Information-to-energy trade-offs and the optimal alphabet of polymer replication
TLDR
This paper models polymer replication as an information channel, revealing information-to-energy trade-offs and why DNA's alphabet prioritizes stability over efficiency.
Key contributions
- Frames polymer replication as a communication channel to analyze information transmission and energy costs.
- Shows small error fractions lead to substantial information loss due to nonlinear error-mutual information relationship.
- Identifies an optimal alphabet size for information-to-energy efficiency, determined by per-monomer assembly free energy.
- Suggests DNA's four-base alphabet prioritizes suppressing spontaneous assembly over information-to-energy efficiency.
Why it matters
This work provides a novel information-theoretic framework for understanding polymer replication, including biological systems like DNA. It highlights fundamental trade-offs between information fidelity, energy cost, and alphabet size, offering insights into evolutionary pressures. The findings can guide the design of future synthetic replication systems.
Original Abstract
We analyze information transmission in a recently proposed coarse-grained model of polymer replication by framing it as a communication channel between templates and copies. By calculating the mutual information in the steady-state limit of long chains, we recover the accurate-random phase diagram and establish that the information per-monomer depends solely on template specificity within the accurate regime. Crucially, even in the accurate region, small error fractions lead to substantial information loss due to the nonlinear relationship between errors and mutual information. Examining the information-to-energy cost ratio reveals non-monotonic behavior as a function of monomer alphabet size, with an optimum determined primarily by the per-monomer assembly free energy. For DNA's four-base alphabet, we find that the observed effective assembly energy (at least $14\,k_B T$) places the system far from the information-transmission optimum, suggesting that biological replication may prioritize the suppression of spontaneous random assembly over information-to-energy efficiency. We also characterize achievable rate-fidelity trade-offs using Shannon bounds, providing a theoretical framework for evaluating future proofreading mechanisms in ensemble models.
📬 Weekly AI Paper Digest
Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.