Information Propagation in Molecular Templating Networks is Constrained by Pathway Free Energy Differences

Core Concepts

The specificity and entropy of product distributions in molecular templating networks are bounded by the free-energy differences along pathways that create and destroy the products, regardless of the complexity of the underlying reaction network.

Abstract

The content discusses the thermodynamic constraints on the distribution of products in molecular templating networks, where multiple distinct products can be selectively produced from a shared set of input molecules using catalytic templates. Key highlights: The steady-state concentrations of the products are bounded by the free-energy changes along the pathways that create and destroy each product, even if the underlying reaction network is complex. The distribution that maximizes the probability of a single product (specificity maximization) is generally different from the distribution that minimizes the entropy of the product ensemble (entropy minimization). For a large number of possible products M, perfect specificity for a single product in steady state requires a free-energy difference between pathways ∆G > ln M, but even for ∆G << ln M, a vanishingly small fraction of the possible products can dominate the ensemble. The optimal system that minimizes the entropy of the product distribution is a "pseudo-equilibrium" one, where each product is coupled to a single dominant pathway, rather than a system that systematically assembles and degrades products. The bounds derived apply to the steady-state distribution, but arbitrary precision can be achieved at finite times without requiring large ∆G.

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Key Insights Distilled From

Information propagation in far-from-equilibrium molecular templating networks is optimised by pseudo-equilibrium systems with negligible dissipation

by Benjamin Qur... at arxiv.org 04-04-2024

https://arxiv.org/pdf/2404.02791.pdf

Deeper Inquiries

How do the bounds on product distribution change if the thermodynamic stabilities of the products are not equal

If the thermodynamic stabilities of the products are not equal, the bounds on product distribution will be affected. The upper and lower bounds on the concentrations of the products, which are determined by the free-energy changes along the pathways, will be different for each product. This means that the constraints on the product distribution will vary depending on the thermodynamic stability of each product. The specificity maximization and entropy minimization will be influenced by these differences in thermodynamic stability, leading to a more complex optimization problem.

Can the bounds be extended to systems where the input monomers are not held at constant concentration by a chemostat

The bounds derived in the context of the system where input monomers are held at constant concentration by a chemostat may not directly apply to systems where this assumption does not hold. In such cases, the dynamics of the system, including the steady-state concentrations of the products, may be different. The bounds may need to be re-evaluated or modified to account for the variability in the concentrations of the input monomers. The extension of these bounds to systems without a constant concentration of input monomers would require a re-examination of the underlying assumptions and mathematical framework.

What are the implications of these bounds for the evolution and optimization of biological information processing systems

The bounds on product distribution have significant implications for the evolution and optimization of biological information processing systems. By understanding the constraints imposed by these bounds, researchers can gain insights into the thermodynamic costs and efficiencies of maintaining specific product distributions in biological systems. These bounds can guide the design and engineering of molecular templating networks to achieve optimal information propagation and minimize entropy production. Additionally, the bounds provide a framework for studying the trade-offs between specificity, entropy, and thermodynamic stability in biological systems, shedding light on the fundamental principles governing information processing in living organisms.