Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Kinetic modeling”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43Linked to original sources
PubMed2006

Kinetic modeling of CO(ad) monolayer oxidation on carbon-supported platinum nanoparticles.

We present a theoretical study of CO(ad) electrooxidation on Pt nanoparticles. Effects of size and surface texture of nanoparticles on the interplay of relevant kinetic processes are investigated. Thereby, strong impacts of particle size on electrocatalytic activities, observed in experiments, are rationalized. Our theoretical approach employs the active site concept to account for the heterogeneous surface of nanoparticles. It, moreover, incorporates finite rates of surface mobility of adsorbed CO. As demonstrated, the model generalizes established mean field or nucleation and growth models. We find very good agreement of our model with chronoamperometric current transients at various particle sizes and electrode potentials (Maillard, F.; Savinova, E. R.; Stimming, U. J. Electroanal. Chem., in press, doi:10.1016/j.jelechem.2006.02.024). The full interplay of on-site reactivity at active sites and low surface mobility of CO(ad) unfolds on the smallest nanoparticles ( approximately 2 nm). In this case, the solution of the model requires kinetic Monte Carlo simulations specifically developed for this problem. For larger nanoparticles (>4 nm) the surface mobility of CO(ad) is high compared to the reaction rate constants, and the kinetic equations can be solved in the limiting case of infinite surface mobility. The analysis provides an insight into the prevailing reaction mechanisms and allows for the estimation of relevant kinetic parameters.

Journal Article↗
PubMed1997

Quantitative kinetic model for photoassembly of the photosynthetic water oxidase from its inorganic constituents: requirements for manganese and calcium in the kinetically resolved steps,.

The process of photoactivation, the assembly of a functional water-oxidizing complex (WOC) from the apoproteins of photosystem II of higher plants and inorganic cofactors (Mn2+, Ca2+, and Cl-), was known from earlier works to be a two-step kinetic process, requiring two light-induced processes separated by a slower dark period. However, these steps had not been directly resolved in any kinetic experiment, until development of an ultrasensitive polarographic O2 electrode and synthesis of an improved chelator for cofactor removal allowed direct kinetic resolution of the first pre-steady state intermediate [Ananyev, G. M. & Dismukes, G. C. (1996a) Biochemistry 35, 4102-4109]. Herein, the dependence of the rates of each of the first two light steps and the dark step of photoactivation was directly determined in spinach PSII membranes over a range of calcium and manganese concentrations at least 10-fold lower than those possible using commercial O2 electrodes. The following results were obtained. (1) One Mn2+ ion binds and is photooxidized to Mn3+ at a high-affinity site, forming the first light-induced intermediate, IM1. Formation of IM1 is coupled to the dissociation of a bound Ca2+ ion either located in the Mn site or coupled to it. (2) The inhibition constant for Ca2+ dissociation from this site is equal to 1.5 mM. (3) The dissociation constant of Mn2+ at this high-affinity site is equal to 8 microM at the optimum calcium concentration for O2-evolving activity of 8 mM, in agreement with the high-affinity site for electron donation to PSII. (4) Prior to the next photolytic step, one Ca2+ ion must bind at its effector site so that stable photooxidation of a second Mn2+ ion can occur, forming the second light-induced intermediate, IM2. This dark process is the rate-determining step. (5) The Michaelis constant for recovery of O2 evolution by Ca2+ binding at this effector site (Km) is equal to 1.4 mM, a value that is the same as that measured for the calcium requirement for O2 evolution in intact PSII. (6) The low quantum yield for the formation of IM2 from IM1 increases linearly with the duration of the dark period up to the longest period we could examine (10 s). Accordingly, the rate limitation in the second photolytic step originates from a slow calcium-induced dark rearrangement of the first intermediate, IM1, which we propose to be a protein conformational change that allows stable binding of the next Mn2+ ion. We further propose that the single Ca2+ ion which is required for assembly of the Mn4 cluster is equivalent to the Ca2+ ion which functions at the "gatekeeper" site in intact O2-evolving centers, where it plays a role in limiting substrate access to the Mn4 cluster [Sivaraja, M., et al. (1989) Biochemistry 28, 9459-9464; Tso, J., et al., (1991) Biochemistry 30, 4734-4739]. A molecular model for photoactivation is proposed and discussed.

Calcium↗
PubMed2001

A kinetic model for the B-Z transition of poly[d(G-C)].poly[d(G-C)] and poly[d(G-m5C)].poly[d(G-m5C)].

The analysis of the kinetic data of the B-Z conformational changes induced by salt in sized double-stranded poly[d(G-C)].poly[d(G-C)] and poly[d(G-m5C)].poly[d(G-m5C)] polymers indicated that there exists a salt threshold which reveals some largely, as yet, unrecognised characteristics of the transition. It was observed that there is a direct correlation between the length of the polymer and the rate of the B-Z transition when the salt concentration in the polymer solution is lower than the salt threshold. The correlation is inverse when the salt concentration is higher than the salt threshold. Thus, the molecular mechanism of the B- to Z-DNA transition varies depending on whether the salt concentration is higher or lower than the threshold. In this context, we have found that the contrasting results reported in the literature describing the rate of the B-Z transition are not contradictory but complementary. The finding of a salt threshold leads to the establishment of a relationship between the cooperativity index of the B-Z transition and the polymer chain length. That relationship is dependent on the chemical structure of the polymer but is temperature independent.

DNA↗
PubMed1986

Kinetic models of induction: II. Decreased turnover of a product or its precursor.

Reduction of the turnover rate constant for a substance or its metabolic precursor is a mechanism for induction which differs markedly in its kinetic characteristics from induction resulting from a direct stimulation of synthesis. The unique aspect of induction following inhibited turnover is that the time course of recovery from the induced to the basal state is more rapid than the time course for induction itself. A general set of kinetic equations is presented here which represents the complete chain of events for such an induction; namely the kinetics of the inducer, the kinetics of a synthesis precursor to the induced product, and the kinetics of the induced product itself. These equations have been used to simulate examples of this type of induction and resemble induction experiments from the literature.

Enzyme Induction↗
PubMed1999

Kinetic model of biosurfactant-enhanced hexadecane biodegradation by Pseudomonas aeruginosa.

Many sites of environmental concern contain groundwater contaminated with nonaqueous phase liquids (NAPL). In such sites interfacial processes may affect both the equilibrium and kinetic behavior of the system. In particular, insoluble hydrocarbon partitioning and microbial biodegradation of insoluble hydrocarbon are influenced by the physicochemical and interfacial characteristics of the system. A mechanistic model describing the influence of biological surfactants on microbial biodegradation of liquid-phase insoluble hydrocarbon and subsequent reduction of nonaqueous-phase liquid hydrocarbon is presented. The model consists of six coupled differential equations which use lumped kinetic parameters to describe surfactant micelle formation and diffusion to the microbial cell, nonlinear kinetic expressions for microbial growth and degradation of insoluble hydrocarbon, kinetic spatial descriptions of the change in NAPL-phase droplet size and the organic phase volume fraction with time, as well as equilibrium partitioning expressions for hydrophobic organic contaminant partioning into the surfactant micelle. The model is validated by comparison to data obtained for hexadecane degradation in a well-mixed batch system by the biosurfactant producing microorganism Pseudomonas aeruginosa strain PG201 as well as for nonproducing mutants' growth and hexadecane biodegradation in the presence of exogenously added biosurfactant. Experimentally determined biological growth parameters, as well as physical parameters such as hydrocarbon droplet size, were applied in the kinetic model. Parameter sensitivity analysis was performed on the physical and biological parameters in the model. The parameter sensitivity analysis indicates that for the biological system examined the rate of hydrocarbon solubilization and micellar transport to the cell controls the rate at which cellular uptake and biodegradation of insoluble hydrocarbon occurs. Practical aspects relating to use of the model for support of surfactant-based bioremediation efforts are discussed.

Alkanes↗
PubMed1996

Enzyme kinetic modelling as a tool to analyse the behaviour of cytochrome P450 catalysed reactions: application to amitriptyline N-demethylation.

1. To determine kinetic parameters (Vmax, K(m)) for cytochrome P450 (CYP) mediated metabolic pathways, nonlinear least squares regression is commonly used to fit a model equation (e.g., Michaelis Menten [MM]) to sets of data points (reaction velocity vs substrate concentration). This method can also be utilized to determine the parameters for more complex mechanisms involving allosteric or multi-enzyme systems. Akaike's Information Criterion (AIC), or an estimation of improvement of fit as successive parameters are introduced in the model (F-test), can be used to determine whether application of more complex models is helpful. To evaluate these approaches, we have examined the complex enzyme kinetics of amitriptyline (AMI) N-demethylation in vitro by human liver microsomes. 2. For a 15-point nortriptyline (NT) formation rate vs substrate (AMI) concentration curve, a two enzyme model, consisting of one enzyme with MM kinetics (Vmax = 1.2 nmol min-1 mg-1, K(m) = 24 microM) together with a sigmoidal component (described by an equation equivalent to the Hill equation for cooperative substrate binding; Vmax = 2.1 nmol min-1 mg-1, K' = 70 microM; Hill exponent n = 2.34), was favoured according to AIC and the F-test. 3. Data generated by incubating AMI under the same conditions but in the presence of 10 microM ketoconazole (KET), a CYP3A3/4 inhibitor, were consistent with a single enzyme model with substrate inhibition (Vmax = 0.74 nmol min-1 mg-1, K(m) = 186 microM, K1 = 0.0028 microM-1). 4. Sulphaphenazole (SPA), a CYP2C9 inhibitor, decreased the rate of NT formation in a concentration dependent manner, whereas a polyclonal rat liver CYP2C11 antibody, inhibitory for S-mephenytoin 4'-hydroxylation in humans, had no important effect on this reaction. 5. Incubation of AMI with 50 microM SPA resulted in a curve consistent with a two enzyme model, one with MM kinetics (Vmax = 0.72 nmol min-1 mg-1, K(m) = 54 microM) the other with 'Hill-kinetics' (Vmax = 2.1 nmol min-1 mg-1, K' = 195 microM; n = 2.38). 6. A fourth data-set was generated by incubating AMI with 10 microM KET and 50 microM SPA. The proposed model of best fit describes two activities, one obeying MM-kinetics (Vmax = 0.048 nmol min-1 mg-1, K(m) = 7 microM) and the other obeying MM kinetics but with substrate inhibition (Vmax = 0.8 nmol min-1 mg-1, K(m) = 443 microM, K1 = 0.0041 microM-1). 7. The combination of kinetic modelling tools and biological data has permitted the discrimination of at least three CYP enzymes involved in AMI N-demethylation. Two are identified as CYP3A3/4 and CYP2C9, although further work in several more livers is required to confirm the participation of the latter.

Amitriptyline↗
PubMed2007

Classical versus stochastic kinetics modeling of biochemical reaction systems.

We study fundamental relationships between classical and stochastic chemical kinetics for general biochemical systems with elementary reactions. Analytical and numerical investigations show that intrinsic fluctuations may qualitatively and quantitatively affect both transient and stationary system behavior. Thus, we provide a theoretical understanding of the role that intrinsic fluctuations may play in inducing biochemical function. The mean concentration dynamics are governed by differential equations that are similar to the ones of classical chemical kinetics, expressed in terms of the stoichiometry matrix and time-dependent fluxes. However, each flux is decomposed into a macroscopic term, which accounts for the effect of mean reactant concentrations on the rate of product synthesis, and a mesoscopic term, which accounts for the effect of statistical correlations among interacting reactions. We demonstrate that the ability of a model to account for phenomena induced by intrinsic fluctuations may be seriously compromised if we do not include the mesoscopic fluxes. Unfortunately, computation of fluxes and mean concentration dynamics requires intensive Monte Carlo simulation. To circumvent the computational expense, we employ a moment closure scheme, which leads to differential equations that can be solved by standard numerical techniques to obtain more accurate approximations of fluxes and mean concentration dynamics than the ones obtained with the classical approach.

Biochemistry↗
PubMedDate not supplied

[Kinetic modeling during continuous hemodiafiltration in patients with sepsis and multiorgan failure].

Kinetic simulation in terms of urea and creatinine is the best way of prescribing a dialysis dose and assessing its quality as it considers differences in a patient's body weight, the level of catabolism, the rate of equilibration, including the recirculation phenomenon noticeably observed under shock. A 2-pool model of distribution of urea and creatinine was employed in the study. The latter was carried out in 31 patients (17 males and 14 females) with sepsis and multi-organ failure receiving 50 sessions of continuous hemodiafiltration (CHDF). The mean duration of CHDF was 73.8 +/- 7.0 (4.0-207.0) hours, the daily volumes of a substitute, a dialysate, and an effluent (filtrate + dialysate) were 33 +/- 1.0 (5.0-60.0), 43.9 +/- 0.8 (2.6-62.0), and 80.4 +/- 1.6 (12.0-122.3) liters a day, respectively. An analysis confirmed the high efficiency of CHDF close to that of the daily volume-body weight ratio and showed that such conditions of the procedure are optimal in maintaining azotemia at the subnormal level irrespective of the degree of cababolism.

Creatinine↗
PubMed2005

Brain lactate kinetics: Modeling evidence for neuronal lactate uptake upon activation.

A critical issue in brain energy metabolism is whether lactate produced within the brain by astrocytes is taken up and metabolized by neurons upon activation. Although there is ample evidence that neurons can efficiently use lactate as an energy substrate, at least in vitro, few experimental data exist to indicate that it is indeed the case in vivo. To address this question, we used a modeling approach to determine which mechanisms are necessary to explain typical brain lactate kinetics observed upon activation. On the basis of a previously validated model that takes into account the compartmentalization of energy metabolism, we developed a mathematical model of brain lactate kinetics, which was applied to published data describing the changes in extracellular lactate levels upon activation. Results show that the initial dip in the extracellular lactate concentration observed at the onset of stimulation can only be satisfactorily explained by a rapid uptake within an intraparenchymal cellular compartment. In contrast, neither blood flow increase, nor extracellular pH variation can be major causes of the lactate initial dip, whereas tissue lactate diffusion only tends to reduce its amplitude. The kinetic properties of monocarboxylate transporter isoforms strongly suggest that neurons represent the most likely compartment for activation-induced lactate uptake and that neuronal lactate utilization occurring early after activation onset is responsible for the initial dip in brain lactate levels observed in both animals and humans.

Animals↗