Entropy demystified the "thermo"-dynamics of stochastically fluctuating systems.
In fluctuating enzyme reaction systems represented in terms of Markov processes, we show that entropy and the Second Law of Thermodynamics are mathematical consequence of the stochastic dynamics. In this kinetic approach to entropy, the Second Law is quantified with a positive entropy production rate. We argue that the concept of entropy is really a mathematical one which arises from any stochastic dynamics. Two examples from molecular biophysics, the efficiency of a motor protein ATPase and the substrate specificity of a phosphorylation-dephosphorylation cycle are discussed.
Qian
Hong
H
Department of Applied Mathematics, University of Washington, Seattle, Washington, USA.
D000251:Adenosine Triphosphatases / Q000378:metabolism; D019277:Entropy; D008390:Markov Chains; D008433:Mathematics; D008954:Models, Biological; D020409:Molecular Motor Proteins / Q000378:metabolism; D010766:Phosphorylation; D013269:Stochastic Processes; D013379:Substrate Specificity; D013816:Thermodynamics
D020409:Molecular Motor Proteins; D000251:Adenosine Triphosphatases