Is it a valid generalization that kinases catalyse reactions involving energy transfer and utilization?

Is it a valid generalization that kinases catalyse reactions involving energy transfer and utilization?

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The Wikipedia entry for kinase states that "a kinase is an enzyme that catalyzes the transfer of phosphate groups from high-energy, phosphate-donating molecules [such as ATP] to specific substrates".

ATP is the energy currency of the cell, so, would it be accurate to say that a kinase catlayses reactions involving energy transfer and utilization within a cell?


  • It is not possible to suggest a verbal or pictorial generalization of the role of kinases.
  • It is futile to try to do so as it is incorrect to think that kinases have a single general role of the type suggested, or that the utilization of free energy from ATP is limited to reactions catalysed by kinases.


Kinase is a surviving trivial name for enzymes that have been classified by IUBMB as ATP phosophotransferases. The categorization solely reflects aspects the chemistry of the reaction catalysed, and the sub-categorization in terms of substrate relects a diversity of roles. Moreover such kinase reactions are only one way in which the free energy of hydrolysis of the phosopho-diester bond of ATP can be utilized - transfer of the phosphoryl group to another molecule. Other types of reaction (and enzyme) are just as, if not more, important.

The diversity of roles played by kinases

I list at random some examples of different types of kinase reactions:

  1. Hexokinase transfers phosphate from ATP to glucose. One purpose is to creaate a charged molecule, glucose 6-phosphate, that cannot go back across the cell membrane.
  2. Thymidine kinase converts thymidine to TMP. Like several other kinases it can be thought of as catalysing a synthetic reaction, the phosphate being a part of the structure of the TMP (and ultimately TPP) molecules.
  3. Protein kinases transfer phosphate to serine, threonine or tyrosine residues of proteins. This is not using ATP for an energetic process, but to cause a change in the structure of the target protein that modulates its activity.
  4. Creatine kinase interconverts creatine and ATP with creatine phosphate (a rapidly mobilizable energy store in muscle) and ADP. As the reaction is reversible it can be thought as either catalysing the formation of creatine phosphate or its mobilization.
  5. Pyruvate kinase is a similar to 4 in that it produces ATP, and as the reaction it catalyses is essentially irreversible in the cell, the name is quite misleading about its function.

Non-kinase enzymes involved in utilizing ATP

These include ATPases, as @BryanKrause remarks, but also some others. Again, some examples at random:

  1. Sodium /Potassium ATPase catalyses active cation transport.
  2. Firefly luciferase (an oxidase) hydroyses ATP to produce light.
  3. Glutamine sythetase (glutamate-ammonia ligase) uses the free-energy of hydrolysis of ATP to convert glutamate and ammonia to glutamine.

Your (original) description:

a kinase helps chemically deliver or metabolize stored energy within a cell

sounds a little more like what many ATPases do: they are using the energy from ATP to do some energetically unfavorable work, such as moving molecules or ions against their concentration gradients. However, kinases have a broad range of different functions.

In some anabolic pathways, yes, kinases are helping to deliver stored energy in the form of phosphate groups onto 'building blocks' of other molecules, and this stored energy can be used for future reactions.

However, when a kinase phosphorylates another molecule (often a protein) to regulate its function, I wouldn't really say that it is delivering energy, just that there is some energy cost to doing the business of flipping cellular light switches, and ATP is readily available as a source to do that. One big advantage of using kinases in these sorts of reactions is that, because a fairly large energy input is required, such reactions don't occur easily by mistake or just due to thermal energy.

Chapter 6 - Membrane bioreactors

Membrane bioreactors (MBRs) combine a membrane system with a biological reaction offering a unique opportunity to restrict the physical space of a biocatalyst, which can be an enzyme, a microorganism or a plant/animal cell. Due to this broad range of biological reactions, the modeling of such MBR systems can be rather different, depending on the biological process taking place. Therefore, this chapter discusses how the different characteristics and complexities of internal MBR processes affect the choice between mechanistic and multivariate statistical models. In many situations, relatively simple mechanistic models can be used, such as in enzymatic bioreactors. However, in complex systems, such as in MBRs for wastewater treatment, particularly when process monitoring and control is envisage, the multivariate statistical modeling approach may become more useful. Considering the bright future of MBRs, modeling requirements will be challenging and will require open-minded approaches.

Chapter 1 Thermodynamics and the regulation of cell functions

This chapter discusses the thermodynamics and the regulation of cell functions. A free-energy transducer may have excess input free-energy available to it. Largely, biochemistry has been successful because it dissected the complex cellular system into smaller parts that could then be analyzed and understood. However, the way back, from understood elemental process to an understanding of the entire cellular system, has remained almost untrodden. The collection of phenomena often called “cellular signal transduction” constitutes an example of a hierarchical (modular) system. Typically, an extracellular signaler binds to a membrane receptor and, for instance, may cause dimerization of the latter. This is a pathway of chemical processes and constitutes one level in the hierarchy. Metabolic and hierarchic control analyses discuss the magnitude of control coefficients. These are defined as the effect of very small changes in parameters on system properties. In the reality of biological regulation, changes are often not very small.

Mechanism and Catalysis of Nucleophilic Substitution in Phosphate Esters

The chapter discusses the various mechanism and catalysis of nucleophilic substitution in phosphate esters. The mechanism of substitution reactions of phosphate esters and related compounds has been the subject of many significant recent investigations. The reason for this interest can be traced to the biochemical significance of phosphate esters and their applications. These materials are utilized in metabolism and genetic processes, and energy is released upon their hydrolysis. Yet in the absence of enzymes, they appear almost inert. The means by which their reactivity is enhanced by an enzyme continues to be a challenging problem for mechanistic investigation. This challenge requires, as a background, an assured knowledge of the reaction mechanisms of these materials in the absence of enzymes and the means by which catalysis can be achieved. Various investigations involving kinetics, stereochemistry, isotope effects, magnetic resonance, theory, and other techniques have been dealt with in this area.

Is it a valid generalization that kinases catalyse reactions involving energy transfer and utilization? - Biology

Glutathione-dependent catalysis is a metabolic adaptation to chemical challenges encountered by all life forms. In the course of evolution, nature optimized numerous mechanisms to use glutathione as the most versatile nucleophile for the conversion of a plethora of sulfur-, oxygen- or carbon-containing electrophilic substances.

Scope of review

This comprehensive review summarizes fundamental principles of glutathione catalysis and compares the structures and mechanisms of glutathione-dependent enzymes, including glutathione reductase, glutaredoxins, glutathione peroxidases, peroxiredoxins, glyoxalases 1 and 2, glutathione transferases and MAPEG. Moreover, open mechanistic questions, evolutionary aspects and the physiological relevance of glutathione catalysis are discussed for each enzyme family.

Major conclusions

It is surprising how little is known about many glutathione-dependent enzymes, how often reaction geometries and acid–base catalysts are neglected, and how many mechanistic puzzles remain unsolved despite almost a century of research. On the one hand, several enzyme families with non-related protein folds recognize the glutathione moiety of their substrates. On the other hand, the thioredoxin fold is often used for glutathione catalysis. Ancient as well as recent structural changes of this fold did not only significantly alter the reaction mechanism, but also resulted in completely different protein functions.

General significance

Glutathione-dependent enzymes are excellent study objects for structure–function relationships and molecular evolution. Notably, in times of systems biology, the outcome of models on glutathione metabolism and redox regulation is more than questionable as long as fundamental enzyme properties are neither studied nor understood. Furthermore, several of the presented mechanisms could have implications for drug development. This article is part of a Special Issue entitled Cellular functions of glutathione.


► Fundamental principles of glutathione catalysis are summarized. ► Mechanisms of enzymes with five non-related protein folds are compared. ► Evolutionary aspects and open mechanistic questions are discussed. ► The physiological relevance of glutathione catalysis is highlighted.


Heme, or protoporphyrin IX, is an iron (III)-containing porphyrin cofactor for a large number of liver microsomal mixed function oxygenases principally in the cytochrome P450 family of enzymes. These enzymes, like flavin monooxygenases, are important in the metabolism of xenobiotics, including drugs. As in the case of the flavin monooxygenases, molecular oxygen binds to the heme cofactor (after reduction of the Fe 3+ to Fe 2+ ), and is converted into a reactive form that is used in a variety of oxygenation reactions, especially hydroxylation and epoxidation reactions. The hydroxylation reactions often occur at seemingly inactivated C atoms. In heme, the peripheral nitrogens represent the 4 pyrrole nitrogens. The axial ligands in the case of CYP450 are a cysteine thiolate from the protein and water. The electrons for reduction of the heme of CYP-450 (the 2 nd and 4 th steps of 4.35) come from an enzyme complexed with CYP450 called NADPH-cytochrome P450 reductase, which contains NADPH and 2 different flavin coenzymes (FAD and FMN) [36] (Figure 25).

Heme is an essential molecule found in many tissues where it plays key roles as the prosthetic group of several proteins involved in vital physiological and metabolic processes such as gas and electron transport. Structurally, heme is a tetrapyrrole ring containing an atom of iron (Fe) in its center. When released into the extracellular milieu, heme exerts several deleterious effects, which make it an important player in infectious and noninfectious hemolytic diseases where large amounts of free heme are observed such as malaria, dengue fever, β-thalassemia, sickle cell disease and ischemia-reperfusion. The heme degradation by HMOX1/HO-1 (heme oxygenase 1) is required and that Fe is essential for the formation of ALIS, as heme analogs lacking the central atom of Fe are not able to induce these structures. ALIS formation is also observed in vivo, in a model of phenylhydrazine (PHZ)-induced hemolysis, indicating that it is an integral part of the host response to excessive free heme and that it may play a role in cellular homeostasis [37].

Flavin-containing monooxygenases (FMOs) also metabolize foreign chemicals, including drugs, pesticides and dietary components. The mechanism of action of FMOs and insights gained from the structure of yeast FMO. The three FMOs (FMOs 1, 2 and 3) that is most important for metabolism of foreign chemicals in humans, focusing on the role of the FMOs and their genetic variants in disease and drug response. Loss-of-function mutations of FMO3 cause the disorder trimethylaminuria [38]. Flavin-containing monooxygenases (FMOs) also catalyze NADPH- dependent monooxygenation of soft-nucleophilic nitrogen, sulfur, and phosphorous atoms contained within various drugs, pesticides, and xenobiotics. Flavin-containing monooxygenase 3 (FMO3) is responsible for the majority of FMO-mediated xenobiotic metabolism in the adult human liver. Mutations in the FMO3 gene can result in defective trimethylamine (TMA) N-oxygenation, which gives rise to the disorder known as trimethylaminuria (TMAU) or ''fish-odour syndrome''[39].


Most of the time the cell is vibrant with chemical activity. Dormancy – the condition of the spore or the seed – is a state that lies in limbo, not dead but not quite alive. Life has to go forward. It begins with the chemical transformations which make the root of metabolism. At the ground level of life, we find dynamic transformations that extract compounds from the environment, process them into the cell's building blocks and energy supply, while discarding what is toxic or cannot be used. Continuously improved by genomic studies, a comprehensive descriptive knowledge of the matching pathways is available in textbooks and databases that provide access to all what we would like to ask about metabolism (perhaps excluding what we failed to notice). This provides us with a description of the basic chemical transformations that continuously unfold in cells. They look smooth while certainly sophisticated. Yet, as in all dynamic processes, especially those involving multiple stages, things must sometimes go awry: even metabolites must be repaired (Danchin et al., 2011 ). Despite their name, accidents are the rule, not the exception. In a famous book, Charles Perrow explored the inevitability of accidents, events that are not foreseen individually, that may be separately thought to happen extremely rarely, but that are doomed to happen sometime, and that he named for that reason ‘normal’ accidents (Perrow, 1984 ). In the case of the cell's metabolism, this is illustrated by the fact that molecules will inevitably be produced or modified out of the anticipated pathways. For example, metabolites become accidentally oxidized or alkylated. Furthermore, there will always be some shadow accompanying core metabolism, with reactions going off the right track, resulting in variations on the theme of normal metabolism, participating in what was named ‘underground’ metabolism (D'Ari and Casadesus, 1998 ) and more recently ‘paralogous’ metabolism (Chan et al., 2014 ). The latter term was proposed to illustrate the likely involvement of enzymes that were paralogues of those involved in normal metabolism as a ready-made way to cope with metabolites that were chemical variants of the normal compounds. Many processes contribute to the way core metabolism goes astray. Rather than follow the logic of metabolism (Danchin and Sekowska, 2014 ), which is essentially based on a combination of chemistry, physics and geology, I explore here widely used genomic resources as well as recent articles to try and identify trends in the way cells cope with chemical accidents. Obviously, it is impossible to explore all the chemical combinations that may have some importance in the cell's life. Here, I propose some tracks that I hope will be useful to genome-related research, via identification of solutions found by living organisms to cope with ‘normal’ accidents during the course of evolution. In order to help future genome annotators to discover unsuspected functions, I split the structure of accidents into two main topics: those resulting from radicals and those resulting from other reactive intermediates (involved in ageing and senescence in particular). In the following, I illustrate the way bacteria cope with reactive molecules with a few concrete examples based on genome studies. The way I proceed may be used for further genome functional exploration, starting, for example, from the list of reactive molecules proposed by Hanson and co-workers (Lerma-Ortiz et al., 2016 ). I have tried, as much as possible, to go back in time and provide reference to early work that, to my knowledge, has not been followed up but might be enlightening for future genome annotation and genome-driven experiments.

Life is change. To study and understand life, it is necessary to study genes, proteins or metabolites and networks thereof in static conditions, but this is not sufficient. Instead, we must learn to handle the dynamic action. Systems biology has been defined in many different ways, always claiming that its new quality compared to traditional biology is the analysis of systems and the interactions of their parts. One important direction in this approach is the integrated investigation of dynamic biological systems by experimental techniques and mathematical modelling.

Yeast is an ideal model organism for the integrated experimental and theoretical approach. It is harmless and easy to cultivate it can be manipulated without ethical problems. Moreover, it is a eukaryote with extensive homology to higher organisms in many aspects. These advantages induce another advantage: since it is a highly employed laboratory organism, a vast amount of qualitative and quantitative data are available, ranging from detailed information about individual genes, proteins or pathways to complete DNA sequences (e.g. for Saccharomyces cerevisiae 31 and Schizosaccharomyces pombe 122 ) or gene expression datasets for all genes under various conditions 25 , 27 , 101 . These data, combined with a number of open questions and unresolved problems, are promising pre-conditions for modelling approaches. In addition, the open mind of the yeast community towards modelling induced the production of further data specifically produced for model quantification and testing 46 , 72 .

Modelling of biochemical networks can help to integrate experimental knowledge into a coherent picture and to test, support or falsify hypotheses about the underlying biological mechanisms. The behaviour of complex systems is often hard to grasp by intuition, because our reasoning tends to follow simple causal chains: if feedback cycles come into play, or if the relative timing of processes makes a difference, then mathematical simulation may be more reliable than mere intuition. Modelling emphasizes the holistic aspects of signalling networks, which disappear if the components are studied separately in different ‘wet labs’ around the globe. Furthermore, once a model has been established, it can be used to test hypotheses or simulate experiments that would be hard or impossible to do in the laboratory.

Modelling itself is useful as a process, even if the resulting model is not satisfactory. It forces abstract thinking and the extraction of essential features of a process. It highlights aspects where our understanding of a matter is wrong or insufficient. It facilitates a unique description of our current knowledge–and of the gaps therein.

For the actual construction of a model, three major directions of discovery have been formulated: bottom-up, top-down and middle-out (term credited to Sydney Brenner, in Noble 76 ). For dynamic models, the bottom-up approach is still prevalent, thanks to the complexity of the systems and to the fact that even the behaviour of individual pathways is rarely understood. The dynamics of small systems, say a set of a few metabolic reactions, are not trivial even less trivial are large networks. Although the vision of a virtual cell is still around, this aim is not close, even for yeast. In general, successful dynamic modelling contains the following ingredients (Figure 1): first, formulation of a problem to solve (no problem, no useful model!) second, construction of a network or wiring scheme for the process and formulation of a set of mathematical equations, usually ordinary differential equations third, model validation (can the model, in principle, give an answer to the posed questions?) and model verification (determine the parameters from experimental data and try to reproduce the input data) and last but not least, the prediction of new features, especially of experimentally testable effects, such as deletion or overexpression mutants, the outcome of changing experimental conditions or the effect of certain perturbations.

Modelling pipeline: schematic representation of customary steps in the development of dynamics models exemplified for an ODE model of osmotic stress response 58

Cellular life combines various different biochemical processes, which have been considered separately in experimental research and in theoretical model building. These processes include metabolism, signalling, gene expression and the cell cycle. We will briefly describe these, highlight their differences and then discuss various models and their abilities to give new insights. First, however, the mathematical techniques and methods commonly used will be outlined.


ATP-binding cassette (ABC) transporters constitute a ubiquitous superfamily of integral membrane proteins that are responsible for the ATP-powered translocation of many substrates across membranes. The highly conserved ABC domains of ABC transporters provide the nucleotide-dependent engine that drives transport. By contrast, the transmembrane domains that create the translocation pathway are more variable. Recent structural advances with prokaryotic ABC transporters have provided a qualitative molecular framework for deciphering the transport cycle. An important goal is to develop quantitative models that detail the kinetic and molecular mechanisms by which ABC transporters couple the binding and hydrolysis of ATP to substrate translocation.


Abscission is the developmental mechanism by which plants are able to shed damaged and excessively formed organs, regulating the metabolic energy required to successfully attain the formation of vegetative and reproductive structures [1]. Abscission encompasses a complex but precise regulation of cell separation that occurs in a specific layer of specialized cells known as abscission zone (AZ) and is simultaneously activated by and responsive to endogenous and exogenous signals, such as abiotic and biotic interactions or exposure to chemical molecules [2, 3]. Once the AZ is properly differentiated, AZ cells acquire competence to respond to triggering-abscission signals through hormone-mediated pathways. After the activation phase, by modulating the expression of genes involved, among others, in cell wall (CW) remodeling and protein metabolism, and a high number of transcription factors, cell separation and differentiation of a protective layer on the proximal side after organ detachment advance as last steps of the abscission process [4, 5]. According to the currently accepted model, the endogenous flow level of inhibitory auxin in an organ destined to abscise must drop to acquire sensitivity to ethylene [6, 7]. Abscisic acid (ABA) is involved by acting as modulator of 1-aminocyclopropane-1-carboxylic acid (ACC) levels, and therefore of ethylene biosynthesis [8]. Increased ethylene biosynthesis is associated with the final events of abscission activation, namely by promoting CW disassembly-related genes transcription [9, 10]. Increased levels of reactive oxygen species (ROS) have a pivotal role in organ abscission control, encompassing multiple steps of signaling, downstream from ethylene, and associated with ROS-sugar-hormone cross talk [11–14].

In reproductive organs, abscission is also related to lower carbohydrate and polyamine (PA) availability to developing flowers and fruits [15–18]. Together with its role as energy source, glucose acts as a repressing signal of programmed cell death (PCD) [19]. A glucose gradient in the AZ was recently suggested, similar to the auxin flux that regulates ethylene signaling [2]. In addition, the inflorescence deficient in abscission (IDA) peptide signals and interacting receptor-like-kinases, HAESA and HAESA-like2, were showed to activate mitogen-activated protein kinase (MAPK) cascades leading to the abscission of floral organs in Arabidopsis thaliana L. [20, 21], in a signaling system that was proposed to be conserved and regulate cell separation in other plant species [22].

Strategies that stimulate flower and fruit abscission are widespread horticultural practices, collectively known as thinning. In seedless table grape (Vitis vinifera L.) production, reduction of the number of berries per bunch is mandatory to guarantee bunch quality and decrease fungal diseases incidence [23]. Gibberellic acid (GAc) spraying during bloom, often followed by hand adjustments, is the most common method for thinning in grapevine [23–27], although the mechanisms by which GAc induces abscission remains largely unknown. Gibberellin (GA) perception and signaling investigated in model plants [28] disclosed early recognition via the GA INSENSITIVE DWARF1 (GID1) receptor and interaction between GA-GID complex and DELLA transcription factor responsible for GA signaling repression. Binding of GA-GID1 to DELLA induces recognition of DELLA for ubiquitination by a specific F-box protein (GID2) that results in a rapid degradation of DELLAs via the ubiquitin-proteasome pathway. Recently, GA-induced changes in the transcriptome of pre-bloom inflorescences and of berry enlargement stages in grapevine were investigated [29, 30] and the results suggested that GAc application to grape flowers and berries has a fairly comprehensive impact on their metabolism mediated by hormone biosynthesis and signaling, in particular through a negative feedback regulation of GAs biosynthesis and signaling [29, 30].

Flower abscission can also be boosted by shading conditions (70-90 % light interception) during bloom [12, 31, 32], paving the way to explore light management as an alternative thinning method. The pronounced reduction of net photosynthetic rates under shading promotes the competition for photoassimilates between vegetative and reproductive organs, leading to shedding of the later with less sink strength at this early stage of development [33]. Shade-induced changes in the transcriptome of apple (Malus × domestica) revealed that photosynthesis repression and associated nutrient stress is perceived at the fruit level, its growth is inhibited by a sugar transport blockage, resulting in a decreased auxin transport to the AZ and concomitant increased sensitivity to ethylene, leading to fruit abscission [18].

Therefore, abscission is a challenging biological question that can be induced by at least two distinct stimuli with distinct physiological basis. Recently, using an experimental assay with potted seeded vines managed under a greenhouse hydroponic production system, and thinned with GAc spraying or via shade nets to reduce intercepted light, we established an efficient method to produce sample sets with predictable abscising potential triggered by different (chemical and environmental) cues, which allowed us to disclose the participation of different metabolic pathways according to the imposed treatment in flower abscission regulation [12]. We now report the effect of the same abscission-inducers using a different genetic background under field conditions. The rationale was that, by using a seedless variety deprived of the main endogenous source of bioactive GAs [34] and developed while adapting to field multiple stresses, the major signals for abscission triggering would be perceived, providing new insights on this subject. Hence, comprehensive cutting-edge metabolomics, RNA-Seq transcriptomics and physiological measurements, were performed to allow discussing how environmental (C-shortage) and GAc application act to trigger flower abscission, to identify routes linking the aptitude of an organ to become competent for cell separation and specificities and communication between different pathways leading to organ drop. In addition, the present study provides the first sequential transcriptomic atlas of GAc-induced flower abscission.


We would like to thank Nicole Buan for providing the rpoA1 external standard mRNA. This work was supported by a National Science Foundation Grant (MCB0517419) to W.W.M. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. We would also like to thank Dr Michael Rother for sharing data and useful discussions.

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