The channel capacity and information density of biochemical signaling cascades

TL;DR

This paper develops a theoretical framework using the fluctuation theorem to quantify the channel capacity and information density of biochemical signaling cascades, enabling more precise analysis of cellular communication systems.

Contribution

It introduces a novel quantitative method for calculating channel capacity and information density of biochemical signaling cascades based on entropy production rates.

Findings

Channel capacity can be derived from the average entropy production rate.

The method was applied to the MAP kinase signaling cascade.

Quantitative analysis of BSCs becomes feasible with this approach.

Abstract

Living cell signaling systems include multistep biochemical signaling reaction cascades (BSCs) comprising modifications of molecular signaling proteins. Substantial data on BSCs have been accumulated in the field of molecular biology and the analysis of signaling systems requires qualitative evaluation. However, quantification of the information and channel capacity of BSCs has not been focused on from the perspective of information theory. In the current study, we aimed to derive basic equations for describing the channel capacity and information density of BSCs using the fluctuation theorem. From the results, channel capacity and information density can be described using the average entropy production rate when the signaling system is minimally redundant. The channel capacity could actually be calculated for the mitogen-activated protein kinase BSC when it was minimally redundant. This quantitative method of examination is applicable to the quantitative analysis of BSCs.