Title
Extracting signal from noise: Kinetic mechanisms from a Michaelis-Menten-like expression for enzymatic fluctuations
Date Issued
01 January 2014
Access level
open access
Resource Type
review
Author(s)
Universidad de California
Abstract
Enzyme-catalyzed reactions are naturally stochastic, and precision measurements of these fluctuations, made possible by single-molecule methods, promise to provide fundamentally new constraints on the possible mechanisms underlying these reactions. We review some aspects of statistical kinetics: a new field with the goal of extracting mechanistic information from statistical measures of fluctuations in chemical reactions. We focus on a widespread and important statistical measure known as the randomness parameter. This parameter is remarkably simple in that it is the squared coefficient of variation of the cycle completion times, although it places significant limits on the minimal complexity of possible enzymatic mechanisms. Recently, a general expression has been introduced for the substrate dependence of the randomness parameter that is for rate fluctuations what the Michaelis-Menten expression is for the mean rate of product generation. We discuss the information provided by the new kinetic parameters introduced by this expression and demonstrate that this expression can simplify the vast majority of published models. © 2013 FEBS.
Start page
498
End page
517
Volume
281
Issue
2
Language
English
OCDE Knowledge area
Bioquímica, Biología molecular
Scopus EID
2-s2.0-84892826721
PubMed ID
Source
FEBS Journal
ISSN of the container
17424658
Sources of information: Directorio de Producción Científica Scopus