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Single‐molecule enzymology à la Michaelis–Menten
Author(s) -
Grima Ramon,
Walter Nils G.,
Schnell Santiago
Publication year - 2014
Publication title -
the febs journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 204
eISSN - 1742-4658
pISSN - 1742-464X
DOI - 10.1111/febs.12663
Subject(s) - enzyme kinetics , rate equation , reaction rate constant , reaction rate , statistical physics , molecule , chemical kinetics , stochastic modelling , kinetics , chemistry , master equation , mathematics , biological system , computer science , enzyme , physics , statistics , biology , classical mechanics , quantum mechanics , biochemistry , organic chemistry , active site , quantum , catalysis
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.