Literature DB >> 16351180

Nonequilibrium steady state of a nanometric biochemical system: determining the thermodynamic driving force from single enzyme turnover time traces.

Wei Min1, Liang Jiang, Ji Yu, S C Kou, Hong Qian, X Sunney Xie.   

Abstract

A single enzyme molecule in a living cell is a nanometric system that catalyzes biochemical reactions in a nonequilibrium steady-state condition. The chemical driving force, Deltamu, is an important thermodynamic quantity that determines the extent to which the reaction system is away from equilibrium. Here we show that Deltamu for an enzymatic reaction in situ can be determined from the nonequilibrium time traces for enzymatic turnovers of individual enzyme molecules, which can now be recorded experimentally by single-molecule techniques. Three different Deltamu estimators are presented from principles of nonequilibrium statistical mechanics: fluctuation theorem, Kawasaki identity, and fluctuation dissipation theorem, respectively. In particular, a maximum likelihood estimation method of Deltamu has been derived based on fluctuation theorem. The statistical precisions of these three Deltamu estimators are analyzed and compared for experimental time traces with finite lengths.

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Year:  2005        PMID: 16351180     DOI: 10.1021/nl0521773

Source DB:  PubMed          Journal:  Nano Lett        ISSN: 1530-6984            Impact factor:   11.189


  4 in total

1.  Note: on the relation between Lifson-Jackson and Derrida formulas for effective diffusion coefficient.

Authors:  Juris R Kalnin; Alexander M Berezhkovskii
Journal:  J Chem Phys       Date:  2013-11-21       Impact factor: 3.488

2.  Stochastic thermodynamics of single enzymes and molecular motors.

Authors:  U Seifert
Journal:  Eur Phys J E Soft Matter       Date:  2011-03-15       Impact factor: 1.890

3.  Quantifying the flux as the driving force for nonequilibrium dynamics and thermodynamics in non-Michaelis-Menten enzyme kinetics.

Authors:  Qiong Liu; Jin Wang
Journal:  Proc Natl Acad Sci U S A       Date:  2019-12-26       Impact factor: 11.205

4.  Discrimination of DNA Methylation Signal from Background Variation for Clinical Diagnostics.

Authors:  Robersy Sanchez; Xiaodong Yang; Thomas Maher; Sally A Mackenzie
Journal:  Int J Mol Sci       Date:  2019-10-27       Impact factor: 5.923

  4 in total

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