Inborn errors of metabolite repair

It is traditionally assumed that enzymes of intermediary metabolism are extremely specific and that this is sufficient to prevent the production of useless and/or toxic side-products. Recent work indicates that this statement is not entirely correct. In reality, enzymes are not strictly specific, they often display weak side activities on intracellular metabolites (substrate promiscuity) that resemble their physiological substrate or slowly catalyse abnormal reactions on their physiological substrate (catalytic promiscuity). They thereby produce non-classical metabolites that are not efficiently metabolised by conventional enzymes. In an increasing number of cases, metabolite repair enzymes are being discovered that serve to eliminate these non-classical metabolites and prevent their accumulation. Metabolite repair enzymes also eliminate non-classical metabolites that are formed through spontaneous (ie, not enzyme-catalysed) reactions. Importantly, genetic deficiencies in several metabolite repair enzymes lead to 'inborn errors of metabolite repair', such as L-2-hydroxyglutaric aciduria, D-2-hydroxyglutaric aciduria, 'ubiquitous glucose-6-phosphatase' (G6PC3) deficiency, the neutropenia present in Glycogen Storage Disease type Ib or defects in the enzymes that repair the hydrated forms of NADH or NADPH. Metabolite repair defects may be difficult to identify as such, because the mutated enzymes are non-classical enzymes that act on non-classical metabolites, which in some cases accumulate only inside the cells, and at rather low, yet toxic, concentrations. It is therefore likely that many additional metabolite repair enzymes remain to be discovered and that many diseases of metabolite repair still await elucidation.

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).

Recent Advances in Enzymatic Complexity Generation: Cyclization Reactions

Enzymes in biosynthetic pathways, especially in plant and microbial metabolism, generate structural and functional group complexity in small molecules by conversion of acyclic frameworks to cyclic scaffolds via short, efficient routes. The distinct chemical logic used by several distinct classes of cyclases, oxidative and non-oxidative, has recently been elucidated by genome mining, heterologous expression, and genetic and mechanistic analyses. These include enzymes performing pericyclic transformations, pyran synthases, tandem acting epoxygenases, and epoxide "hydrolases", as well as oxygenases and radical S-adenosylmethionine enzymes that involve rearrangements of substrate radicals under aerobic or anaerobic conditions.

Enzyme sequestration by the substrate: An analysis in the deterministic and stochastic domains

This paper is concerned with the potential multistability of protein concentrations in the cell. That is, situations where one, or a family of, proteins may sit at one of two or more different steady state concentrations in otherwise identical cells, and in spite of them being in the same environment. For models of multisite protein phosphorylation for example, in the presence of excess substrate, it has been shown that the achievable number of stable steady states can increase linearly with the number of phosphosites available. In this paper, we analyse the consequences of adding enzyme docking to these and similar models, with the resultant sequestration of phosphatase and kinase by the fully unphosphorylated and by the fully phosphorylated substrates respectively. In the large molecule numbers limit, where deterministic analysis is applicable, we prove that there are always values for these rates of sequestration which, when exceeded, limit the extent of multistability. For the models considered here, these numbers are much smaller than the affinity of the enzymes to the substrate when it is in a modifiable state. As substrate enzyme-sequestration is increased, we further prove that the number of steady states will inevitably be reduced to one. For smaller molecule numbers a stochastic analysis is more appropriate, where multistability in the large molecule numbers limit can manifest itself as multimodality of the probability distribution; the system spending periods of time in the vicinity of one mode before jumping to another. Here, we find that substrate enzyme sequestration can induce bimodality even in systems where only a single steady state can exist at large numbers. To facilitate this analysis, we develop a weakly chained diagonally dominant M-matrix formulation of the Chemical Master Equation, allowing greater insights in the way particular mechanisms, like enzyme sequestration, can shape probability distributions and therefore exhibit different behaviour across different regimes.

The Protein Cost of Metabolic Fluxes: Prediction from Enzymatic Rate Laws and Cost Minimization

Bacterial growth depends crucially on metabolic fluxes, which are limited by the cell’s capacity to maintain metabolic enzymes. The necessary enzyme amount per unit flux is a major determinant of metabolic strategies both in evolution and bioengineering. It depends on enzyme parameters (such as k_cat and K_M constants), but also on metabolite concentrations. Moreover, similar amounts of different enzymes might incur different costs for the cell, depending on enzyme-specific properties such as protein size and half-life. Here, we developed enzyme cost minimization (ECM), a scalable method for computing enzyme amounts that support a given metabolic flux at a minimal protein cost. The complex interplay of enzyme and metabolite concentrations, e.g. through thermodynamic driving forces and enzyme saturation, would make it hard to solve this optimization problem directly. By treating enzyme cost as a function of metabolite levels, we formulated ECM as a numerically tractable, convex optimization problem. Its tiered approach allows for building models at different levels of detail, depending on the amount of available data. Validating our method with measured metabolite and protein levels in E. coli central metabolism, we found typical prediction fold errors of 4.1 and 2.6, respectively, for the two kinds of data. This result from the cost-optimized metabolic state is significantly better than randomly sampled metabolite profiles, supporting the hypothesis that enzyme cost is important for the fitness of E. coli. ECM can be used to predict enzyme levels and protein cost in natural and engineered pathways, and could be a valuable computational tool to assist metabolic engineering projects. Furthermore, it establishes a direct connection between protein cost and thermodynamics, and provides a physically plausible and computationally tractable way to include enzyme kinetics into constraint-based metabolic models, where kinetics have usually been ignored or oversimplified.

“Enzyme cost”, the amount of protein needed for a given metabolic flux, is crucial for the metabolic choices cells have to make. However, due to the technical limitations of linear optimization methods, this cost has traditionally been ignored by constraint-based metabolic models such as Flux Balance Analysis. On the other hand, more detailed kinetic models which use ordinary differential equations to simulate fluxes for different choices of enzyme allocation, are computationally demanding and not scalable enough. In this work, we developed a method which utilizes the full kinetic model to predict steady-state enzyme costs, using a scalable and robust algorithm based on convex optimization. We show that the minimization of enzyme cost is a meaningful optimality principle by comparing our predictions to measured enzyme and metabolite levels in exponentially growing E. coli. This method could be used to quantify the enzyme cost of many other pathways and explain why evolution has selected some low-yield metabolic strategies, including aerobic fermentation in yeast and cancer cells. Furthermore, future metabolic engineering projects could benefit from our method by choosing pathways that reduce the total amount of enzyme required for the synthesis of a value-added product.

Modeling the enzyme kinetic reaction

The Enzymatic control reactions model was presented within the scope of fractional calculus. In order to accommodate the usual initial conditions, the fractional derivative used is in Caputo sense. The methodologies of the three analytical methods were used to derive approximate solution of the fractional nonlinear system of differential equations. Two methods use integral operator and the other one uses just an integral. Numerical results obtained exhibit biological behavior of real world problem.

Computing with synthetic protocells

In this article we present a new kind of computing device that uses biochemical reactions networks as building blocks to implement logic gates. The architecture of a computing machine relies on these generic and composable building blocks, computation units, that can be used in multiple instances to perform complex boolean functions. Standard logical operations are implemented by biochemical networks, encapsulated and insulated within synthetic vesicles called protocells. These protocells are capable of exchanging energy and information with each other through transmembrane electron transfer. In the paradigm of computation we propose, protoputing, a machine can solve only one problem and therefore has to be built specifically. Thus, the programming phase in the standard computing paradigm is represented in our approach by the set of assembly instructions (specific attachments) that directs the wiring of the protocells that constitute the machine itself. To demonstrate the computing power of protocellular machines, we apply it to solve a NP-complete problem, known to be very demanding in computing power, the 3-SAT problem. We show how to program the assembly of a machine that can verify the satisfiability of a given boolean formula. Then we show how to use the massive parallelism of these machines to verify in less than 20 min all the valuations of the input variables and output a fluorescent signal when the formula is satisfiable or no signal at all otherwise.

[Metabolic correction: a biochemical option against diseases]

Human development and its physiology depends on a number of complex biochemical body processes, many of which are interactive and codependent. The speed and the degree in which many physiological reactions are completed depend on enzyme activity, which in turn depends on the bioavailability of co-factors and micronutrients such as vitamins and minerals. To achieve a healthy physiological state, organism need that biochemical reactions occur in a controlled and specific way at a particular speed and level or grade fully completed. To achieve this, is required an optimal metabolic balance. Factors such as, a particular genetic composition, inadequate dietary consumption patterns, traumas, diseases, toxins and environmental stress all of these factors rising demands for nutrients in order to obtain optimal metabolic balance. Metabolic correction is a biochemical and physiological concept that explains how improvements in cellular biochemistry of an organism can help the body achieve metabolic and physiological optimization. We summarize the contribution of several pioneers in understanding the role of micronutrients in health management. The concept of metabolic correction is becoming a significant term due to the presence of genetic variants that affect the speed of reactions of enzymes, causing metabolic alterations that enhance or promote the state/development of multiple diseases. Decline in the nutritional value of the food we eat, the increase in demand for certain nutrients caused by normal development, diseases and medications induce, usually, nutrients consumption. These nutritional deficiencies and insufficiencies are causing massive economic costs due to increased morbidity and mortality in our society. In summary, metabolic correction improves the enzymatic function, which favors the physiological normal functions, thus, contributing to improving health and the welfare of the human being. The purpose of this paper is to describe and introduce the concept of optimal metabolic correction as a functional cost-effective mechanism against disease, in addition, to contribute to diseases prevention and regeneration of the body and health.

Biological organisation as closure of constraints

We propose a conceptual and formal characterisation of biological organisation as a closure of constraints. We first establish a distinction between two causal regimes at work in biological systems: processes, which refer to the whole set of changes occurring in non-equilibrium open thermodynamic conditions; and constraints, those entities which, while acting upon the processes, exhibit some form of conservation (symmetry) at the relevant time scales. We then argue that, in biological systems, constraints realise closure, i.e. mutual dependence such that they both depend on and contribute to maintaining each other. With this characterisation in hand, we discuss how organisational closure can provide an operational tool for marking the boundaries between interacting biological systems. We conclude by focusing on the original conception of the relationship between stability and variation which emerges from this framework.

Kinetic memory based on the enzyme-limited competition

Cellular memory, which allows cells to retain information from their environment, is important for a variety of cellular functions, such as adaptation to external stimuli, cell differentiation, and synaptic plasticity. Although posttranslational modifications have received much attention as a source of cellular memory, the mechanisms directing such alterations have not been fully uncovered. It may be possible to embed memory in multiple stable states in dynamical systems governing modifications. However, several experiments on modifications of proteins suggest long-term relaxation depending on experienced external conditions, without explicit switches over multi-stable states. As an alternative to a multistability memory scheme, we propose "kinetic memory" for epigenetic cellular memory, in which memory is stored as a slow-relaxation process far from a stable fixed state. Information from previous environmental exposure is retained as the long-term maintenance of a cellular state, rather than switches over fixed states. To demonstrate this kinetic memory, we study several models in which multimeric proteins undergo catalytic modifications (e.g., phosphorylation and methylation), and find that a slow relaxation process of the modification state, logarithmic in time, appears when the concentration of a catalyst (enzyme) involved in the modification reactions is lower than that of the substrates. Sharp transitions from a normal fast-relaxation phase into this slow-relaxation phase are revealed, and explained by enzyme-limited competition among modification reactions. The slow-relaxation process is confirmed by simulations of several models of catalytic reactions of protein modifications, and it enables the memorization of external stimuli, as its time course depends crucially on the history of the stimuli. This kinetic memory provides novel insight into a broad class of cellular memory and functions. In particular, applications for long-term potentiation are discussed, including dynamic modifications of calcium-calmodulin kinase II and cAMP-response element-binding protein essential for synaptic plasticity.

Cryptococcus neoformans and Cryptococcus gattii, the etiologic agents of cryptococcosis

Cryptococcus neoformans and Cryptococcus gattii are the two etiologic agents of cryptococcosis. They belong to the phylum Basidiomycota and can be readily distinguished from other pathogenic yeasts such as Candida by the presence of a polysaccharide capsule, formation of melanin, and urease activity, which all function as virulence determinants. Infection proceeds via inhalation and subsequent dissemination to the central nervous system to cause meningoencephalitis. The most common risk for cryptococcosis caused by C. neoformans is AIDS, whereas infections caused by C. gattii are more often reported in immunocompetent patients with undefined risk than in the immunocompromised. There have been many chapters, reviews, and books written on C. neoformans. The topics we focus on in this article include species description, pathogenesis, life cycle, capsule, and stress response, which serve to highlight the specializations in virulence that have occurred in this unique encapsulated melanin-forming yeast that causes global deaths estimated at more than 600,000 annually.

Optimizing metabolite production using periodic oscillations

Methods for improving microbial strains for metabolite production remain the subject of constant research. Traditionally, metabolic tuning has been mostly limited to knockouts or overexpression of pathway genes and regulators. In this paper, we establish a new method to control metabolism by inducing optimally tuned time-oscillations in the levels of selected clusters of enzymes, as an alternative strategy to increase the production of a desired metabolite. Using an established kinetic model of the central carbon metabolism of Escherichia coli, we formulate this concept as a dynamic optimization problem over an extended, but finite time horizon. Total production of a metabolite of interest (in this case, phosphoenolpyruvate, PEP) is established as the objective function and time-varying concentrations of the cellular enzymes are used as decision variables. We observe that by varying, in an optimal fashion, levels of key enzymes in time, PEP production increases significantly compared to the unoptimized system. We demonstrate that oscillations can improve metabolic output in experimentally feasible synthetic circuits.

Vascular targeting of nanocarriers: perplexing aspects of the seemingly straightforward paradigm

Targeted nanomedicine holds promise to find clinical use in many medical areas. Endothelial cells that line the luminal surface of blood vessels represent a key target for treatment of inflammation, ischemia, thrombosis, stroke, and other neurological, cardiovascular, pulmonary, and oncological conditions. In other cases, the endothelium is a barrier for tissue penetration or a victim of adverse effects. Several endothelial surface markers including peptidases (e.g., ACE, APP, and APN) and adhesion molecules (e.g., ICAM-1 and PECAM) have been identified as key targets. Binding of nanocarriers to these molecules enables drug targeting and subsequent penetration into or across the endothelium, offering therapeutic effects that are unattainable by their nontargeted counterparts. We analyze diverse aspects of endothelial nanomedicine including (i) circulation and targeting of carriers with diverse geometries, (ii) multivalent interactions of carrier with endothelium, (iii) anchoring to multiple determinants, (iv) accessibility of binding sites and cellular response to their engagement, (v) role of cell phenotype and microenvironment in targeting, (vi) optimization of targeting by lowering carrier avidity, (vii) endocytosis of multivalent carriers via molecules not implicated in internalization of their ligands, and (viii) modulation of cellular uptake and trafficking by selection of specific epitopes on the target determinant, carrier geometry, and hydrodynamic factors. Refinement of these aspects and improving our understanding of vascular biology and pathology is likely to enable the clinical translation of vascular endothelial targeting of nanocarriers.

Factors and processes modulating phenotypes in neuronopathic lysosomal storage diseases

Lysosomal storage diseases are inherited metabolic disorders caused by genetic defects causing deficiency of various lysosomal proteins, and resultant accumulation of non-degraded compounds. They are multisystemic diseases, and in most of them (>70%) severe brain dysfunctions are evident. However, expression of various phenotypes in particular diseases is extremely variable, from non-neuronopathic to severely neurodegenerative in the deficiency of the same enzyme. Although all lysosomal storage diseases are monogenic, clear genotype-phenotype correlations occur only in some cases. In this article, we present an overview on various factors and processes, both general and specific for certain disorders, that can significantly modulate expression of phenotypes in these diseases. On the basis of recent reports describing studies on both animal models and clinical data, we propose a hypothesis that efficiency of production of compounds that cannot be degraded due to enzyme deficiency might be especially important in modulation of phenotypes of patients suffering from lysosomal storage diseases.

Metabolite proofreading, a neglected aspect of intermediary metabolism

Enzymes of intermediary metabolism are less specific than what is usually assumed: they often act on metabolites that are not their 'true' substrate, making abnormal metabolites that may be deleterious if they accumulate. Some of these abnormal metabolites are reconverted to normal metabolites by repair enzymes, which play therefore a role akin to the proofreading activities of DNA polymerases and aminoacyl-tRNA synthetases. An illustrative example of such repair enzymes is L-2-hydroxyglutarate dehydrogenase, which eliminates a metabolite abnormally made by a Krebs cycle enzyme. Mutations in L-2-hydroxyglutarate dehydrogenase lead to L-2-hydroxyglutaric aciduria, a leukoencephalopathy. Other examples are the epimerase and the ATP-dependent dehydratase that repair hydrated forms of NADH and NADPH; ethylmalonyl-CoA decarboxylase, which eliminates an abnormal metabolite formed by acetyl-CoA carboxylase, an enzyme of fatty acid synthesis; L-pipecolate oxidase, which repairs a metabolite formed by a side activity of an enzyme of L-proline biosynthesis. Metabolite proofreading enzymes are likely quite common, but most of them are still unidentified. A defect in these enzymes may account for new metabolic disorders.

The utility of paradoxical components in biological circuits

A recurring theme in biological circuits is the existence of components that are antagonistically bifunctional, in the sense that they simultaneously have two opposing effects on the same target or biological process. Examples include bifunctional enzymes that carry out two opposing reactions such as phosphorylating and dephosphorylating the same target, regulators that activate and also repress a gene in circuits called incoherent feedforward loops, and cytokines that signal immune cells to both proliferate and die. Such components are termed "paradoxical", and in this review we discuss how they can provide useful features to cell circuits that are otherwise difficult to achieve. In particular, we summarize how paradoxical components can provide robustness, generate temporal pulses, and provide fold-change detection, in which circuits respond to relative rather than absolute changes in signals.

Hydrogen tunneling links protein dynamics to enzyme catalysis

The relationship between protein dynamics and function is a subject of considerable contemporary interest. Although protein motions are frequently observed during ligand binding and release steps, the contribution of protein motions to the catalysis of bond making/breaking processes is more difficult to probe and verify. Here, we show how the quantum mechanical hydrogen tunneling associated with enzymatic C-H bond cleavage provides a unique window into the necessity of protein dynamics for achieving optimal catalysis. Experimental findings support a hierarchy of thermodynamically equilibrated motions that control the H-donor and -acceptor distance and active-site electrostatics, creating an ensemble of conformations suitable for H-tunneling. A possible extension of this view to methyl transfer and other catalyzed reactions is also presented. The impact of understanding these dynamics on the conceptual framework for enzyme activity, inhibitor/drug design, and biomimetic catalyst design is likely to be substantial.

Monod before Monod: enzymatic adaptation, Lwoff, and the legacy of general biology

For most of his scientific career, Jacques Monod appeared to be a man of a single problem: the formation of enzymes and the regulation of their properties. His ability to produce theoretical models led him to play a major role in both the discovery of the operon regulation and the model of allosteric transitions. The successes of Monod, from the 1950s to the Noble Prize (1965), are already well documented. In this paper, I will focus on the Monod before Monod, that is, the Monod who, during the 1940s, tried to explain the fundamental phenomenon of enzymatic adaptation. To begin with, however, I will survey how this phenomenon was discovered and explained by French Pasteurians at the very beginning of the twentieth century. This first explanation took place amidst an entrenched Lamarckian atmosphere in French thought, which was still alive during the 1920s and the 1930s, when Monod commenced the study of biology at the Sorbonne. Because of his will to construct a scientific biology free from teleology, Monod always tried to break from the legacy of this traditional background of Lamarckism, and he consequently developed ways of thinking that, in the main, were not part of the French biological tradition. Nevertheless, one point did link Monod to French history: his fruitful interactions with André Lwoff. As we shall see, these interactions were necessary for the development of Monod's science, both technically and intellectually speaking.

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.

High-throughput structural biology of metabolic enzymes and its impact on human diseases

The Structural Genomics Consortium (SGC) is a public-private partnership that aims to determine the three-dimensional structures of human proteins of medical relevance and place them into the public domain without restriction. To date, the Oxford Metabolic Enzyme Group at SGC has deposited the structures of more than 140 human metabolic enzymes from diverse protein families such as oxidoreductases, hydrolases, oxygenases and fatty acid transferases. A subset of our target proteins are involved in the inherited disorders of carbohydrate, fatty acid, amino acid and vitamin metabolism. This article will provide an overview of the structural data gathered from our high-throughput efforts and the lessons learnt in the structure-function relationship of these enzymes, small molecule development and the molecular basis of disease mutations.

[Using peptide strategy for study functions and structure of signal proteins with enzymatic activity]

The peptide strategy, a new direction of molecular endocrinology, includes the synthesis of peptides corresponding to functional regions of signal proteins, the use of the peptides for study of the molecular mechanisms of transduction of hormonal signal into cell ant the development of selective regulators of hormonal signaling systems on the basis of these peptides. The peptide strategy is used for study a wide spectrum of the proteins, components of signal systems, the proteins possessing the catalytic activity in particular, such as tyrosine kinases receptors, the enzymes generating the second messengers, serine/threonine protein kinase, phosphatases. In the first time in the review the data concerning the synthetic peptides, derivatives of the primary structure of proteins with the enzymatic activity, their application for study of the structural-functional organization and the molecular mechanisms of action of signal proteins, and the construction of regulators of fundamental cell processes on the basis of these peptides are analyzed and summarized.

Impact of temperature on the time required for the establishment of primordial biochemistry, and for the evolution of enzymes

All reactions are accelerated by an increase in temperature, but the magnitude of that effect on very slow reactions does not seem to have been fully appreciated. The hydrolysis of polysaccharides, for example, is accelerated 190,000-fold when the temperature is raised from 25 to 100 °C, while the rate of hydrolysis of phosphate monoester dianions increases 10,300,000-fold. Moreover, the slowest reactions tend to be the most heat-sensitive. These tendencies collapse, by as many as five orders of magnitude, the time that would have been required for early chemical evolution in a warm environment. We propose, further, that if the catalytic effect of a "proto-enzyme"--like that of modern enzymes--were mainly enthalpic, then the resulting rate enhancement would have increased automatically as the environment became cooler. Several powerful nonenzymatic catalysts of very slow biological reactions, notably pyridoxal phosphate and the ceric ion, are shown to meet that criterion. Taken together, these findings greatly reduce the time that would have been required for early chemical evolution, countering the view that not enough time has passed for life to have evolved to its present level of complexity.

Nitrite biosensing via selective enzymes--a long but promising route

The last decades have witnessed a steady increase of the social and political awareness for the need of monitoring and controlling environmental and industrial processes. In the case of nitrite ion, due to its potential toxicity for human health, the European Union has recently implemented a number of rules to restrict its level in drinking waters and food products. Although several analytical protocols have been proposed for nitrite quantification, none of them enable a reliable and quick analysis of complex samples. An alternative approach relies on the construction of biosensing devices using stable enzymes, with both high activity and specificity for nitrite. In this paper we review the current state-of-the-art in the field of electrochemical and optical biosensors using nitrite reducing enzymes as biorecognition elements and discuss the opportunities and challenges in this emerging market.

Ascorbate and plasma membrane electron transport--enzymes vs efflux

Transplasma membrane electron transport (tPMET) systems transfer electrons across the plasma membrane, resulting in the net reduction of extracellular oxidants (e.g., ferricyanide) at the expense of intracellular reductants such as NADH and ascorbate. In mammalian tPMET systems, the major proximal electron donor is ascorbate. The classical description of ascorbate-dependent tPMET views ascorbate as a restrictively intracellular electron donor to a transplasma membrane enzymatic activity that transfers electrons across the plasma membrane to various physiological acceptors (e.g., ferric iron and the ascorbyl radical). Candidate proteins involved in this process include members of the cytochrome b(561) family (e.g., duodenal cytochrome b). However, mounting evidence suggests that cellular export of ascorbate (and concomitant import of its two-electron oxidation product, dehydroascorbate) may constitute a novel and physiologically relevant form of ascorbate-dependent tPMET. As with enzymatic tPMET, cellular ascorbate export results in net electron transfer from the cytoplasm to the extracellular space. The mechanisms of ascorbate release from cells are ill-defined, though volume-sensitive anion channels and exocytosis remain promising candidates. Cellular ascorbate release is implicated in various homeostatic processes including ascorbate maintenance in blood and brain, and the uptake of non-transferrin-bound iron by cells. Recent insights into the "duality" of ascorbate-dependent tPMET are discussed.

Quantum catalysis in enzymes: beyond the transition state theory paradigm. A Discussion Meeting held at the Royal Society on 14 and 15 November 2005

How do enzymes work? What is the physical basis of the phenomenal rate enhancements achieved by enzymes? Do we have a theoretical framework that accounts for observed catalytic rates? These are the foremost questions-with particular emphasis on tunnelling phenomena-debated at this Discussion Meeting by the leading practitioners in the field.

EFICAz2: enzyme function inference by a combined approach enhanced by machine learning

BACKGROUND

We previously developed EFICAz, an enzyme function inference approach that combines predictions from non-completely overlapping component methods. Two of the four components in the original EFICAz are based on the detection of functionally discriminating residues (FDRs). FDRs distinguish between member of an enzyme family that are homofunctional (classified under the EC number of interest) or heterofunctional (annotated with another EC number or lacking enzymatic activity). Each of the two FDR-based components is associated to one of two specific kinds of enzyme families. EFICAz exhibits high precision performance, except when the maximal test to training sequence identity (MTTSI) is lower than 30%. To improve EFICAz's performance in this regime, we: i) increased the number of predictive components and ii) took advantage of consensual information from the different components to make the final EC number assignment.

RESULTS

We have developed two new EFICAz components, analogs to the two FDR-based components, where the discrimination between homo and heterofunctional members is based on the evaluation, via Support Vector Machine models, of all the aligned positions between the query sequence and the multiple sequence alignments associated to the enzyme families. Benchmark results indicate that: i) the new SVM-based components outperform their FDR-based counterparts, and ii) both SVM-based and FDR-based components generate unique predictions. We developed classification tree models to optimally combine the results from the six EFICAz components into a final EC number prediction. The new implementation of our approach, EFICAz2, exhibits a highly improved prediction precision at MTTSI < 30% compared to the original EFICAz, with only a slight decrease in prediction recall. A comparative analysis of enzyme function annotation of the human proteome by EFICAz2 and KEGG shows that: i) when both sources make EC number assignments for the same protein sequence, the assignments tend to be consistent and ii) EFICAz2 generates considerably more unique assignments than KEGG.

CONCLUSION

Performance benchmarks and the comparison with KEGG demonstrate that EFICAz2 is a powerful and precise tool for enzyme function annotation, with multiple applications in genome analysis and metabolic pathway reconstruction. The EFICAz2 web service is available at: http://cssb.biology.gatech.edu/skolnick/webservice/EFICAz2/index.html.

Enzyme function prediction with interpretable models

Enzymes play central roles in metabolic pathways, and the prediction of metabolic pathways in newly sequenced genomes usually starts with the assignment of genes to enzymatic reactions. However, genes with similar catalytic activity are not necessarily similar in sequence, and therefore the traditional sequence similarity-based approach often fails to identify the relevant enzymes, thus hindering efforts to map the metabolome of an organism.Here we study the direct relationship between basic protein properties and their function. Our goal is to develop a new tool for functional prediction (e.g., prediction of Enzyme Commission number), which can be used to complement and support other techniques based on sequence or structure information. In order to define this mapping we collected a set of 453 features and properties that characterize proteins and are believed to be related to structural and functional aspects of proteins. We introduce a mixture model of stochastic decision trees to learn the set of potentially complex relationships between features and function. To study these correlations, trees are created and tested on the Pfam classification of proteins, which is based on sequence, and the EC classification, which is based on enzymatic function. The model is very effective in learning highly diverged protein families or families that are not defined on the basis of sequence. The resulting tree structures highlight the properties that are strongly correlated with structural and functional aspects of protein families, and can be used to suggest a concise definition of a protein family.

BRENDA, AMENDA and FRENDA the enzyme information system: new content and tools in 2009

The BRENDA (BRaunschweig ENzyme DAtabase) (http://www.brenda-enzymes.org) represents the largest freely available information system containing a huge amount of biochemical and molecular information on all classified enzymes as well as software tools for querying the database and calculating molecular properties. The database covers information on classification and nomenclature, reaction and specificity, functional parameters, occurrence, enzyme structure and stability, mutants and enzyme engineering, preparation and isolation, the application of enzymes, and ligand-related data. The data in BRENDA are manually curated from more than 79,000 primary literature references. Each entry is clearly linked to a literature reference, the origin organism and, where available, to the protein sequence of the enzyme protein. A new search option provides the access to protein-specific data. FRENDA (Full Reference ENzyme DAta) and AMENDA (Automatic Mining of ENzyme DAta) are additional databases created by continuously improved text-mining procedures. These databases ought to provide a complete survey on enzyme data of the literature collection of PubMed. The web service via a SOAP (Simple Object Access Protocol) interface for access to the BRENDA data has been further enhanced.

Porcine preadipocyte proliferation and differentiation: a role for leptin?

The present study was designed to determine whether porcine leptin can alter the proliferation and differentiation of the porcine preadipocyte. The stromal vascular cell fraction of neonatal pig s.c. adipose tissue was isolated by collagenase digestion, filtration, and subsequent centrifugation. For differentiation studies, cells were seeded on six-well tissue culture plates and proliferated to confluency in 10% (vol/vol) fetal bovine serum (FBS) in Dulbecco's modified Eagle medium/F12 (DMEM/F12; 50:50). Cultures were differentiated using 2.5% pig serum (vol/vol) and recombinant porcine leptin at concentrations of 0 to 1,000 ng/mL alone or in combination with porcine insulin (100 nM), dexamethasone (1 microM), or IGF-1 (250 ng/mL). After 7 d of lipid filling, cultures were harvested for analysis of sn-glycerol 3 phosphate dehydrogenase (GPDH) and lipoprotein lipase (LPL). The GPDH and LPL activities are measures of preadipocyte differentiation. Data were corrected for protein content of the cultures. For proliferation experiments, 24 h after seeding cells with 10% FBS in DMEM/F12 in 25-cm2 tissue culture flasks, cells were switched to 5% FBS and supplemented with 0 to 1,000 ng of porcine leptin or 1,000 ng of murine leptin. Cell proliferation was measured by 3H-thymidine incorporation in preconfluent cultures over 24 h on d 4 of culture. At confluency, cells were switched to a medium to promote differentiation and lipid filling (2.5% pig serum, 100 nM insulin, 1 microM dexamethasone) for 7 d. Cells were harvested from the flasks and adipocytes were separated from stromal cells by Percoll gradient centrifugation. In a series of experiments, leptin alone or in combination with insulin, dexamethasone, or IGF-I did not affect differentiation as measured by the activity of GPDH and LPL. Leptin at any concentration did not inhibit differentiation induced by insulin, dexamethasone, or IGF-I; however, leptin at 1,000 ng/mL stimulated a 30% increase in preadipocyte proliferation (P = 0.007; n = 6) and a 27% increase in stromal cell proliferation (P < 0.001; n = 6). These results indicate that, at most, porcine leptin may contribute to the recruitment of new adipocytes within the adipose tissue.

Transient stress and stress enzyme responses have practical impacts on parameters of embryo development, from IVF to directed differentiation of stem cells

In this review, we discuss the expression, regulation, downstream mechanisms, and function of stress-induced stress enzymes in mammalian oocytes, peri-implantation embryos, and the stem cells derived from those embryos. Recent reports suggest that stress enzymes mediate developmental functions during early mammalian development, in addition to the homeostatic functions shared with somatic cells. Stress-induced enzymes appear to insure that necessary developmental events occur: many of these events may occur at a slower rate, although some may occur more rapidly. Developmental events induced by stress may be mediated by a single dominant enzyme, but there are examples of responses that require the integration of more than one stress enzyme. The discussion focuses on the consequences of stress as a function of duration and magnitude, and this includes an emerging understanding of the threshold levels of duration and magnitude that lead to pathology. Other topics discussed are the reversibility of the developmental as well as homeostatic consequences of stress, the further problems with readaptation after stress subsides, and the mechanisms and functions of stress enzymes during early mammalian development. The analyses are done with specific concern for their practical impact in assisted reproductive technology (ART) and stem cell technologies.

Adrenal androgens in humans and nonhuman primates: production, zonation and regulation

The synthesis and secretion of large quantities of the adrenal androgens, dehydroepiandrosterone (DHEA) and its sulfoconjugate DHEA sulfate (DS), is a phenomenon that appears limited to humans and some nonhuman primates. Both hydroxylase and lyase activities of the enzyme 17alpha-hydroxylase/17,20-lyase cytochrome P450 (P450c17) are necessary for DHEA production and are differentially regulated during adrenal development. Production of DHEA and DS occurs in the zona reticularis (ZR) of adults and the fetal zone of fetal primate adrenal glands, which is the primary substrate for maternal estrogen production during pregnancy. The onset of adrenal androgen production in childhood, referred to as adrenarche, corresponds with the establishment of the ZR: but the process is poorly understood, largely due to the lack of accessible animal models. Several nonhuman primates have been used to study adrenal function and remodeling, though none completely recapitulates human adrenarche, developmentally, functionally or temporally. This review will summarize the variations in adrenal androgen production and adrenal zonation in humans and nonhuman primates throughout life. It is hoped that recent studies demonstrating adrenarche in the rhesus will put in proper context the significance of adrenal zonation in nonhuman primates as valid models for human adrenal development and function.

Steroidogenic enzymes

The enzymes and pathways of steroidogenesis are familiar to most endocrinologists, but the biochemistry and molecular biology of these processes are still being studied. This chapter outlines current knowledge about each enzyme. The quantitative regulation of steroidogenesis occurs at the first step, the conversion of cholesterol to pregnenolone. Chronic regulation is principally at the level of transcription of the gene for P450 side chain cleave (P450scc), which is the enzymatically rate-limiting step. Acute regulation is mediated by steroidogenic acute regulatory protein, which facilitates the rapid influx of cholesterol into mitochondria, where P450scc resides. Qualitative regulation, determining the class of steroid produced, is principally determined by P450c17. In the absence of P450c17 in the zona glomerulosa, C21 deoxy steroids are produced, leading to the mineralocorticoid aldosterone. In the presence of the 17alpha-hydroxylase but not the 17,20 lyase activity of P450c17 in the zona fasciculata, C21, 17-hydroxy steroids are produced, leading to the glucocorticoid cortisol. When both the 17alpha-hydroxylase and 17,20 lyase activities of P450c17 are present in the zona reticularis, the androgen precursor dehydroepiandrosterone is produced. The discrimination between 17alpha-hydroxylase and 17,20 lyase activities is regulated by two posttranslational events, the serine phosphorylation of P450c17 and the allosteric action of cytochrome b5, both of which act to optimize the interaction of P450c17 with its obligatory electron donor, P450 oxidoreductase.

Cardiac sodium channel Nav1.5 and its associated proteins

The main cardiac voltage-gated Na+ channel, Nav1.5, plays a key role in generation of the cardiac action potential (cardiac excitability) and propagation of the electrical impulse in the heart (cardiac conduction). During the past decade, numerous mutations in SCN5A, the gene, encoding Nav1.5, were found in patients with different pathologic cardiac phenotypes such as the congenital long QT syndrome type 3, Brugada syndrome, and progressive cardiac conduction defect (or Lenègre-Lev disease). These mutations define a sub-group of Nav1.5 / SCN5A-related cardiac channelopathies. Recent works have suggested that Nav1.5 is part of several multi-protein complexes located in different membrane compartments of the cardiac cells. In some instances, the genes of these regulatory proteins were also found to be mutated in patients with inherited forms of cardiac arrhythmias. The proteins that associate with Nav1.5, and form these complexes, can be classified as 1) anchoring/adaptor proteins, 2) enzymes interacting with and modifying the channel, and 3) proteins modulating the biophysical properties of Nav1.5 upon binding. The purpose of this short article is to review the proposed roles of these interactions. These recent observations indicate that the expression level, cellular localization, and activity of Nav1.5 are finely regulated by complex molecular mechanisms that we are only starting to elucidate.

Mechanism of cell surface expression of the Streptococcus mitis platelet binding proteins PblA and PblB

PblA and PblB are prophage-encoded proteins of Streptococcus mitis strain SF100 that mediate binding to human platelets. The mechanism for surface expression of these proteins has been unknown, as they do not contain signal sequences or cell wall sorting motifs. We therefore assessed whether expression of these proteins was linked the lytic cycle of the prophage. Deletion of either the holin or lysin gene resulted in retention of PblA and PblB in the cytoplasm, and loss of these proteins from the cell wall. Flow cytometric analysis revealed that induction of phage replication in SF100 produced a subpopulation of cells with increased permeability. This effect was abrogated by disruption of the holin and lysin genes. Treatment of these mutants with exogenous PblA and PblB restored surface expression, apparently via binding of the proteins to cell wall choline. Loss of PblA and PblB expression was associated with decreased platelet binding in vitro, and reduced virulence in an animal model of endocarditis. Thus, expression of PblA and PblB occurs via a novel mechanism, whereby phage induction increases bacterial permeability and release of the proteins, followed by their binding to surface of viable cells. This mechanism may be important for endovascular infection.

Genome-wide analysis of enzyme structure-function combination across three domains of life

To investigate diverse enzyme structure-function combination (SFC) types in different species, 34 different genome sequences were annotated using the protein catalytic domain database SCOPEC (http://www.enzome.com/enzome/), in which both the structure and function for each entry are known. Annotated enzymes with catalytic domains from the same SCOP superfamily are considered to have an identical structure. Annotated enzymes sharing the identical three-digit EC number are considered to have the same enzymatic function. Results reveal that the different SFC types for enzymes identified in archaea, bacteria and eukaryota are 137, 300 and 313, respectively. About 80% of the SFCs identified in archaea can be consistently found in bacteria and eukaryota species, whereas 28% and 35% combination types in bacteria and eukaryota respectively are unique to their corresponding groups. The number of functions per structure and the number of structures per function for the annotated sequences were measured in different species. Furthermore, a new concept was proposed to represent enzymatic structures as a functional similarity network. Thus, the current study will be helpful to enhance the global view on the evolution of enzymatic structure and function.

Isolation and properties of a levo-lactonase from Fusarium proliferatum ECU2002: a robust biocatalyst for production of chiral lactones

A fungus strain ECU2002, capable of enantioselectively hydrolyzing chiral lactones to optically pure hydroxy acids, was newly isolated from soil samples through two steps of screening and identified as Fusarium proliferatum (Matsushima) Nirenberg. From the crude extract of F. proliferatum ECU2002, a novel levo-lactonase was purified to homogeneity, with a purification factor of 460-folds and an overall yield of 9.7%, by ultrafiltration, acetone precipitation, and chromatographic separation through DEAE-Toyopearl, Butyl-Toyopearl, Hydroxyapatite, Toyoscreen-Super Q, and TSK-gel columns. The purified enzyme is a monomer; with a molecular mass of ca 68 kDa and a pI of 5.7 as determined by two-dimensional electrophoresis. The catalytic performance of the partially purified levo-lactonase was investigated, giving temperature and pH optima at 50 degrees C and 7.5, respectively, for gamma-butyrolactone hydrolysis. The substrate specificity of the partially purified lactonase was also examined using several useful lactones, among which alpha-hydroxy-gamma-butyrolactone was the best substrate, with 448-fold higher lactonase activity as compared to gamma-butyrolactone. The F. proliferatum lactonase preferentially hydrolyzed the levo enantiomer of butyrolactones, including beta-butyrolactone, alpha-hydroxy-gamma-butyrolactone, alpha-hydroxy-beta,beta-dimethyl-gamma-butyrolactone (pantolactone), and beta-hydroxy-gamma-butyrolactone, affording (+)-hydroxy acids in high (94.8 approximately 98.2%) enantiomeric excesses (ee) and good conversions (38.2 approximately 44.2%). A simple immobilization of the crude lactonase with glutaraldehyde cross-linking led to a stable and easy-to-handle biocatalyst for catalytic resolution of chiral lactones. The immobilized lactonase also performed quite well in repeated batch resolution of dl-pantolactone at a concentration of 35% (w/v), retaining 67% of initial activity after ten cycles of reaction (corresponding to a half life of 20 cycles) and affording the product in 94 approximately 97% ee, which can be easily enhanced to >99% ee after the d-hydroxy acid was chemically converted into l-lactone and crystallized.

Enzymes and pharmacogenetics of cardiovascular drugs

To select the best drug for a patient, physicians can use pharmacogenomics to optimize the effective drug and to minimize adverse reactions. Many enzymes are involved in the pharmacokinetic and pharmacodynamic sources of cardiovascular drugs. Taking the antihypertensive drugs as an example, the variability in blood pressure response is very high in different individuals, some of them having an increase in blood pressure. The most important proteins involved in the patient response to a drug are cytochrome P450 (CYP) 2D6, CYP2C19, CYP3A4 and the ABCB1 transporter. These enzymes, at the origin of important side effects or drug interactions, are responsible, at a great extent, of the cardiovascular drug response variability. Genotyping of the most important CYP today is easy while no reliable tool has been developed for the ABC transporters ATPase dependent and linked to the other phase I and phase II enzymes. The second relevant group of enzymes are involved in pharmacodynamic action of cardiovascular drugs: enzymes of the renin-angiotensin system and enzymes of the lipid metabolism. Angiotensin converting enzyme (ACE) is the most studied target with a relevant insertion deletion polymorphism. Contradictory reported data could be explained by ethnic differences or patient sample size which are often too small.

Selection strategies for improved biocatalysts

Enzymes have become an attractive alternative to conventional catalysts in numerous industrial processes. However, their properties do not always meet the criteria of the application of interest. Directed evolution is a powerful tool for adopting the characteristics of an enzyme. However, selection of the evolved variants is a critical step, and therefore new strategies to enable selection of the desired enzymatic activity have been developed. This review focuses on these novel strategies for selecting enzymes from large libraries, in particular those that are used in the synthesis of pharmaceutical intermediates and pharmaceuticals.