The copying of a polymer sequence into a new polymer is central to biology. Although the growth of a copy attached to its template has received much attention, effective copies must persist after template separation. We show that this separation has three fundamental thermodynamic effects. Firstly, attractive polymer-template interactions favor polymerization but inhibit separation, playing a double-edged role. Secondly, given separation, more work is always necessary to create a specific copy than a non-specific polymer of the same length. Finally, the mixing of copies from distinct templates makes correlations between template and copy sequences unexploitable, combining with copying inaccuracy to reduce the free energy stored in a polymer ensemble. This lower stored free energy in turn reduces the minimal entropy generation during non-specific depolymerization .
Living cells use readout molecules to record the state of receptor proteins, similar to measurements or copies in typical computational devices. But is this analogy rigorous? Can cells be optimally efficient, and if not, why? We show that , as in computation, a canonical biochemical readout network generates correlations; extracting no work from these correlations sets a lower bound on dissipation. For general input, the biochemical network cannot reach this bound, even with arbitrarily slow reactions or weak thermodynamic driving. It faces an accuracy-dissipation trade-off that is qualitatively distinct from and worse than implied by the bound, and more complex steady-state copy processes cannot perform better. Nonetheless, the cost remains close to the thermodynamic bound unless accuracy is extremely high. Additionally, we show that biomolecular reactions could be used in thermodynamically optimal devices under exogenous manipulation of chemical fuels, suggesting an experimental system for testing computational thermodynamics .
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The copying of a polymer sequence into a new polymer is central to biology. Although the growth of a copy attached to its template has received much attention, effective copies must persist after template separation.
Living cells use readout molecules to record the state of receptor proteins, similar to measurements or copies in typical computational devices. But is this analogy rigorous? Can cells be optimally efficient, and if not, why?
R
this separation has three fundamental thermodynamic effects. Firstly, attractive polymer-template interactions favor polymerization but inhibit separation, playing a double-edged role. Secondly, given separation, more work is always necessary to create a specific copy than
, as in computation,
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non-specific polymer of the same length. Finally, the mixing of copies from distinct templates makes correlations between template and copy sequences unexploitable, combining with copying inaccuracy to reduce the free energy stored in a polymer ensemble. This lower stored free energy in turn reduces the minimal entropy generation during non-specific depolymerization
canonical biochemical readout network generates correlations; extracting no work from these correlations sets a lower bound on dissipation. For general input, the biochemical network cannot reach this bound, even with arbitrarily slow reactions or weak thermodynamic driving. It faces an accuracy-dissipation trade-off that is qualitatively distinct from and worse than implied by the bound, and more complex steady-state copy processes cannot perform better. Nonetheless, the cost remains close to the thermodynamic bound unless accuracy is extremely high. Additionally, we show that biomolecular reactions could be used in thermodynamically optimal devices under exogenous manipulation of chemical fuels, suggesting an experimental system for testing computational thermodynamics