The energy cost and optimal design of networks for biological discrimination

TL;DR

This paper establishes a fundamental error-cost bound for biological proofreading networks, revealing how different enzymes operate near or far from this limit based on their functional constraints and energy dissipation.

Contribution

It introduces a theoretical error-cost bound for proofreading networks, linking kinetic parameters to dissipation and error, and analyzes its implications for biological enzymes.

Findings

DNA replication by T7 DNA polymerase is nearly optimized.

E. coli IleRS operates close to the bound but is limited by speed.

E. coli ribosome functions in a high-dissipation regime to increase speed.

Abstract

Many biological processes discriminate between correct and incorrect substrates through the kinetic proofreading mechanism which enables lower error at the cost of higher energy dissipation. Elucidating physicochemical constraints for global minimization of dissipation and error is important for understanding enzyme evolution. Here, we identify theoretically a fundamental error-cost bound which tightly constrains the performance of proofreading networks under any parameter variations preserving the rate discrimination between substrates. The bound is kinetically controlled, i.e. completely determined by the difference between the transition state energies on the underlying free energy landscape. The importance of the bound is analyzed for three biological processes. DNA replication by T7 DNA polymerase is shown to be nearly optimized, i.e. its kinetic parameters place it in the immediate proximity of the error-cost bound. The isoleucyl-tRNA synthetase (IleRS) of E. coli also operates close to the bound, but further optimization is prevented by the need for reaction speed. In contrast, E. coli ribosome operates in a high-dissipation regime, potentially in order to speed up protein production. Together, these findings establish a fundamental error-dissipation relation in biological proofreading networks and provide a theoretical framework for studying error-dissipation trade-off in other systems with biological discrimination.