The Experts below are selected from a list of 309 Experts worldwide ranked by ideXlab platform
Jianshu Cao - One of the best experts on this subject based on the ideXlab platform.
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conformational nonequilibrium enzyme kinetics generalized Michaelis menten equation
Journal of Physical Chemistry Letters, 2017Co-Authors: Evan D Piephoff, Jianshu CaoAbstract:In a conformational nonequilibrium steady state (cNESS), enzyme turnover is modulated by the underlying conformational dynamics. On the basis of a discrete kinetic network model, we use an integrated probability flux balance method to derive the cNESS turnover rate for a conformation-modulated enzymatic reaction. The traditional Michaelis–Menten (MM) rate equation is extended to a generalized form, which includes non-MM corrections induced by conformational population currents within combined cyclic kinetic loops. When conformational detailed balance is satisfied, the turnover rate reduces to the MM functional form, explaining its general validity. For the first time, a one-to-one correspondence is established between non-MM terms and combined cyclic loops with unbalanced conformational currents. Cooperativity resulting from nonequilibrium conformational dynamics can be achieved in enzymatic reactions, and we provide a novel, rigorous means of predicting and characterizing such behavior. Our generalized M...
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conformational nonequilibrium enzyme kinetics generalized Michaelis menten equation
arXiv: Biological Physics, 2017Co-Authors: Evan D Piephoff, Jianshu CaoAbstract:In a conformational nonequilibrium steady state (cNESS), enzyme turnover is modulated by the underlying conformational dynamics. Based on a discrete kinetic network model, we use the integrated probability flux balance method to derive the cNESS turnover rate for a conformation-modulated enzymatic reaction. The traditional Michaelis-Menten (MM) rate equation is extended to a generalized form, which includes non-MM corrections induced by conformational population currents within combined cyclic kinetic loops. When conformational detailed balance is satisfied, the turnover rate reduces to the MM functional form, explaining its validity for many enzymatic systems. For the first time, a one-to-one correspondence is established between non-MM terms and combined cyclic loops with unbalanced conformational currents. Cooperativity resulting from nonequilibrium conformational dynamics has been observed in enzymatic reactions, and we provide a novel, rigorous means of predicting and characterizing such behavior. Our generalized MM equation affords a systematic approach for exploring cNESS enzyme kinetics.
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Michaelis menten equation and detailed balance in enzymatic networks
Journal of Physical Chemistry B, 2011Co-Authors: Jianshu CaoAbstract:Many enzymatic reactions in biochemistry are far more complex than the celebrated Michaelis−Menten scheme, but the observed turnover rate often obeys the hyperbolic dependence on the substrate concentration, a relation established almost a century ago for the simple Michaelis−Menten mechanism. To resolve the longstanding puzzle, we apply the flux balance method to predict the functional form of the substrate dependence in the mean turnover time of complex enzymatic reactions and identify detailed balance (i.e., the lack of unbalanced conformtional current) as a sufficient condition for the Michaelis−Menten equation to describe the substrate concentration dependence of the turnover rate in an enzymatic network. This prediction can be verified in single-molecule event-averaged measurements using the recently proposed signatures of detailed balance violations. The finding helps analyze recent single-molecule studies of enzymatic networks and can be applied to other external variables, such as force-dependenc...
Józef Drabowicz - One of the best experts on this subject based on the ideXlab platform.
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solvent free Michaelis arbuzov rearrangement under flow conditions
Journal of Organic Chemistry, 2019Co-Authors: Aleksandra Jasiak, Grażyna Mielniczak, Krzysztof Owsianik, Marek Koprowski, Dorota Krasowska, Józef DrabowiczAbstract:The first solvent- and catalyst-free procedure for the Michaelis-Arbuzov reaction under flow conditions was developed. A variety of alkylphosphonic esters could be obtained using this protocol starting from the corresponding trialkyl phosphites and even catalytic amounts of alkyl halides with very short reaction times (8.33-50 min) and excellent conversions. In general, this protocol works effectively when the alkyl halide is used in catalytic amounts as low as 5-10% only if it concerns the synthesis of homo alkylphosphonates. One equivalent and an excess of alkyl halides should be used in the reaction with alkyl phosphite if the alkyl group of the selected substrates differ. Thus, it provides a sustainable, fast alternative to the existing methods for the preparation of alkylphosphonates. The isolation of the reaction products is straightforward due to the lack of solvents and a high purity of the obtained products (conv ≥ 99%), and notably, in the catalytic procedures there are only traces of alkyl halides formed after the reaction is complete. The reactions conducted using a glass microreactor chip with an internal volume of 250 μL allow the production of 1.6-1.95 g of organophosphorus esters per hour.
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Solvent-Free Michaelis–Arbuzov Rearrangement under Flow Conditions
2019Co-Authors: Aleksandra Jasiak, Grażyna Mielniczak, Krzysztof Owsianik, Marek Koprowski, Dorota Krasowska, Józef DrabowiczAbstract:The first solvent- and catalyst-free procedure for the Michaelis–Arbuzov reaction under flow conditions was developed. A variety of alkylphosphonic esters could be obtained using this protocol starting from the corresponding trialkyl phosphites and even catalytic amounts of alkyl halides with very short reaction times (8.33–50 min) and excellent conversions. In general, this protocol works effectively when the alkyl halide is used in catalytic amounts as low as 5–10% only if it concerns the synthesis of homo alkylphosphonates. One equivalent and an excess of alkyl halides should be used in the reaction with alkyl phosphite if the alkyl group of the selected substrates differ. Thus, it provides a sustainable, fast alternative to the existing methods for the preparation of alkylphosphonates. The isolation of the reaction products is straightforward due to the lack of solvents and a high purity of the obtained products (conv ≥ 99%), and notably, in the catalytic procedures there are only traces of alkyl halides formed after the reaction is complete. The reactions conducted using a glass microreactor chip with an internal volume of 250 μL allow the production of 1.6–1.95 g of organophosphorus esters per hour
Santiago Schnell - One of the best experts on this subject based on the ideXlab platform.
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validity of the Michaelis menten equation steady state or reactant stationary assumption that is the question
FEBS Journal, 2014Co-Authors: Santiago SchnellAbstract:The Michaelis–Menten equation is generally used to estimate the kinetic parameters, V and KM, when the steady-state assumption is valid. Following a brief overview of the derivation of the Michaelis–Menten equation for the single-enzyme, single-substrate reaction, a critical review of the criteria for validity of the steady-state assumption is presented. The application of the steady-state assumption makes the implicit assumption that there is an initial transient during which the substrate concentration remains approximately constant, equal to the initial substrate concentration, while the enzyme–substrate complex concentration builds up. This implicit assumption is known as the reactant stationary assumption. This review presents evidence showing that the reactant stationary assumption is distinct from and independent of the steady-state assumption. Contrary to the widely believed notion that the Michaelis–Menten equation can always be applied under the steady-state assumption, the reactant stationary assumption is truly the necessary condition for validity of the Michaelis–Menten equation to estimate kinetic parameters. Therefore, the application of the Michaelis–Menten equation only leads to accurate estimation of kinetic parameters when it is used under experimental conditions meeting the reactant stationary assumption. The criterion for validity of the reactant stationary assumption does not require the restrictive condition of choosing a substrate concentration that is much higher than the enzyme concentration in initial rate experiments.
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single molecule enzymology a la Michaelis menten
FEBS Journal, 2014Co-Authors: Ramon Grima, Nils G Walter, Santiago SchnellAbstract:Over the past 100 years, deterministic rate equations have been successfully used to infer enzyme-catalysed reaction mechanisms and to estimate rate constants from reaction kinetics experiments conducted in vitro. In recent years, sophisticated experimental techniques have been developed that begin to allow the measurement of enzyme-catalysed and other biopolymer-mediated reactions inside single cells at the single-molecule level. Time-course data obtained using these methods are considerably noisy because molecule numbers within cells are typically quite small. As a consequence, the interpretation and analysis of single-cell data requires stochastic methods, rather than deterministic rate equations. Here, we concisely review both experimental and theoretical techniques that enable single-molecule analysis, with particular emphasis on the major developments in the field of theoretical stochastic enzyme kinetics, from its inception in the mid-20th century to its modern-day status. We discuss the differences between stochastic and deterministic rate equation models, how these depend on enzyme molecule numbers and substrate inflow into the reaction compartment, and how estimation of rate constants from single-cell data is possible using recently developed stochastic approaches.
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single molecule enzymology a la Michaelis menten
arXiv: Subcellular Processes, 2013Co-Authors: Ramon Grima, Nils G Walter, Santiago SchnellAbstract:In the past one hundred years, deterministic rate equations have been successfully used to infer enzyme-catalysed reaction mechanisms and to estimate rate constants from reaction kinetics experiments conducted in vitro. In recent years, sophisticated experimental techniques have been developed that allow the measurement of enzyme- catalysed and other biopolymer-mediated reactions inside single cells at the single molecule level. Time course data obtained by these methods are considerably noisy because molecule numbers within cells are typically quite small. As a consequence, the interpretation and analysis of single cell data requires stochastic methods, rather than deterministic rate equations. Here we concisely review both experimental and theoretical techniques which enable single molecule analysis with particular emphasis on the major developments in the field of theoretical stochastic enzyme kinetics, from its inception in the mid-twentieth century to its modern day status. We discuss the differences between stochastic and deterministic rate equation models, how these depend on enzyme molecule numbers and substrate inflow into the reaction compartment and how estimation of rate constants from single cell data is possible using recently developed stochastic approaches.
Ramon Grima - One of the best experts on this subject based on the ideXlab platform.
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stochastic time dependent enzyme kinetics closed form solution and transient bimodality
Journal of Chemical Physics, 2020Co-Authors: James Holehouse, Augustinas Sukys, Ramon GrimaAbstract:We derive an approximate closed-form solution to the chemical master equation describing the Michaelis-Menten reaction mechanism of enzyme action. In particular, assuming that the probability of a complex dissociating into an enzyme and substrate is significantly larger than the probability of a product formation event, we obtain expressions for the time-dependent marginal probability distributions of the number of substrate and enzyme molecules. For delta function initial conditions, we show that the substrate distribution is either unimodal at all times or else becomes bimodal at intermediate times. This transient bimodality, which has no deterministic counterpart, manifests when the initial number of substrate molecules is much larger than the total number of enzyme molecules and if the frequency of enzyme-substrate binding events is large enough. Furthermore, we show that our closed-form solution is different from the solution of the chemical master equation reduced by means of the widely used discrete stochastic Michaelis-Menten approximation, where the propensity for substrate decay has a hyperbolic dependence on the number of substrate molecules. The differences arise because the latter does not take into account enzyme number fluctuations, while our approach includes them. We confirm by means of a stochastic simulation of all the elementary reaction steps in the Michaelis-Menten mechanism that our closed-form solution is accurate over a larger region of parameter space than that obtained using the discrete stochastic Michaelis-Menten approximation.
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single molecule enzymology a la Michaelis menten
FEBS Journal, 2014Co-Authors: Ramon Grima, Nils G Walter, Santiago SchnellAbstract:Over the past 100 years, deterministic rate equations have been successfully used to infer enzyme-catalysed reaction mechanisms and to estimate rate constants from reaction kinetics experiments conducted in vitro. In recent years, sophisticated experimental techniques have been developed that begin to allow the measurement of enzyme-catalysed and other biopolymer-mediated reactions inside single cells at the single-molecule level. Time-course data obtained using these methods are considerably noisy because molecule numbers within cells are typically quite small. As a consequence, the interpretation and analysis of single-cell data requires stochastic methods, rather than deterministic rate equations. Here, we concisely review both experimental and theoretical techniques that enable single-molecule analysis, with particular emphasis on the major developments in the field of theoretical stochastic enzyme kinetics, from its inception in the mid-20th century to its modern-day status. We discuss the differences between stochastic and deterministic rate equation models, how these depend on enzyme molecule numbers and substrate inflow into the reaction compartment, and how estimation of rate constants from single-cell data is possible using recently developed stochastic approaches.
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single molecule enzymology a la Michaelis menten
arXiv: Subcellular Processes, 2013Co-Authors: Ramon Grima, Nils G Walter, Santiago SchnellAbstract:In the past one hundred years, deterministic rate equations have been successfully used to infer enzyme-catalysed reaction mechanisms and to estimate rate constants from reaction kinetics experiments conducted in vitro. In recent years, sophisticated experimental techniques have been developed that allow the measurement of enzyme- catalysed and other biopolymer-mediated reactions inside single cells at the single molecule level. Time course data obtained by these methods are considerably noisy because molecule numbers within cells are typically quite small. As a consequence, the interpretation and analysis of single cell data requires stochastic methods, rather than deterministic rate equations. Here we concisely review both experimental and theoretical techniques which enable single molecule analysis with particular emphasis on the major developments in the field of theoretical stochastic enzyme kinetics, from its inception in the mid-twentieth century to its modern day status. We discuss the differences between stochastic and deterministic rate equation models, how these depend on enzyme molecule numbers and substrate inflow into the reaction compartment and how estimation of rate constants from single cell data is possible using recently developed stochastic approaches.
Weng Kee Wong - One of the best experts on this subject based on the ideXlab platform.
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optimal design for goodness of fit of the Michaelis menten enzyme kinetic function
Journal of the American Statistical Association, 2005Co-Authors: Holger Dette, Viatcheslav B Melas, Weng Kee WongAbstract:We construct efficient designs for the Michaelis–Menten enzyme kinetic model capable of checking model assumptions. An extended model called EMAX is also considered for this purpose. This model is widely used in pharmacokinetics and reduces to the Michaelis–Menten model for a specific choice of parameter settings. Our strategy is to find efficient designs for estimating the parameters in the EMAX model and at the same time test the validity of the Michaelis–Menten model against the EMAX model by maximizing a minimum of the D or D1 efficiencies taken over a range of values for the nonlinear parameters. In particular, we show that such designs are (a) efficient for estimating parameters in the EMAX model, (b) about 70% efficient for estimating parameters in the Michaelis–Menten model, (c) efficient for testing the Michaelis–Menten model against the EMAX model, and (d) robust with respect to misspecification of the unknown parameters in the nonlinear model.
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design issues for the Michaelis menten model
Journal of Theoretical Biology, 2002Co-Authors: Jesus Lopezfidalgo, Weng Kee WongAbstract:We discuss design issues for the Michaelis-Menten model and use geometrical arguments to find optimal designs for estimating a subset of the model parameters, or a linear combination of the parameters. We propose multiple-objective optimal designs when the parameters have different levels of interest to the researcher. In addition, we compare six commonly used sequence designs in the biological sciences for estimating parameters and, propose optimal choices for the parameters for geometric designs using closed-form efficiency formulas.
