymatic activities. The EFI also includes the Microbiology Core that evaluates the in vivo context of in vitro enzymatic functions and confirms the functional predictions of the EFI. The deliverables of the EFI to the scientific community include (1) development of a large-scale, multidisciplinary sequence/structure-based strategy for functional assignment of unknown enzymes discovered in genome projects (target selection, protein production, structure determination, computation, experimental enzymology, microbiology, and structure-based annotation), (2) dissemination of the strategy to the community via publications, collaborations, workshops, and symposia, (3) computational and bioinformatic tools for using the strategy, (4) provision of experimental protocols and/or reagents for enzyme production and characterization, and (5) dissemination of data via the EFI's Website, http://enzymefunction.org. The realization of multidisciplinary strategies for functional assignment will begin to define the full metabolic diversity that exists in nature and will impact basic biochemical and evolutionary understanding, as well as a wide range of applications of central importance to industrial, medicinal, and pharmaceutical efforts.

Progesterone 5β-reductase of Erysimum crepidifolium: cDNA cloning, expression in Escherichia coli, and reduction of enones with the recombinant protein

Erysimum is a genus of the Brassicaceae family closely related to the genus Arabidopsis. Several Erysimum species accumulate 5β-cardenolides. Progesterone 5β-reductases (P5βRs) first described in Digitalis species are thought to be involved in 5β-cardenolide biosynthesis. P5βRs belong to the dehydrogenase/reductase super-family of proteins. A full length cDNA clone encoding a P5βR was isolated from Erysimum crepidifolium leaves by 5'/3' RACE-PCR (termed EcP5βR). Subsequently, the P5βR cDNAs of another nine Erysimum species were amplified by RT-PCR using 5' and 3' end primers deduced from the EcP5βR cDNA. The EcP5βR cDNA is 1170bp long and encodes for 389 amino acids. The EcP5βR cDNA was ligated into the vector pQE 30 UA and the recombinant His-tagged protein (termed rEcP5βR) was over-expressed in Escherichia coli and purified by Ni-chelate affinity chromatography. Kinetic constants were determined for progesterone, 2-cyclohexen-1-one, isophorone, and NADPH. The by far highest specificity constant (k(cat)K(M)⁻¹) was estimated for 2-cyclohexen-1-one indicating that this monocyclic enone may be more related to the natural substrate of the enzyme than progesterone. The atomic structure of rEcP5βR was modelled using the crystal structure of P5βR from Digitalis lanata 2V6G as the template. All sequence motifs specific for SDRs as well as the NFYYxxED motif typical for P5βR-like enzymes were present and the protein sequence fitted into the template smoothly.