Abstract
Living systems are open systems, where the laws of nonequilibrium thermodynamics play the important role. Therefore, studying living systems from a nonequilibrium thermodynamic aspect is interesting and useful. In this review, we briefly introduce the history and current development of nonequilibrium thermodynamics, especially that in biochemical systems. We first introduce historically how people realized the importance to study biological systems in the thermodynamic point of view. We then introduce the development of stochastic thermodynamics, especially three landmarks: Jarzynski equality, Crooks’ fluctuation theorem and thermodynamic uncertainty relation. We also summarize the current theoretical framework for stochastic thermodynamics in biochemical reaction networks, especially the thermodynamic concepts and instruments at nonequilibrium steady state. Finally, we show two applications and research paradigms for thermodynamic study in biological systems.
Highlights
The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, AAIC, Peking University, Abstract: Living systems are open systems, where the laws of nonequilibrium thermodynamics play the important role
The dynamics of this system can be regarded as a single molecule jumping between the three states X1, X2, X3, with the probability stopping at each state pi equals to the concentration of each component at steady state
How to define the thermodynamic quantities in chemical reaction systems? they are well defined in equilibrium statistical mechanics, these definitions are traditionally only proved to hold at equilibrium state
Summary
In the framework of stochastic process, chemical reactions are considered as a series of Markov processes described by chemical master equations (CMEs) [41,42]. Suppose there is a system consisting of three components X1 , X2 , X3 which can be transferred to each other by unimolecular reactions, i.e., k31 The dynamics of this system can be regarded as a single molecule jumping between the three states X1 , X2 , X3 , with the probability stopping at each state pi equals to the concentration of each component at steady state. Generally the dynamics of a CRN can be regarded the system jump between different microscopic states via Markov processes and can be described by a CME. Such description in terms of stochastic process is proposed much earlier than the research on NESS or stochastic thermodynamics and had already brought in many important applications.
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