Performance limits and trade-offs in entropy-driven biochemical computers

• Published in: Journal of theoretical biology Vol. 443; pp. 1 - 9
• Main Author: Chu, Dominique
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 14.04.2018
• Subjects: Biochemical Phenomena; Biological computing; Computers, Molecular; Cost of computation; Entropy; Information thermodynamics; Linear noise approximation; Models, Biological; Cost of computation; Linear noise approximation; Biological computing; Information thermodynamics
• ISSN: 0022-5193; 1095-8541; 1095-8541
• DOI: 10.1016/j.jtbi.2018.01.022

•It is discussed what computation might mean in the context of biochemical networks.•A model of biochemical computation based on continuous Markov chains is presented.•It is shown that computation leads to a trade-off between energy cost and the accuracy of the computation.•Trade-offs involving time occur only when it is taken into account that the result of the computation needs to be measured. It is now widely accepted that biochemical reaction networks can perform computations. Examples are kinetic proof reading, gene regulation, or signalling networks. For many of these systems it was found that their computational performance is limited by a trade-off between the metabolic cost, the speed and the accuracy of the computation. In order to gain insight into the origins of these trade-offs, we consider entropy-driven computers as a model of biochemical computation. Using tools from stochastic thermodynamics, we show that entropy-driven computation is subject to a trade-off between accuracy and metabolic cost, but does not involve time-trade-offs. Time trade-offs appear when it is taken into account that the result of the computation needs to be measured in order to be known. We argue that this measurement process, although usually ignored, is a major contributor to the cost of biochemical computation.