BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. In parallel to the terms ‘transcriptome’ and ‘proteome’, the set of metabolites synthesized by a biological system constitute its ‘metabolome’. Yet, unlike other functional genomics approaches, the unbiased simultaneous identification and quantification of plant metabolomes has been largely neglected. Until recently, most analyses were restricted to profiling selected classes of compounds, or to fingerprinting metabolic changes without sufficient analytical resolution to determine metabolite levels and identities individually. As a prerequisite for metabolomic analysis, careful consideration of the methods employed for tissue extraction, sample preparation, data acquisition, and data mining must be taken. In this review, the differences among metabolite target analysis, metabolite profiling, and metabolic fingerprinting are clarified, and terms are defined. Current approaches are examined, and potential applications are summarized with a special emphasis on data mining and mathematical modelling of metabolism.

https://link.springer.com/content/pdf/10.1023%2FA%3A1013713905833.pdf

Metabolomics - the link between genotypes and phenotypes

Molybdenum is the only second-row transition metal required by most living organisms, and is nearly universally distributed in biology. Enzymes containing molybdenum in their active sites have long been recognized,1 and at present over 50 molybdenum-containing enzymes have been purified and biochemically characterized; a great many more gene products have been annotated as putative molybdenum-containing proteins on the basis of genomic and bioinformatic analysis.2 In certain cases, our understanding of the relationship between enzyme structure and function is such that we can speak with confidence as to the detailed nature of the reaction mechanism and, with the availability of high-resolution X-ray crystal structures, the specific means by which transition states are stabilized and reaction rate is accelerated within the friendly confines of the active site. At the same time, our understanding of the biosynthesis of the organic cofactor that accompanies molybdenum (variously called molybdopterin or pyranopterin), the manner in which molybdenum is incorporated into it, and then further modified as necessary prior to insertion into apoprotein has also (in at least some cases) become increasingly well understood.

It is now well-established that all molybdenum-containing enzymes other than nitrogenase (in which molybdenum is incorporated into a [MoFe7S9] cluster of the active site) fall into three large and mutually exclusive families, as exemplified by the enzymes xanthine oxidase, sulfite oxidase, and DMSO reductase; these enzymes represent the focus of the present account.3 The structures of the three canonical molybdenum centers in their oxidized Mo(VI) states are shown in Figure 1, along with that for the pyranopterin cofactor. The active sites of members of the xanthine oxidase family have an LMoVIOS-(OH) structure with a square-pyramidal coordination geometry. The apical ligand is a Mo=O ligand, and the equatorial plane has two sulfurs from the enedithiolate side chain of the pyranopterin cofactor, a catalytically labile Mo–OH group, and most frequently a Mo=S. Nonfunctional forms of these enzymes exist in which the equatorial Mo=S is replaced with a second Mo=O; in at least one member of the family the Mo=S is replaced by a Mo=Se, and in others it is replaced by a more complex –S–Cu–S–Cys to give a binuclear center. Members of the sulfite oxidase family have a related LMoVIO2(S–Cys) active site, again square-pyramidal with an apical Mo=O and a bidentate enedithiolate Ligand (L) in the equatorial plane but with a second equatorial Mo=O (rather than Mo–OH) and a cysteine ligand contributed by the protein (rather than a Mo=S) completing the molybdenum coordination sphere. The final family is the most diverse structurally, although all members possess two (rather than just one) equiv of the pyranopterin cofactor and have an L2MoVIY(X) trigonal prismatic coordination geometry. DMSO reductase itself has a catalytically labile Mo=O as Y and a serinate ligand as X completing the metal coordination sphere of oxidized enzyme. Other family members have cysteine (the bacterial Nap periplasmic nitrate reductases), selenocysteine (formate dehydrogenase H), –OH (arsenite oxidase), or aspartate (the NarGHI dissimilatory nitrate reductases) in place of the serine. Some enzymes have S or even Se in place of the Mo=O group. Members of the DMSO reductase family exhibit a general structural homology to members of the aldehyde:ferredoxin oxidoreductase family of tungsten-containing enzymes;4 indeed, the first pyranopterin-containing enzyme to be crystallographically characterized was the tungsten-containing aldehyde:ferredoxin oxidoreductase from Pyrococcus furiosus,5 a fact accounting for why many workers in the field prefer “pyranopterin” (or, perhaps waggishly, “tungstopterin”) to “molybdopterin”. The term pyranopterin will generally be used in the present account.




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Figure 1


Active site structures for the three families of mononuclear molybdenum enzymes. The structures shown are, from left to right, for xanthine oxidase, sulfite oxidase, and DMSO reductase. The structure of the pyranopterin cofactor common to all of these enzymes (as well as the tungsten-containing enzymes) is given at the bottom.

/pdf/the-mononuclear-molybdenum-enzymes-huemv59go8.pdf

The Mononuclear Molybdenum Enzymes

Most cancer cells exhibit increased glycolysis and use this metabolic pathway for generation of ATP as a main source of their energy supply. This phenomenon is known as the Warburg effect and is considered as one of the most fundamental metabolic alterations during malignant transformation. In recent years, there are significant progresses in our understanding of the underlying mechanisms and the potential therapeutic implications. Biochemical and molecular studies suggest several possible mechanisms by which this metabolic alteration may evolve during cancer development. These mechanisms include mitochondrial defects and malfunction, adaptation to hypoxic tumor microenvironment, oncogenic signaling, and abnormal expression of metabolic enzymes. Importantly, the increased dependence of cancer cells on glycolytic pathway for ATP generation provides a biochemical basis for the design of therapeutic strategies to preferentially kill cancer cells by pharmacological inhibition of glycolysis. Several small molecules have emerged that exhibit promising anticancer activity in vitro and in vivo, as single agent or in combination with other therapeutic modalities. The glycolytic inhibitors are particularly effective against cancer cells with mitochondrial defects or under hypoxic conditions, which are frequently associated with cellular resistance to conventional anticancer drugs and radiation therapy. Because increased aerobic glycolysis is commonly seen in a wide spectrum of human cancers and hypoxia is present in most tumor microenvironment, development of novel glycolytic inhibitors as a new class of anticancer agents is likely to have broad therapeutic applications.

/pdf/glycolysis-inhibition-for-anticancer-treatment-40rjcq29jf.pdf

Glycolysis inhibition for anticancer treatment

Introduction Fundamentals of biochemical modeling Balance equations Rate laws Generalized mass-action kinetics Various enzyme kinetic rate laws Thermodynamic flow-force relationships Power-law approximation Steady states of biochemical networks General considerations Stable and unstable steady states Multiple steady states Metabolic oscillations Background Mathematical conditions for oscillations Glycolytic oscillations Models of intracellular calcium oscillations A simple three-variable model with only monomolecular and bimolecular reactions Possible physiological significance of oscillations Stoichiometric analysis Conservation relations Linear dependencies between the rows of the stoichiometry matrix Non-negative flux vectors Elementary flux modes Thermodynamic aspects A generalized Wegscheider condition Strictly detailed balanced subnetworks Onsager's reciprocity reactions for coupled enyme reactions Time hierarchy in metabolism Time constants The quasi-steady-state approximation The Rapid equilibrium approximation Modal analysis Metabolic control analysis Basic definitions A systematic approach Theorems of metabolic control analysis Summation theorems Connectivity theorems Calculation of control coefficients using the theorems Geometrical interpretation Control analysis of various systems General remarks Elasticity coefficients for specific rate laws Control coefficients for simple hypothetical pathways Unbranched chains A branched system Control of erythrocyte energy metabolism The reaction system Basic model Interplay of ATP production and ATP consumption Glycolytic energy metabolism and osmotic states A simple model of oxidative phosphorylation A three-step model of serine biosynthesis Time-dependent control coefficients Are control coefficients always parameter independent? Posing the problem A system without conserved moieties A system with a conserved moiety A system including dynamic channeling Normalized versus non-normalized coefficients Analysis in terms of variables other than steady-state concentrations and fluxes General analysis Concentration ratios and free-energy-differences as state variables Entropy production as response variable Control of transient times Control of oscillations A second-order approach A quantitative approach to metabolic regulations Co-response coefficients Fluctuations of internal variables versus parameter perturbations Internal response coefficients Rephrasing the basic equations of metabolic control analysis in terms of co-response coefficients and internal response coefficients Control within and between subsystems Modular approach Overall elasticities Overall control coefficients Flux control insusceptibility Control exerted by elementary steps in enzyme catalysis Control analysis of metabolic channeling Comparison of metabolic control analysis and power-law formalism Computational aspects Application of optimization methods and the interrelation with evolution Optimization of the catalytic properties of single enzymes Basic assumptions Optimal values of elementary rate constants Optimal Michaelis constants Optimization of multienzyme systems Maximization of steady-state flux Influence of osmotic constraints and minimization of intermediate concentrations Minimization of transient times Optimal stoichiometries.

The Regulation of Cellular Systems

Evolution and regulatory role of the hexokinases

Control of metabolic processes

The concentration of an inhibitor that decreases the rate of an enzyme-catalysed reaction by 50%, symbolized i !.& , is often used in pharmacological studies to characterize inhibitors. It can be estimated from the common inhibition plots used in biochemistry by means of the fact that the extrapolated inhibitor concentration at which the rate becomes infinite is equal to fii !.& . This method is, in principle, more accurate than comparing the rates at various dierent inhibitor concentrations, and inferring the value of i !.& by interpolation. Its reciprocal, 1}i !.& , is linearly dependent on a ! }V, the uninhibited rate divided by the limiting rate, and the extrapolated value of a ! }V at which 1}i !.& is zero allows the type of inhibition to be characterized: this value is 1 if the inhibition is strictly competitive; greater than 1 if the inhibition is mixed with a predominantly competitive component; infinite (i.e. 1}i !.&

Relationships between inhibition constants, inhibitor concentrations for 50% inhibition and types of inhibition: new ways of analysing data.

Knowledge of the behaviour of bacterial communities is crucial for understanding biogeochemical cycles and developing environmental biotechnology. Here we demonstrate the formation of an artificial consortium between two anaerobic bacteria, Clostridium acetobutylicum (Gram-positive) and Desulfovibrio vulgaris Hildenborough (Gram-negative, sulfate-reducing) in which physical interactions between the two partners induce emergent properties. Molecular and cellular approaches show that tight cell-cell interactions are associated with an exchange of molecules, including proteins, which allows the growth of one partner (D. vulgaris) in spite of the shortage of nutrients. This physical interaction induces changes in expression of two genes encoding enzymes at the pyruvate crossroads, with concomitant changes in the distribution of metabolic fluxes, and allows a substantial increase in hydrogen production without requiring genetic engineering. The stress induced by the shortage of nutrients of D. vulgaris appears to trigger the interaction.

/pdf/nutritional-stress-induces-exchange-of-cell-material-and-1x0o7os7ft.pdf

Nutritional stress induces exchange of cell material and energetic coupling between bacterial species

A complex of five different enzymes: ribose-phosphate isomerase, phosphoribulokinase, ribulose-bisphosphate carboxylase/oxygenase, phosphoglycerate kinase and glyceraldehyde-phosphate dehydrogenase, has been purified from spinach chloroplasts. These enzymes catalyse five consecutive reactions of the Calvin cycle, of which the two reactions catalysed by phosphoribulokinase and ribulose-bisphosphate carboxylase/oxygenase are unique to this cycle. The five-enzyme complex has been purified by successive chromatographies on DEAE-Trisacryl, Sephadex G-200 and hydroxyapatite. The homogeneity of the complex has been tested by analytical centrifugation and electrophoresis. Depending on the technique used to estimate its molecular mass, the value obtained varies between 520 kDa and 536 kDa. In addition to the five enzymes mentioned above, the complex contains a 65-kDa polypeptide. The quaternary structure of these enzymes in the complex appears to be different from what has been described for the individual enzymes in the ‘noncomplexed state’.



The five-enzyme complex is functional as glyceraldehyde 3-phosphate is formed from ribose 5-phosphate. Preliminary experiments suggest that channelling of reaction intermediates occurs within the complex.

http://bip.cnrs-mrs.fr/bip10/Gontero88.pdf

María Luz Cárdenas

Papers

Evolution and regulatory role of the hexokinases

Control of metabolic processes

Relationships between inhibition constants, inhibitor concentrations for 50% inhibition and types of inhibition: new ways of analysing data.

Nutritional stress induces exchange of cell material and energetic coupling between bacterial species

A functional five-enzyme complex of chloroplasts involved in the Calvin cycle.