Reductionism in the study of enzyme adaptation.

One of the principal goals of comparative biology is the elucidation of mechanisms by which organisms adapt to different environments. The study of enzyme structure, function, and stability has contributed significantly to this effort, by revealing adaptation at a molecular level. Comparative biochemistry, including enzymology, necessarily pursues a reductionist approach in describing the function and structure of biomolecules, allowing more straightforward study of molecular systems by removing much of the complexity of their biological milieu. Although this reductionism has allowed a remarkable series of discoveries linking chemical processes to metabolism and to whole-organism function in the context of the environment, it also has the potential to mislead when careful consideration is not made of the simplifying assumptions inherent to such research. In this review, a brief history of the growth of enzymology, its reliance on a reductionist philosophy, and its contributions to our understanding of biological systems is given. Examples then are provided of research techniques, based on a reductionist approach, that have advanced our knowledge about enzyme adaptation to environmental stresses, including stability assays, enzyme kinetics, and the impact of solute composition on enzyme function. In each case, the benefits of the reductionist nature of the approach is emphasized, notable advances are described, but potential drawbacks due to inherent oversimplification of the study system are also identified.

Lytic polysaccharide monooxygenases and other histidine-brace copper proteins: structure, oxygen activation and biotechnological applications.

Lytic polysaccharide monooxygenases (LPMOs) are mononuclear copper enzymes that catalyse the oxidative cleavage of glycosidic bonds. They are characterised by two histidine residues that coordinate copper in a configuration termed the Cu-histidine brace. Although first identified in bacteria and fungi, LPMOs have since been found in all biological kingdoms. LPMOs are now included in commercial enzyme cocktails used in industrial biorefineries. This has led to increased process yield due to the synergistic action of LPMOs with glycoside hydrolases. However, the introduction of LPMOs makes control of the enzymatic step in industrial stirred-tank reactors more challenging, and the operational stability of the enzymes is reduced. It is clear that much is still to be learned about the interaction between LPMOs and their complex natural and industrial environments, and fundamental scientific studies are required towards this end. Several atomic-resolution structures have been solved providing detailed information on the Cu-coordination sphere and the interaction with the polysaccharide substrate. However, the molecular mechanisms of LPMOs are still the subject of intense investigation; the key question being how the proteinaceous environment controls the copper cofactor towards the activation of the O-O bond in O2 and cleavage of the glycosidic bonds in polysaccharides. The need for biochemical characterisation of each putative LPMO is discussed based on recent reports showing that not all proteins with a Cu-histidine brace are enzymes.

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).

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.

Limits to a classic paradigm: most transcription factors in E. coli regulate genes involved in multiple biological processes.

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.

A Bird's-Eye View of Enzyme Evolution: Chemical, Physicochemical, and Physiological Considerations.

Enzymes catalyze a vast range of reactions. Their catalytic performances, mechanisms, global folds, and active-site architectures are also highly diverse, suggesting that enzymes are shaped by an entire range of physiological demands and evolutionary constraints, as well as by chemical and physicochemical constraints. We have attempted to identify signatures of these shaping demands and constraints. To this end, we describe a bird's-eye view of the enzyme space from two angles: evolution and chemistry. We examine various chemical reaction parameters that may have shaped the catalytic performances and active-site architectures of enzymes. We test and weigh these considerations against physiological and evolutionary factors. Although the catalytic properties of the "average" enzyme correlate with cellular metabolic demands and enzyme expression levels, at the level of individual enzymes, a multitude of physiological demands and constraints, combined with the coincidental nature of evolutionary processes, result in a complex picture. Indeed, neither reaction type (a chemical constraint) nor evolutionary origin alone can explain enzyme rates. Nevertheless, chemical constraints are apparent in the convergence of active-site architectures in independently evolved enzymes, although significant variations within an architecture are common.

Compositional and functional investigation of individual and pooled venoms from long-term captive and recently wild-caught Bothrops jararaca snakes.

Intraspecific venom variability has been extensively reported in a number of species and is documented to be the result of several factors. However, current evidence for snake venom variability related to captivity maintenance is controversial. Here we report a compositional and functional investigation of individual and pooled venoms from long-term captive (LTC) and recently wild-caught (RWC) B. jararaca snakes. The composition of individual venoms showed a remarkable variability in terms of relative abundance of toxins (evidenced by 1-DE and RP-HPLC), enzymatic activities (proteolytic, PLA2, and LAAO) and coagulant activity, even among captive specimens. Thus, no compositional and functional pattern could be established to assign each individual venom to a specific group. Conversely, pooled venom from LTC and RWC snakes showed no significant differences regarding protein composition (characterized by 1-DE and shotgun proteomics), enzymatic activities (proteolytic, PLA2 and LAAO) and biological function (coagulant, hemorrhagic and lethal activities), except for edematogenic activity, which was more prominent in RWC venom pool. Additionally, both pooled venoms displayed similar immunoreactivity with the bothropic antivenom produced by Instituto Butantan. Taken together, our results highlight the complexity and the high intraspecific variation of B. jararaca venom, that is not influenced at a discernible extent by captivity maintenance. BIOLOGICAL SIGNIFICANCE: Bothrops jararaca snakes are one of the main causes of snakebites in Southeastern Brazil. Due to its medical interest, the venom of this species is the most studied and characterized among Brazilian snakes and captive B. jararaca specimens are maintained for long periods of time in our venom production facility. However, knowledge on the influence of captivity maintenance on B. jararaca venom variability is scarce. In this report, we described a high compositional and functional variability of individual venoms from LTC and RWC B. jararaca snakes, which are not observed between LTC and RWC pooled venoms. This intraspecific variability is more likely to be due to genetic/populational differences rather than "captivity vs wild" conditions. In this regard, data generated by the present work support the use of venom from captive and wild snakes for antivenom production and scientific research. Moreover, the data generated by this study highlight the importance of analyzing individual venom samples in studies involving intraspecific venom variability.

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.

Advances in enzyme bioelectrochemistry.

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.

CR2Cancer: a database for chromatin regulators in human cancer.

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.

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.

Advances in enzyme bioelectrochemistry

ABSTRACT 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.

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 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.

Investigating Information Dynamics in Living Systems through the Structure and Function of Enzymes.

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.

Analytic derivation of bacterial growth laws from a simple model of intracellular chemical dynamics.

Experiments have found that the growth rate and certain other macroscopic properties of bacterial cells in steady-state cultures depend upon the medium in a surprisingly simple manner; these dependencies are referred to as 'growth laws'. Here we construct a dynamical model of interacting intracellular populations to understand some of the growth laws. The model has only three population variables: an amino acid pool, a pool of enzymes that transport an external nutrient and produce the amino acids, and ribosomes that catalyze their own and the enzymes' production from the amino acids. We assume that the cell allocates its resources between the enzyme sector and the ribosomal sector to maximize its growth rate. We show that the empirical growth laws follow from this assumption and derive analytic expressions for the phenomenological parameters in terms of the more basic model parameters. Interestingly, the maximization of the growth rate of the cell as a whole implies that the cell allocates resources to the enzyme and ribosomal sectors in inverse proportion to their respective 'efficiencies'. The work introduces a mathematical scheme in which the cellular growth rate can be explicitly determined and shows that two large parameters, the number of amino acid residues per enzyme and per ribosome, are useful for making approximations.

Mechanisms of Lung Fibrosis Resolution.

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.

[Metabolic correction: a biochemical option against diseases]. / Corrección metabólica: Una opción bioquímica contra las enfermedades.

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.