Four tables available at the above site.
The kinetic parameters of enzymes are key to understanding the rate and specificity of most biological processes. Although specific trends are frequently studied for individual enzymes, global trends are rarely addressed. We performed an analysis of k(cat) and K(M) values of several thousand enzymes collected from the literature. We found that the "average enzyme" exhibits a k(cat) of ~0 s(-1) and a k(cat)/K(M) of ~10(5) s(-1) M(-1), much below the diffusion limit and the characteristic textbook portrayal of kinetically superior enzymes. Why do most enzymes exhibit moderate catalytic efficiencies? Maximal rates may not evolve in cases where weaker selection pressures are expected. We find, for example, that enzymes operating in secondary metabolism are, on average, ~30-fold slower than those of central metabolism. We also find indications that the physicochemical properties of substrates affect the kinetic parameters. Specifically, low molecular mass and hydrophobicity appear to limit K(M) optimization. In accordance, substitution with phosphate, CoA, or other large modifiers considerably lowers the K(M) values of enzymes utilizing the substituted substrates. It therefore appears that both evolutionary selection pressures and physicochemical constraints shape the kinetic parameters of enzymes. It also seems likely that the catalytic efficiency of some enzymes toward their natural substrates could be increased in many cases by natural or laboratory evolution.
Noise in gene expression is generated at multiple levels, such as transcription and translation, chromatin remodeling and pathway-specific regulation. Studies of individual promoters have suggested different dominating noise sources, raising the question of whether a general trend exists across a large number of genes and conditions. We examined the variation in the expression levels of 43 Saccharomyces cerevisiae proteins, in cells grown under 11 experimental conditions. For all classes of genes and under all conditions, the expression variance was approximately proportional to the mean; the same scaling was observed at steady state and during the transient responses to the perturbations. Theoretical analysis suggests that this scaling behavior reflects variability in mRNA copy number, resulting from random 'birth and death' of mRNA molecules or from promoter fluctuations. Deviation of coexpressed genes from this general trend, including high noise in stress-related genes and low noise in proteasomal genes, may indicate fluctuations in pathway-specific regulators or a differential activation pattern of the underlying gene promoters.
The laws of thermodynamics constrain the action of biochemical systems. However, thermodynamic data on biochemical compounds can be difficult to find and is cumbersome to perform calculations with manually. Even simple thermodynamic questions like ‘how much Gibbs energy is released by ATP hydrolysis at pH 5?’ are complicated excessively by the search for accurate data. To address this problem, eQuilibrator couples a comprehensive and accurate database of thermodynamic properties of biochemical compounds and reactions with a simple and powerful online search and calculation interface. The web interface to eQuilibrator (http://equilibrator.weizmann.ac.il) enables easy calculation of Gibbs energies of compounds and reactions given arbitrary pH, ionic strength and metabolite concentrations. The eQuilibrator code is open-source and all thermodynamic source data are freely downloadable in standard formats. Here we describe the database characteristics and implementation and demonstrate its use.
Contrary to the textbook portrayal of glycolysis as a single pathway conserved across all domains of life, not all sugar-consuming organisms use the canonical Embden-Meyerhoff-Parnass (EMP) glycolytic pathway. Prokaryotic glucose metabolism is particularly diverse, including several alternative glycolytic pathways, the most common of which is the Entner-Doudoroff (ED) pathway. The prevalence of the ED pathway is puzzling as it produces only one ATP per glucose-half as much as the EMP pathway. We argue that the diversity of prokaryotic glucose metabolism may reflect a tradeoff between a pathway's energy (ATP) yield and the amount of enzymatic protein required to catalyze pathway flux. We introduce methods for analyzing pathways in terms of thermodynamics and kinetics and show that the ED pathway is expected to require several-fold less enzymatic protein to achieve the same glucose conversion rate as the EMP pathway. Through genomic analysis, we further show that prokaryotes use different glycolytic pathways depending on their energy supply. Specifically, energy-deprived anaerobes overwhelmingly rely upon the higher ATP yield of the EMP pathway, whereas the ED pathway is common among facultative anaerobes and even more common among aerobes. In addition to demonstrating how protein costs can explain the use of alternative metabolic strategies, this study illustrates a direct connection between an organism's environment and the thermodynamic and biochemical properties of the metabolic pathways it employs.evolution | enzyme cost G lycolysis is the process by which glucose is broken down anaerobically into incompletely oxidized compounds like pyruvate, a process which is usually coupled to the synthesis of ATP. Although the Embden-Meyerhof-Parnas pathway (EMP, often simply "glycolysis") is the nearly ubiquitous glycolytic route among eukaryotes (1, 2), it is not the only game in town. Prokaryotes display impressive diversity in glucose metabolism (2, 3) and natural glycolytic alternatives like the Entner-Doudoroff (ED), and phosphoketolase pathways attest to the fact that there are multiple biologically feasible routes for glucose metabolism (2, 4-8). Natural glycolytic pathways vary in their reaction sequence and in how much ATP they produce per glucose metabolized, ranging from zero to three ATP molecules in most cases (7).The EMP and ED pathways ( Fig. 1 A and B and Fig. S1) are the most common bacterial glycolytic pathways (2, 4, 9), and their general schemes are quite similar: glucose is phosphorylated and then cleaved into two three-carbon units, which are further metabolized to produce ATP (4). In some organisms, these pathways differ slightly in the specific redox cofactors they use (e.g., NAD + vs. NADP + ; Fig. 1B, Fig. S2, and Table S1), but here we focus on the prominent difference in ATP yield. If we take lactate as a representative final product, these two pathways have the same net reaction:and differ primarily in n, the number of ATP produced, and the specific intermediate reaction steps (Fig. 1B, SI T...
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