Alternative substrate and inhibition kinetics of aminoglycoside nucleotidyltransferase 2''-I in support of a Theorell-Chance kinetic mechanism

Biochemistry ◽  
1988 ◽  
Vol 27 (10) ◽  
pp. 3826-3833 ◽  
Author(s):  
Cynthia A. Gates ◽  
Dexter B. Northrop
1952 ◽  
Vol 25 (1) ◽  
pp. 21-32 ◽  
Author(s):  
W. C. Warner ◽  
J. Reid Shelton

Abstract Three olefins were oxidized in the liquid phase with molecular oxygen to determine the kinetics of the oxidation reactions and the relationship to oxidation of rubber. The instantaneous rate of oxidation was found to be related to the analytically determined olefin and peroxide concentrations by the equation : Rate=k (unreacted olefin)(peroxide), where rate equals moles of oxygen per mole of original olefin per hour and the parentheses represent molarities. Presence of a phenyl group was found to affect k, but only in a minor way, indicating that the same fundamental kinetic mechanism applies in both aromatic and aliphatic olefins. The data are consistent with the general kinetic mechanism of Bolland involving oxygen attack at the alpha-methylenic group. However, it appears probable that initial oxygen attack can also occur at the double bond, resulting in the formation of a peroxide biradical, which may then react with other olefin molecules, initiating the usual chain reaction mechanism.


2018 ◽  
Vol 115 (50) ◽  
pp. E11604-E11613 ◽  
Author(s):  
Eric A. Galburt

The regulation of transcription allows cells to adjust the rate of RNA polymerases (RNAPs) initiated in a promoter-specific manner. Classically, transcription factors are directed to a subset of promoters via the recognition of DNA sequence motifs. However, a unique class of regulators is recruited directly through interactions with RNAP. Surprisingly, these factors may still possess promoter specificity, and it has been postulated that the same kinetic mechanism leads to different regulatory outcomes depending on a promoter’s basal rate constants. However, mechanistic studies of regulation typically report factor activity in terms of changes in the thermodynamics or kinetics of individual steps or states while qualitatively linking these observations to measured changes in transcript production. Here, I present online calculators that allow for the direct testing of mechanistic hypotheses by calculating the steady-state transcript flux in the presence and absence of a factor as a function of initiation rate constants. By evaluating how the flux ratio of a single kinetic mechanism varies across promoter space, quantitative insights into the potential of a mechanism to generate promoter-specific regulatory outcomes are obtained. Using these calculations, I predict that the mycobacterial transcription factor CarD is capable of repression in addition to its known role as an activator of ribosomal genes. In addition, a modification of the mechanism of the stringent response factors DksA/guanosine 5′-diphosphate 3′-diphosphate (ppGpp) is proposed based on their ability to differentially regulate transcription across promoter space. Overall, I conclude that a multifaceted kinetic mechanism is a requirement for differential regulation by this class of factors.


2011 ◽  
Vol 54 ◽  
pp. S312 ◽  
Author(s):  
H. Dahari ◽  
N. Barretto ◽  
B.J. Sainz ◽  
J. Guedj ◽  
A.S. Perelson ◽  
...  

1995 ◽  
Vol 10 (2) ◽  
pp. 268-273 ◽  
Author(s):  
N. Vandewalle ◽  
R. Cloots ◽  
M. Ausloos

We present optical observations of magnetically melt-textured DyBa2Cu3O7−x with and without 20 wt. % excess of Dy2BaCuO5. From these observations, we propose some kinetic mechanism of the growth of 123 compounds. Kinetic processes can be simulated on computers. Two (very) simple models derived from the well-known Eden model are presented. They simulate the growth of the grain front. The simulated patterns agree with the observations. The microstructure of such materials cannot be explained by thermodynamic and chemical considerations alone, but explanations must include the kinetics of the growth front as well. From our observations, we conclude that the growth probability ratios g110/g100 and g100/g001 are of the order of 10 and 50, respectively.


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