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Journal ArticleDOI

Single-molecule enzyme kinetics in the presence of inhibitors.

Soma Saha, +2 more
- 25 Jul 2012 - 
- Vol. 137, Iss: 4, pp 045102-045102
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TLDR
This work derives exact expressions for the waiting time distribution for competitive, uncompetitive, and mixed inhibitions to quantitatively show that the presence of inhibitors can induce dynamic disorder in all three modes of inhibitions resulting in temporal fluctuations in the reaction rate.
Abstract
Recent studies in single-molecule enzyme kinetics reveal that the turnover statistics of a single enzyme is governed by the waiting time distribution that decays as mono-exponential at low substrate concentration and multi-exponential at high substrate concentration. The multi-exponentiality arises due to protein conformational fluctuations, which act on the time scale longer than or comparable to the catalytic reaction step, thereby inducing temporal fluctuations in the catalytic rate resulting in dynamic disorder. In this work, we study the turnover statistics of a single enzyme in the presence of inhibitors to show that the multi-exponentiality in the waiting time distribution can arise even when protein conformational fluctuations do not influence the catalytic rate. From the Michaelis-Menten mechanism of inhibited enzymes, we derive exact expressions for the waiting time distribution for competitive, uncompetitive, and mixed inhibitions to quantitatively show that the presence of inhibitors can induce dynamic disorder in all three modes of inhibitions resulting in temporal fluctuations in the reaction rate. In the presence of inhibitors, dynamic disorder arises due to transitions between active and inhibited states of enzymes, which occur on time scale longer than or comparable to the catalytic step. In this limit, the randomness parameter (dimensionless variance) is greater than unity indicating the presence of dynamic disorder in all three modes of inhibitions. In the opposite limit, when the time scale of the catalytic step is longer than the time scale of transitions between active and inhibited enzymatic states, the randomness parameter is unity, implying no dynamic disorder in the reaction pathway.

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Citations
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Journal ArticleDOI

Extracting signal from noise: kinetic mechanisms from a Michaelis-Menten-like expression for enzymatic fluctuations.

TL;DR: A widespread and important statistical measure known as the randomness parameter, which is the squared coefficient of variation of the cycle completion times, although it places significant limits on the minimal complexity of possible enzymatic mechanisms is focused on.
Journal ArticleDOI

Single-molecule theory of enzymatic inhibition.

TL;DR: In this paper, the authors take the single-enzyme perspective and rebuild the theory of enzymatic inhibition from the bottom up, finding that stochastic fluctuations at the singleenzyme level could make inhibitors act as activators, and state in terms of experimentally measurable quantities-a mathematical condition for the emergence of this surprising phenomenon.
Journal ArticleDOI

Single-molecule theory of enzymatic inhibition predicts the emergence of inhibitor-activator duality

TL;DR: In this article, the authors take the single enzyme perspective and rebuild the theory of enzymatic inhibition from the bottom up, finding that accounting for multi-conformational enzyme structure and intrinsic randomness cannot undermine the validity of classical results in the case of competitive inhibition; but that it should strongly change our view on the uncompetitive and mixed modes of inhibition.
Journal ArticleDOI

Structural conditions on complex networks for the Michaelis–Menten input–output response

TL;DR: The graph-based “linear framework” is used to show how the Michaelis–Menten (MM) formula arises whenever appropriate structural conditions are satisfied, both at thermodynamic equilibrium and when energy is being dissipated.
Journal ArticleDOI

Poisson indicator and Fano factor for probing dynamic disorder in single-molecule enzyme inhibition kinetics.

TL;DR: A generic stochastic model is considered to describe the kinetics of single-molecule enzyme inhibition reactions in which the turnover events correspond to conversion of substrate into a product by a single enzyme molecule in the presence of an inhibitor.
References
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Book

Stochastic processes in physics and chemistry

TL;DR: In this article, the authors introduce the Fokker-planck equation, the Langevin approach, and the diffusion type of the master equation, as well as the statistics of jump events.

Stochastic Processes in Physics and Chemistry

Abstract: Preface to the first edition. Preface to the second edition. Abbreviated references. I. Stochastic variables. II. Random events. III. Stochastic processes. IV. Markov processes. V. The master equation. VI. One-step processes. VII. Chemical reactions. VIII. The Fokker-Planck equation. IX. The Langevin approach. X. The expansion of the master equation. XI. The diffusion type. XII. First-passage problems. XIII. Unstable systems. XIV. Fluctuations in continuous systems. XV. The statistics of jump events. XVI. Stochastic differential equations. XVII. Stochastic behavior of quantum systems.
Journal ArticleDOI

Single-Molecule Enzymatic Dynamics

TL;DR: A molecular memory phenomenon, in which an enzymatic turnover was not independent of its previous turnovers because of a slow fluctuated of protein conformation, was evidenced by spontaneous spectral fluctuation of FAD.
Journal ArticleDOI

Correlating Structural Dynamics and Function in Single Ribozyme Molecules

TL;DR: The complex structural dynamics quantitatively explain the heterogeneous cleavage kinetics common to many catalytic RNAs and the intimate coupling of structural dynamics and function is likely a general phenomenon for RNA.
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