News and Publications

Self-Organized Autocatalytic Networks

Understanding the molecular basis of life has been the central goal of chemical and biological sciences. However, little is known about the fundamental properties that distinguish the chemistry of living systems, which gives rise to animate characteristics, from inanimate in vitro chemical transformations. Recent advances in the mathematical understanding of complex nonlinear systems, chemistry, molecular biology, and analytical sciences are allowing a new, broad, and unique attack on the fundamental understanding of living processes.

The approach that we use is based on the following premises. Living systems are considered autonomous self-reproducing entities that operate on the basis of information. Information is originated at the molecular level by covalent chemistry, transferred and processed through noncovalent chemistry, expanded in complexity at the system level, and ultimately changed through reproduction and natural selection. In a living system, the complex blend of nonlinear molecular information-transfer processes is thought to bring about a coherent self-organized chemical system--a collective of interacting and interdependent molecular species, a "molecular ecosystem"--that as a whole can have emergent properties far greater than the simple sum of its chemical constituents. Therefore, to understand and ultimately mimic the properties of living systems, we are defining the basic forms of self-organized autocatalytic chemical networks, how the networks can be constructed, and how the interplay of information and nonlinear catalysis can lead to the expression of emergent properties (Fig. 1).

The basic methods required for the study of self-organized networks were resolved through rational de novo design of catalysts that form amide bonds (ligases and replicases) for sequence-specific peptide-fragment condensation reactions. These catalysts in turn have enabled the design and study of simple self-organized reciprocal, autocratic, and mutualistic networks that begin to display some of the basic properties often associated with living systems, such as selection, symbiosis, and error correction. Our current efforts focus on the design and characterization of more complex networks and molecular ecosystems.

Publications

Lee, D.H., Severin, K., Ghadiri, M.R. Autocatalytic networks: The transition from molecular self-replication to ecosystems. Curr. Opin. Chem. Biol. 1:491, 1997.

Lee, D.H., Severin, K., Yokobayashi, Y., Ghadiri, M.R. Emergence of symbiosis in peptide self-replication through a hypercyclic network. Nature 390:591, 1997.

Severin, K., Lee, D.H., Martinez, J.A., Vieth, M., Ghadiri, M.R. Dynamic error-correction in autocatalytic peptide networks. Angew. Chem. Int. Ed. 37:126, 1998.