Publication: Autocatalytic, bistable, oscillatory networks of biologically relevant organic reactions
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Abstract
Networks of organic chemical reactions are centrally important in life, and were likely to have played a central role in its origins. Network dynamics regulate cell division, circadian rhythms, nerve impulses, chemotaxis, and guide development of organisms. Although out-of-equilibrium networks of chemical reactions have the potential to display emergent network dynamics such as spontaneous pattern formation, bistability, and periodic oscillations, the principles that enable networks of organic reactions to develop complex behaviors are incompletely understood. Here we describe a network of biologically relevant organic reactions (amide formation, thiolate-thioester exchange, thiolate-disulfide interchange, and conjugate addition) that displays bistability and oscillations in concentrations of organic thiols and amides. Oscillations arise from the interaction between three subcomponents of the network: (i) an autocatalytic cycle that generates thiols and amides from thioesters and dialkyl disulfides; (ii) a trigger that controls autocatalytic growth; and (iii) inhibitory processes that remove activating thiol species produced during the autocatalytic cycle. In contrast to previous studies demonstrating oscillations and bistability using highly evolved biomolecules (i.e., enzymes and DNA) or inorganic molecules of questionable biochemical relevance (e.g. those used in Belousov-Zhabotinsky-type reactions), the organic molecules used in our network are relevant to current metabolism and similar to those that might have existed on early Earth. By using small organic molecules to build a network of organic reactions with autocatalytic, bistable, and oscillatory behavior, we identified principles that clarify how dynamic networks relevant to life might possibly have developed. In the future, modifications of this network will clarify the influence of molecular structure on the dynamics of reaction networks, and may enable the design of biomimetic networks, and of synthetic self-regulating and evolving chemical systems.