Oscillations in Networks of Organic and Enzymatic Reactions

Functionality of biological cell comes from the well-orchestrated action of many biochemical reactions. These reactions form a dissipative, out-of-equilibrium chemical network in which the concentrations of interacting—and reacting—molecules are autonomously regulated in space and time. The mechanisms of self-regulation that enable cellular stability, growth, and adaption are, however, difficult to recreate in synthetic systems, slowing progress in the development of smart materials and drug.

Organic molecules, which can have innumerable variations in molecular structure, could enable network properties to be fine-tuned—a property essential to both functional design of network dynamics and evolutionary convergence. The design principles that enable the assembly of individual organic reactions into networks of reactions with functional behaviors, however, are incompletely understood.

We have recently developed two classes of programmable reaction networks consisting of organic molecules that can be structurally modified: (i) trypsin based networks,¹ (ii) thiols-thioesters based networks.² We designed oscillators from these chemistries as representative examples of functional systems (chemical clock) that require both positive and negative feedback within a system. In the independent work, we compartmentalized a “molecular program” that consisted of the mixture of trypsinogen (a zymogen of trypsin) with its strong inhibitor. When subjected to the spatially ununiform signal of trypsin, this system can recognize the density of trypsin sources.

The structures of the presented reaction networks are easy to tune through structural modification of the constituent organic molecules. It, thus, affords new opportunities to examine the influence of molecular structure on reaction network dynamics, to build biomimetic networks, and to design synthetic self-regulating and evolving chemical systems.

[1] S. N. Semenov, et al., Nat. Chem., 2015, 7, 160-165.

[2] S. N. Semenov, et al., Nature, 2016, 537, 656 - 660.