Binding of transcription factors adapts to resolve information-energy trade-off

TL;DR

This paper models transcription factor-DNA binding as an information transfer problem, revealing that binding energies are optimized to maximize information gain per energy, balancing energetic costs and informational efficiency.

Contribution

It introduces a theoretical framework linking binding energy and information transfer, supported by analysis of diverse transcription factors across species.

Findings

Binding energies nearly maximize information gain per energy.

Transcription factor binding adapts to optimize information transfer.

Supports the idea of information gain as a universal design principle.

Abstract

We examine the binding of transcription factors to DNA in terms of an information transfer problem. The input of the noisy channel is the biophysical signal of a factor bound to a DNA site, and the output is a distribution of probable DNA sequences at this site. This task involves an inherent tradeoff between the information gain and the energetics of the binding interaction - high binding energies provide higher information gain but hinder the dynamics of the system as factors are bound too tightly. We show that adaptation of the binding interaction towards increasing information transfer under a general energy constraint implies that the information gain per specific binding energy at each base-pair is maximized. We analyze hundreds of prokaryote and eukaryote transcription factors from various organisms to evaluate the discrimination energies. We find that, in accordance with our theoretical argument, binding energies nearly maximize the information gain per energy. This work suggests the adaptation of information gain as a generic design principle of molecular recognition systems.