Topological, Compositional, and Dynamic Information in Chemical Reaction Systems

Abstract

Chemical reaction systems hold great promise for mimicking the fundamental processes of life and as the basis for new, sophisticated chemical technologies. These systems are conventionally viewed from a molecular perspective, in which their structure and behavior are controlled through molecular design. Achieving the ambitions of systems chemistry entails increasing system complexity and diversity from a few well‐understood components to large networks in which precise interactions are challenging to predict and control. Intuitive approaches are therefore required to design and understand complex chemical systems, particularly in experimental investigations. Using the formose reaction as a model system, this Perspective discusses three kinds of information that provide a basis for understanding and reasoning about complex chemical reaction systems. Reaction topological information, condensed into reaction rules, provides a means to compactly describe reaction systems, generate reaction network topologies, and reason about key reaction processes. Compositional information can be quantified using information‐theoretic measures that describe reaction outcomes and their effective degrees of freedom. Dynamic information arises from the time‐dependent processing of inputs by reaction networks and can reveal modular, covariant responses to environmental perturbations. These concepts may prove useful for exploring prebiotic evolution, designing chemical systems for computation, and engineering functional chemical reaction networks.