Stochastic innovation as a mechanism by which catalysts might self-assemble into chemical reaction networks

Abstract

We develop a computer model for how two different chemical catalysts in solution, A and B, could be driven to form AB complexes, based on the concentration gradients of a substrate or product that they share in common. If A's product is B's substrate, B will be attracted to A, mediated by a common resource that is not otherwise plentiful in the environment. By this simple physicochemical mechanism, chemical reactions could spontaneously associate to become chained together in solution. According to the model, such catalyst self-association processes may resemble other processes of ''stochastic innovation,'' such as Darwinian evolution in biology, that involve a search among options, a selection among those options, and then a lock-in of that selection. Like Darwinian processes, this simple chemical process exhibits cooperation, competition, innovation, and a preference for consistency. This model may be useful for understanding organizational processes in prebiotic chemistry and for developing new kinds of self-organization in chemically reacting systems. innovation,'' whereby a biological, physical, or sociological system: (i) searches among viable options, then (ii) selects one or more of those options that is ''best'' by some metric, then (iii) locks in that selection for the future. In biology, the best-known example is Darwinian evolution (1), where variation is the term that describes the search step, and natural selection is the term that describes steps (i) and (ii). Stochastic innovation occurs in learning and memory and neural development, where the correlated firings of neurons can lead to changes in synaptic strength (2-5), and to the development of the vascular system, where new blood vessels grow toward oxygen-deprived cells (6,7).Stochastic innovation appears in other arenas, too. Human beings, businesses, and social organizations evolve through decision-making: they search among the options available to them, make self-serving choices, then remember and act on those decisions in the future. Social insects, like ants, search randomly for food, then lock in the discovery with chemical trails for the rest of the colony (8, 9). Computer models of artificial life and artificial societies show that stochastic innovation can meet apparent goals that were not programmed into them at earlier times (10, 11). The power of stochastic innovation is that it can lead to complex behaviors or organizational structures that are responsive to changes in the environment, even though such processes are unguided, unplanned, and stochastic.Our interest here is in whether stochastic innovation might also be achievable in chemistry and biochemistry. Can chemical and biochemical reactions be chained together in complex and innovative ways, driven only by simple physicochemical search and selection processes? If so, it may be useful, not only as a tool in chemistry and biochemistry, but also for giving insights into the processes of chemical organization that may have occurred during prebiotic evolution.Here, we propose a ...

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