Biological molecular machines can process information to reduce energy losses

TL;DR

This paper demonstrates that biological molecular machines can process information to reduce energy losses, supported by theoretical proofs and computer simulations, highlighting the role of memory and organization in their efficiency.

Contribution

It introduces a generalized fluctuation theorem linking information processing to energy dissipation reduction in molecular machines, supported by simulations.

Findings

Memory utilization can reduce energy dissipation in molecular machines.

Protein motors may operate as dimers or higher assemblies due to transient memory.

Information has a physical meaning related to energy division in biological systems.

Abstract

Biological molecular machines are enzymes that simultaneously catalyze two processes, one donating free energy and second accepting it. Recent studies show that most native protein enzymes have a rich stochastic dynamics that often manifests in fluctuating rates of the catalyzed processes and the presence of short-term memory resulting from transient non-ergodicity. For such dynamics, we prove the generalized fluctuation theorem predicting a possible reduction of energy dissipation at the expense of creating some information stored in memory. The theoretical relationships are verified in computer simulations of random walk on a model critical complex network. The transient utilization of memory may turn out to be crucial for the movement of protein motors and the reason for most protein machines to operate as dimers or higher organized assemblies. From a broader physical point of view, the division of free energy into the operation and organization energy is worth emphasizing. Information can be assigned a physical meaning of a change in the value of both these functions of state.