Evolutionary optimization has been successfully used to increase our understanding of key properties of biochemical systems. Traditional optimization is, however, often insufficient for gaining deeper insights into the evolution of such systems because usually there is a mutual relationship between the properties optimized by evolution and the properties of the environment. Thus, by evolving towards optimal properties, organisms change their environment, which in turn alters the optimum. Evolutionary game theory provides an appropriate framework for analyzing evolution in such 'dynamic fitness landscapes'. We therefore argue that it is a promising approach to studying the evolution of biochemical systems. Indeed, recent studies have applied evolutionary game theory to key issues in the evolution of energy metabolism.