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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)., (© The Author(s) 2020. Published by Oxford University Press.)

Transcription factors (TFs) are important drivers of cellular decision-making. When bacteria encounter a change in the environment, TFs alter the expression of a defined set of genes in order to adequately respond. It is commonly assumed that genes regulated by the same TF are involved in the same biological process. Examples of this are methods that rely on coregulation to infer function of not-yet-annotated genes. We have previously shown that only 21% of TFs involved in metabolism regulate functionally homogeneous genes, based on the proximity of the gene products' catalyzed reactions in the metabolic network. Here, we provide more evidence to support the claim that a 1-TF/1-process relationship is not a general property. We show that the observed functional heterogeneity of regulons is not a result of the quality of the annotation of regulatory interactions, nor the absence of protein-metabolite interactions, and that it is also present when function is defined by Gene Ontology terms. Furthermore, the observed functional heterogeneity is different from the one expected by chance, supporting the notion that it is a biological property. To further explore the relationship between transcriptional regulation and metabolism, we analyzed five other types of regulatory groups and identified complex regulons (i.e. genes regulated by the same combination of TFs) as the most functionally homogeneous, and this is supported by coexpression data. Whether higher levels of related functions exist beyond metabolism and current functional annotations remains an open question., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

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., Competing Interests: The authors have declared that no competing interests exist.

Chromatin regulators (CRs) can dynamically modulate chromatin architecture to epigenetically regulate gene expression in response to intrinsic and extrinsic signalling cues. Somatic alterations or misexpression of CRs might reprogram the epigenomic landscape of chromatin, which in turn lead to a wide range of common diseases, notably cancer. Here, we present CR2Cancer, a comprehensive annotation and visualization database for CRs in human cancer constructed by high throughput data analysis and literature mining. We collected and integrated genomic, transcriptomic, proteomic, clinical and functional information for over 400 CRs across multiple cancer types. We also built diverse types of CR-associated relations, including cancer type dependent (CR-target and miRNA-CR) and independent (protein-protein interaction and drug-target) ones. Furthermore, we manually curated around 6000 items of aberrant molecular alterations and interactions of CRs in cancer development from 5007 publications. CR2Cancer provides a user-friendly web interface to conveniently browse, search and download data of interest. We believe that this database would become a valuable resource for cancer epigenetics investigation and potential clinical application. CR2Cancer is freely available at http://cis.hku.hk/CR2Cancer., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Bioelectrochemistry can be defined as a branch of Chemical Science concerned with electron-proton transfer and transport involving biomolecules, as well as electrode reactions of redox enzymes. The bioelectrochemical reactions and system have direct impact in biotechnological development, in medical devices designing, in the behavior of DNA-protein complexes, in green-energy and bioenergy concepts, and make it possible an understanding of metabolism of all living organisms (e.g. humans) where biomolecules are integral to health and proper functioning. In the last years, many researchers have dedicated itself to study different redox enzymes by using electrochemistry, aiming to understand their mechanisms and to develop promising bioanodes and biocathodes for biofuel cells as well as to develop biosensors and implantable bioelectronics devices. Inside this scope, this review try to introduce and contemplate some relevant topics for enzyme bioelectrochemistry, such as the immobilization of the enzymes at electrode surfaces, the electron transfer, the bioelectrocatalysis, and new techniques conjugated with electrochemistry vising understand the kinetics and thermodynamics of redox proteins. Furthermore, examples of recent approaches in designing biosensors and biofuel developed are presented.

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 kcat and KM 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., Competing Interests: The authors have declared that no competing interests exist.

Enzymes are proteins that accelerate intracellular chemical reactions often by factors of 105-1012s-1. We propose the structure and function of enzymes represent the thermodynamic expression of heritable information encoded in DNA with post-translational modifications that reflect intra- and extra-cellular environmental inputs. The 3 dimensional shape of the protein, determined by the genetically-specified amino acid sequence and post translational modifications, permits geometric interactions with substrate molecules traditionally described by the key-lock best fit model. Here we apply Kullback-Leibler (K-L) divergence as metric of this geometric "fit" and the information content of the interactions. When the K-L 'distance' between interspersed substrate pn and enzyme rn positions is minimized, the information state, reaction probability, and reaction rate are maximized. The latter obeys the Arrhenius equation, which we show can be derived from the geometrical principle of minimum K-L distance. The derivation is first limited to optimum substrate positions for fixed sets of enzyme positions. However, maximally improving the key/lock fit, called 'induced fit,' requires both sets of positions to be varied optimally. We demonstrate this permits and is maximally efficient if the key and lock particles pn, rn are quantum entangled because the level of entanglement obeys the same minimized value of the Kullback-Leibler distance that occurs when all pn ≈ rn. This implies interchanges pn ⇄ brn randomly taking place during a reaction successively improves key/lock fits, reducing the activation energy Ea and increasing the reaction rate k. Our results demonstrate the summation of heritable and environmental information that determines the enzyme spatial configuration, by decreasing the K-L divergence, is converted to thermodynamic work by reducing Ea and increasing k of intracellular reactions. Macroscopically, enzyme information increases the order in living systems, similar to the Maxwell demon gedanken, by selectively accelerating specific reaction thus generating both spatial and temporal concentration gradients.

Fibrogenesis involves a dynamic interplay between factors that promote the biosynthesis and deposition of extracellular matrix along with pathways that degrade the extracellular matrix and eliminate the primary effector cells. Opposing the often held perception that fibrotic tissue is permanent, animal studies and clinical data now demonstrate the highly plastic nature of organ fibrosis that can, under certain circumstances, regress. This review describes the current understanding of the mechanisms whereby the lung is known to resolve fibrosis focusing on degradation of the extracellular matrix, removal of myofibroblasts, and the role of inflammatory cells. Although there are significant gaps in understanding lung fibrosis resolution, accelerated improvements in biotechnology and bioinformatics are expected to improve the understanding of these mechanisms and have high potential to lead to novel and effective restorative therapies in the treatment not only of pulmonary fibrosis, but also of a wide-ranging spectrum of chronic disorders., (Copyright © 2016 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

In 1959, Jacques Monod wrote a manuscript entitled Cybernétique enzymatique [Enzymatic cybernetics]. Never published, this unpublished manuscript presents a synthesis of how Monod interpreted enzymatic adaptation just before the publication of the famous papers of the 1960s on the operon. In addition, Monod offers an example of a philosophy of biology immersed in scientific investigation. Monod's philosophical thoughts are classified into two categories, methodological and ontological. On the methodological side, Monod explicitly hints at his preferences regarding the scientific method in general: hypothetical-deductive method, and use of theoretical models. He also makes heuristic proposals regarding molecular biology: the need to analyse the phenomena in question at the level of individual cells, and the dual aspect of all biological explanation, functional and evolutionary. Ontological issues deal with the notions of information and genetic determinism, "cellular memory", the irrelevance of the notion of "living matter", and the usefulness of a cybernetic comprehension of molecular biology., (Copyright © 2015 Académie des sciences. Published by Elsevier SAS. All rights reserved.)

The field of redox proteomics focuses to a large extent on analyzing cysteine oxidation in proteins under different experimental conditions and states of diseases. The identification and localization of oxidized cysteines within the cellular milieu is critical for understanding the redox regulation of proteins under physiological and pathophysiological conditions, and it will in turn provide important information that are potentially useful for the development of novel strategies in the treatment and prevention of diseases associated with oxidative stress. Antioxidant enzymes that catalyze oxidation/reduction processes are able to serve as redox biomarkers in various human diseases, and they are key regulators controlling the redox state of functional proteins. Redox regulators with antioxidant properties related to active mediators, cellular organelles, and the surrounding environments are all connected within a network and are involved in diseases related to redox imbalance including cancer, ischemia/reperfusion injury, neurodegenerative diseases, as well as normal aging. In this review, we will briefly look at the selected aspects of oxidative thiol modification in antioxidant enzymes and thiol oxidation in proteins affected by redox control of antioxidant enzymes and their relation to disease.

Enzymes play important roles in catalysing biochemical transaction paths, acting as logical machines through the morphology of the processes. A key challenge in elucidating the nature of these systems, and for engineering manufacturing methods inspired by biochemical reactions, is to attain a comprehensive understanding of the stereochemical ground rules of enzymatic reactions. Here, we present a model of catalysis that can be performed magnetically by centimetre-sized passive floating units. The designed system, which is equipped with permanent magnets only, passively obeys the local causalities imposed by magnetic interactions, albeit it shows a spatial behaviour and an energy profile analogous to those of biochemical enzymes. In this process, the enzyme units trigger physical conformation changes of the target by levelling out the magnetic potential barrier (activation potential) to a funnel type and, thus, induce cascading conformation changes of the targeted substrate units reacting in parallel. The inhibitor units, conversely, suppress such changes by increasing the potential. Because the model is purely mechanical and established on a physics basis in the absence of turbulence, each performance can be explained by the morphology of the unit, extending the definition of catalysis to systems of alternative scales.

We present a quantitative model to demonstrate that coclustering multiple enzymes into compact agglomerates accelerates the processing of intermediates, yielding the same efficiency benefits as direct channeling, a well-known mechanism in which enzymes are funneled between enzyme active sites through a physical tunnel. The model predicts the separation and size of coclusters that maximize metabolic efficiency, and this prediction is in agreement with previously reported spacings between coclusters in mammalian cells. For direct validation, we study a metabolic branch point in Escherichia coli and experimentally confirm the model prediction that enzyme agglomerates can accelerate the processing of a shared intermediate by one branch, and thus regulate steady-state flux division. Our studies establish a quantitative framework to understand coclustering-mediated metabolic channeling and its application to both efficiency improvement and metabolic regulation.

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 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., (Copyright © 2014 Cold Spring Harbor Laboratory Press; all rights reserved.)

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.

We have compiled MultitaskProtDB, available online at http://wallace.uab.es/multitask, to provide a repository where the many multitasking proteins found in the literature can be stored. Multitasking or moonlighting is the capability of some proteins to execute two or more biological functions. Usually, multitasking proteins are experimentally revealed by serendipity. This ability of proteins to perform multitasking functions helps us to understand one of the ways used by cells to perform many complex functions with a limited number of genes. Even so, the study of this phenomenon is complex because, among other things, there is no database of moonlighting proteins. The existence of such a tool facilitates the collection and dissemination of these important data. This work reports the database, MultitaskProtDB, which is designed as a friendly user web page containing >288 multitasking proteins with their NCBI and UniProt accession numbers, canonical and additional biological functions, monomeric/oligomeric states, PDB codes when available and bibliographic references. This database also serves to gain insight into some characteristics of multitasking proteins such as frequencies of the different pairs of functions, phylogenetic conservation and so forth.

Background: Pythium insidiosum is an oomycete classified in the kingdom Stramenopila. P. insidiosum hyphae are not able to initiate infection without the secretion of hydrolytic enzymes, which are considered an important factor in microbial virulence., Aims: To evaluate the extracellular enzymatic activity of 14 Brazilian P. insidiosum isolates and a standard strain (ATCC 58637) by the API-ZYM System screening method., Methods: Zoospores were grown in RPMI 1640 broth, and 65 μL of the liquid phase were inoculated in each cupule of the API-ZYM strips., Results: Differences in the enzymatic activities were observed among the isolates, although phosphohydrolases and ester hydrolases were conspicuous among all isolates. β-glucosidase was also present in most of the isolates. Enzymatic activities of α-glucosidase and chymotrypsin were not observed, differing from a previous study involving Australian isolates and intracellular enzymes., Conclusions: The discrepancy in the enzymatic profile observed among Brazilian P. insidiosum isolates reflects the phenotypic variations found in susceptibility tests., (Copyright © 2012 Revista Iberoamericana de Micología. Published by Elsevier Espana. All rights reserved.)

Heme, which is composed of iron and the small organic molecule protoporphyrin, is an essential component of hemoglobin as well as a variety of physiologically important hemoproteins. During erythropoiesis, heme synthesis is induced before, and is essential for, globin synthesis. Although all cells possess the ability to synthesize heme, there are distinct differences between regulation of the pathway in developing erythroid cells and all other types of cells. Disorders that compromise the ability of the developing red cell to synthesize heme can have profound medical implications. The biosynthetic pathway for heme and key regulatory features are reviewed herein, along with specific human genetic disorders that arise from defective heme synthesis such as X-linked sideroblastic anemia and erythropoietic protoporphyria.

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., (Copyright © 2013 Elsevier Inc. All rights reserved.)

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.

We have developed a new COFACTOR webserver for automated structure-based protein function annotation. Starting from a structural model, given by either experimental determination or computational modeling, COFACTOR first identifies template proteins of similar folds and functional sites by threading the target structure through three representative template libraries that have known protein-ligand binding interactions, Enzyme Commission number or Gene Ontology terms. The biological function insights in these three aspects are then deduced from the functional templates, the confidence of which is evaluated by a scoring function that combines both global and local structural similarities. The algorithm has been extensively benchmarked by large-scale benchmarking tests and demonstrated significant advantages compared to traditional sequence-based methods. In the recent community-wide CASP9 experiment, COFACTOR was ranked as the best method for protein-ligand binding site predictions. The COFACTOR sever and the template libraries are freely available at http://zhanglab.ccmb.med.umich.edu/COFACTOR.

Purpose: Given serious concerns over the adverse effects of enzyme induction, modern nonenzyme-inducing antiepileptic drugs (AEDs) may be preferable, provided they have similar efficacy as enzyme-inducing AEDs. This is currently unclear., Methods: Therefore, we performed a meta-analysis of the evidence to determine the placebo-corrected efficacy of adjunctive treatment with modern nonenzyme-inducing AEDs versus modern enzyme-inducing AEDs that are on the market for refractory focal epilepsy., Key Findings: Of 322 potentially eligible articles reviewed in full text, 129 (40%) fulfilled eligibility criteria. After excluding 92 publications, 37 studies dealing with a total of 9,860 patients with refractory focal epilepsy form the basis for the evidence. The overall weighted pooled-risk ratio (RR) in favor of enzyme-inducing AEDs over placebo was 2.37 (95% confidence interval [CI] 1.77-3.18, p < 0.001) for at least 50% seizure reduction and 4.45 (2.26-8.76, p < 0.001) for seizure freedom. The corresponding weighted pooled RR in favor of nonenzyme-inducing AEDs over placebo was 2.28 (95% CI 2.03-2.57, p < 0.001) for at least 50% seizure reduction and 3.23 (95% CI 2.23-4.67, p < 0.001) for seizure freedom. In a meta-regression analysis in the same sample with at least 50% seizure reduction as outcome, the ratio of RRs for enzyme-inducing AEDs (eight studies) versus nonenzyme-inducing AEDs (29 studies) was 1.01 (95% CI 0.77-1.34, p = 0.92)). Similarly, the ratio of RRs for a seizure-free outcome for enzyme-inducing AEDs (six studies) versus nonenzyme-inducing AEDs (19 studies) was 1.38 (95% CI 0.60-3.16, p = 0.43)., Significance: Although the presence of moderate heterogeneity may reduce the validity of the results and limit generalizations from the findings, we conclude that the efficacy of adjunctive treatment with modern nonenzyme-inducing AEDs is similar to that of enzyme-inducing AEDs. Given the negative consequences of enzyme induction, our data suggest that nonenzyme-inducing AEDs may be useful alternatives to enzyme-inducing AEDs for treatment of refractory focal epilepsy., (Wiley Periodicals, Inc. © 2012 International League Against Epilepsy.)

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.

Ovarian progesterone induces essential changes leading to a temporary state of uterine receptivity for conceptus implantation. Estrogens secreted by the porcine conceptus on days 11 and 12 of pregnancy provide the initial signal for maternal recognition of pregnancy and maintenance of a functional corpus luteum (CL) for continued production of progesterone. As prostaglandins F(2)(α) (PGF(2)(α)) and E(2) (PGE(2)) exert opposing actions on the CL, a tight control over their synthesis and secretion is critical either for the initiation of luteolysis or maintenance of pregnancy. One of the supportive mechanisms by which conceptus inhibits luteolysis is changing PG synthesis in favor of luteoprotective PGE(2). Conceptus PGE(2) could be amplified by PGE(2) feedback loop in the endometrium. In pigs, as in other species, implantation and establishment of pregnancy is associated with upregulation of expression of proinflammatory factors, which include cytokines, growth factors, and lipid mediators. The conceptus produces inflammatory mediators: interferon γ and interferon δ, interleukins IL1B and IL6, and PGs, which probably activate inflammatory pathways in the endometrium. The endometrium responds to these embryonic signals by enhancing further progesterone-induced uterine receptivity. Understanding the mechanisms of pregnancy establishment is required for translational research to increase reproductive efficiencies and fertility in humans and animals.

Background: Several studies have mentioned network modularity-that a network can easily be decomposed into subgraphs that are densely connected within and weakly connected between each other-as a factor affecting metabolic robustness. In this paper we measure the relation between network modularity and several aspects of robustness directly in a model system of metabolism., Methodology/principal Findings: By using a model for generating chemical reaction systems where one can tune the network modularity, we find that robustness increases with modularity for changes in the concentrations of metabolites, whereas it decreases with changes in the expression of enzymes. The same modularity scaling is true for the speed of relaxation after the perturbations., Conclusions/significance: Modularity is not a general principle for making metabolism either more or less robust; this question needs to be addressed specifically for different types of perturbations of the system.

Digesta flow-behavior types in the intestinal lumen, such as turbulent and laminar flow, should define modes of digestion and absorption. This review presents a simulation of flow behavior in the intestinal lumen and discusses the behavior of nutrients and enzymes in the intestinal lumen under laminar-flow conditions. The significance of digesta viscosity for glucose and water absorption and digestion and fermentation in the intestine is also discussed.

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.

This paper develops concepts for assessing and quantifying the regulation of the rate of an enzyme-catalyzed reaction. We show how generic reversible rate equations can be recast in two ways, one making the distance from equilibrium explicit, thereby allowing the distinction between kinetic and thermodynamic control of reaction rate, as well as near-equilibrium and far-from-equilibrium reactions. Recasting in the second form separates mass action from rate capacity and quantifies the degree to which intrinsic mass action contributes to reaction rate and how regulation of an enzyme-catalyzed reaction either enhances or counteracts this mass-action behavior. The contribution of enzyme binding to regulation is analyzed in detail for a number of enzyme-kinetic rate laws, including cooperative reactions.

Alterations in epigenetic processes probably underlie most human malignancies. Novel genome-wide techniques, such as chromatin immunoprecipitation and high-throughput sequencing, have become state-of-the-art methods to map the epigenomic landscape of development and disease, such as in cancers. Despite these advances, the functional significance of epigenetic enzymes in cancer progression, such as prostate cancer, remain incompletely understood. A comprehensive mapping and functional understanding of the cancer epigenome will hopefully help to facilitate development of novel cancer therapy targets and improve future diagnostics. The authors have developed a novel cell microarray-based high-content siRNA screening technique suitable to address the putative functional role and impact of all known putative and novel epigenetic enzymes in cancer, including prostate cancer.

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.

The functional repertoire of a network is determined by its topology. Ma et al. (2009) analyze enzyme networks with three nodes and take a reverse-engineering approach to ask how many core network topologies can establish perfect adaptation, the ability to reset after perturbation. Surprisingly, the answer is just two.

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.

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.

Recent laboratory experiments suggest that a molecule's ability to evolve neutrally is important for its ability to generate evolutionary innovations. In contrast to laboratory experiments, life unfolds on time-scales of billions of years. Here, we ask whether a molecule's ability to evolve neutrally-a measure of its robustness-facilitates evolutionary innovation also on these large time-scales. To this end, we use protein designability, the number of sequences that can adopt a given protein structure, as an estimate of the structure's ability to evolve neutrally. Based on two complementary measures of functional diversity-catalytic diversity and molecular functional diversity in gene ontology-we show that more robust proteins have a greater capacity to produce functional innovations. Significant associations among structural designability, folding rate and intrinsic disorder also exist, underlining the complex relationship of the structural factors that affect protein evolution.

One of the alluring aspects of examining chromatin modifications in the role of modulating transcription required for long-term memory processes is that these modifications may provide transient and potentially stable epigenetic marks in the service of activating and/or maintaining transcriptional processes. These, in turn, may ultimately participate in the molecular mechanisms required for neuronal changes subserving long-lasting changes in behavior. As an epigenetic mechanism of transcriptional control, chromatin modification has been shown to participate in maintaining cellular memory (e.g., cell fate) and may underlie the strengthening and maintenance of synaptic connections required for long-term changes in behavior. Epigenetics has become central to several fields of neurobiology, where researchers have found that regulation of chromatin modification has a significant role in epilepsy, drug addiction, depression, neurodegenerative diseases, and memory. In this review, we will discuss the role of chromatin modifying enzymes in memory processes, as well as how recent studies in yeast genetics and cancer biology may impact the way we think about how chromatin modification and chromatin remodeling regulate neuronal function.

In Escherichia coli and Salmonella typhimurium, L-threonine is cleaved non-oxidatively to propionate via 2-ketobutyrate by biodegradative threonine deaminase, 2-ketobutyrate formate-lyase (or pyruvate formate-lyase), phosphotransacetylase and propionate kinase. In the anaerobic condition, L-threonine is converted to the energy-rich keto acid and this is subsequently catabolised to produce ATP via substrate-level phosphorylation, providing a source of energy to the cells. Most of the enzymes involved in the degradation of L-threonine to propionate are encoded by the anaerobically regulated tdc operon. In the recent past, extensive structural and biochemical studies have been carried out on these enzymes by various groups. Besides detailed structural and functional insights, these studies have also shown the similarities and differences between the other related enzymes present in the metabolic network. In this paper, we review the structural and biochemical studies carried out on these enzymes.

Background: Epigenetic regulators (histone acetyltransferases, methyltransferases, chromatin-remodelling enzymes, etc) play a fundamental role in the control of gene expression by modifying the local state of chromatin. However, due to their recent discovery, little is yet known about their own regulation. This paper addresses this point, focusing on alternative splicing regulation, a mechanism already known to play an important role in other protein families, e.g. transcription factors, membrane receptors, etc., Results: To this end, we compiled the data available on the presence/absence of alternative splicing for a set of 160 different epigenetic regulators, taking advantage of the relatively large amount of unexplored data on alternative splicing available in public databases. We found that 49 % (70 % in human) of these genes express more than one transcript. We then studied their alternative splicing patterns, focusing on those changes affecting the enzyme's domain composition. In general, we found that these sequence changes correspond to different mechanisms, either repressing the enzyme's function (e.g. by creating dominant-negative inhibitors of the functional isoform) or creating isoforms with new functions., Conclusion: We conclude that alternative splicing of epigenetic regulators can be an important tool for the function modulation of these enzymes. Considering that the latter control the transcriptional state of large sets of genes, we propose that epigenetic regulation of gene expression is itself strongly regulated by alternative splicing.

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.

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.

Stress enzymes triggered by transient stress mediate reprioritization of developmental and homeostatic events to flexibly accomplish the next essential developmental event. This review analyzes recent studies on stress and stress enzyme function during early mammalian development and describes the diverse consequences that result from measurement, analysis of function, and management of stress and stress enzymes during development.

Chemical reactions are involved at many stages of the drug design process. This starts with the analysis of biochemical pathways that are controlled by enzymes that might be downregulated in certain diseases. In the lead discovery and lead optimization process compounds have to be synthesized in order to test them for their biological activity. And finally, the metabolism of a drug has to be established. A better understanding of chemical reactions could strongly help in making the drug design process more efficient. We have developed methods for quantifying the concepts an organic chemist is using in rationalizing reaction mechanisms. These methods allow a comprehensive modeling of chemical reactivity and thus are applicable to a wide variety of chemical reactions, from gas phase reactions to biochemical pathways. They are empirical in nature and therefore allow the rapid processing of large sets of structures and reactions. We will show here how methods have been developed for the prediction of acidity values and of the regioselectivity in organic reactions, for designing the synthesis of organic molecules and of combinatorial libraries, and for furthering our understanding of enzyme-catalyzed reactions and of the metabolism of drugs.

The BRENDA (BRaunschweig ENzyme DAtabase) enzyme information system (http://www.brenda.uni-koeln.de) is the largest publicly available enzyme information system worldwide. The major parts of its contents are manually extracted from primary literature. It is not restricted to specific groups of enzymes, but includes information on all identified enzymes irrespective of the enzyme's source. The range of data encompasses functional, structural, sequence, localisation, disease-related, isolation, stability information on enzyme and ligand-related data. Each single entry is linked to the enzyme source and to a literature reference. Recently the data repository was complemented by text-mining data in AMENDA (Automatic Mining of ENzyme DAta) and FRENDA (Full Reference ENzyme DAta). A genome browser, membrane protein prediction and full-text search capacities were added. The newly implemented web service provides instant access to the data for programmers via a SOAP (Simple Object Access Protocol) interface. The BRENDA data can be downloaded in the form of a text file from the beginning of 2007.

Meridamycin is a non-immunosuppressant, FKBP-binding macrocyclic polyketide, which has major potential as a neuroprotectant in a range of neurodegenerative disorders including dementia, Parkinson's disease and ischaemic stroke. A biosynthetic cluster predicted to encode biosynthesis of meridamycin was cloned from the prolific secondary-metabolite-producing strain Streptomyces sp. DSM 4137, not previously known to produce this compound, and specific gene deletion was used to confirm the role of this cluster in the biosynthesis of meridamycin. The meridamycin modular polyketide synthase consists of 14 extension modules distributed between three giant multienzyme proteins. The terminal module is flanked by a highly unusual cytochrome P450-like domain. The characterization of the meridamycin biosynthetic locus in this readily manipulated streptomycete species opens the way to the engineering of new, altered meridamycins of potential therapeutic importance.

Over the last several decades, research on snake venom toxins has provided not only new tools to decipher molecular details of various physiological processes, but also inspiration to design and develop a number of therapeutic agents. Blood circulation, particularly thrombosis and haemostasis, is one of the major targets of several snake venom proteins. Among them, anticoagulant proteins have contributed to our understanding of molecular mechanisms of blood coagulation and have provided potential new leads for the development of drugs to treat or to prevent unwanted clot formation. Some of these anticoagulants exhibit various enzymatic activities whereas others do not. They interfere in normal blood coagulation by different mechanisms. Although significant progress has been made in understanding the structure-function relationships and the mechanisms of some of these anticoagulants, there are still a number of questions to be answered as more new anticoagulants are being discovered. Such studies contribute to our fight against unwanted clot formation, which leads to death and debilitation in cardiac arrest and stroke in patients with cardiovascular and cerebrovascular diseases, arteriosclerosis and hypertension. This review describes the details of the structure, mechanism and structure-function relationships of anticoagulant proteins from snake venoms.

Lysins are murein hydrolases produced by bacteriophage that act on the bacterial host cell wall to release progeny phage. When added extrinsically in their purified form, these enzymes produce total lysis of susceptible Gram-positive bacteria within seconds, suggesting a unique antimicrobial strategy. All known Gram-positive lysins are produced as a single polypeptide containing a catalytic activity domain, which cleaves one of the four major peptidoglycan bonds, and a cell-wall-binding domain, which may bind a species-specific carbohydrate epitope in the cell wall. Here, we have cloned and expressed a unique lysin from the streptococcal bacteriophage C(1), termed PlyC. Molecular characterization of the plyC operon reveals that PlyC is, surprisingly, composed of two separate gene products, PlyCA and PlyCB. Based on biochemical and biophysical studies, the catalytically active PlyC holoenzyme is composed of eight PlyCB subunits for each PlyCA. Inhibitor studies predicted the presence of an active-site cysteine, and bioinformatic analysis revealed a cysteine, histidine-dependent amidohydrolase/peptidase domain within PlyCA. Point mutagenesis confirmed that PlyCA is responsible for the observed catalytic activity, and Cys-333 and His-420 are the active-site residues. PlyCB was found to self-assemble into an octamer, and this complex alone was able to direct streptococcal cell-wall-specific binding. Similar to no other proteins in sequence databases, PlyC defines a previously uncharacterized structural family of cell-wall hydrolases.

Values of enzyme kinetic parameters are a key requisite for the kinetic modelling of biochemical systems. For most kinetic parameters, however, not even an order of magnitude is known, so the estimation of model parameters from experimental data remains a major task in systems biology. We propose a statistical approach to infer values for kinetic parameters across species and enzymes making use of parameter values that have been measured under various conditions and that are nowadays stored in databases. We fit the data by a statistical regression model in which the substrate, the combination enzyme-substrate and the combination organism-substrate have a linear effect on the logarithmic parameter value. As a result, we obtain predictions and error ranges for unknown enzyme parameters. We apply our method to decadic logarithmic Michaelis-Menten constants from the BRENDA database and confirm the results with leave-one-out crossvalidation, in which we mask one value at a time and predict it from the remaining data. For a set of 8 metabolites we obtain a standard prediction error of 1.01 for the deviation of the predicted values from the true values, while the standard deviation of the experimental values is 1.16. The method is applicable to other types of kinetic parameters for which many experimental data are available.