Optimal Control of Evolutionary Dynamics

TL;DR

This paper demonstrates how biochemical networks utilize optimal control strategies in their evolutionary processes, explaining extremization patterns in redox potentials through an analytical framework based on optimal control theory.

Contribution

It introduces an analytical framework applying optimal control theory to evolutionary dynamics, revealing how biochemical networks optimize fitness measures.

Findings

Redox potentials of electron transport proteins are extremized.

Biochemical networks exploit optimal control strategies during evolution.

Optimal control theory explains observed evolutionary patterns.

Abstract

Elucidating the fitness measures optimized during the evolution of complex biological systems is a major challenge in evolutionary theory. We present experimental evidence and an analytical framework demonstrating how biochemical networks exploit optimal control strategies in their evolutionary dynamics. Optimal control theory explains a striking pattern of extremization in the redox potentials of electron transport proteins, assuming only that their fitness measure is a control objective functional with bounded controls.