Thermodynamically Driven Signal Amplification
Joshua Petrack, David Soloveichik, David Doty

TL;DR
This paper explores how thermodynamic binding networks can be designed to exponentially amplify molecular signals, providing a robust alternative to kinetic-based methods like PCR, and establishes fundamental bounds on amplification capabilities.
Contribution
It introduces a method to design TBNs that can exponentially amplify signals from a single molecule and proves an upper bound on the maximum possible amplification.
Findings
Exponential signal amplification is achievable with specific TBN designs.
A doubly exponential upper bound limits the amplification possible in TBNs.
Thermodynamic systems can change states significantly with minimal molecular input.
Abstract
The field of chemical computation attempts to model computational behavior that arises when molecules, typically nucleic acids, are mixed together. Thermodynamic binding networks (TBNs) is a highly abstracted model that focuses on which molecules are bound to each other in a "thermodynamically stable" sense. Stability is measured based only on how many bonds are formed and how many total complexes are in a configuration, without focusing on how molecules are binding or how they became bound. We study the problem of signal amplification: detecting a small quantity of some molecule and amplifying its signal to something more easily detectable. This problem has natural applications such as disease diagnosis. By focusing on thermodynamically favored outcomes, we seek to design chemical systems that perform the task of signal amplification robustly without relying on kinetic pathways that…
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