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2003 Annual Science Report

Scripps Research Institute Reporting  |  JUL 2002 – JUN 2003

Ghadiri - Self-Reproducing Molecular Systems and Darwinian Chemistry

4 Institutions
3 Teams
0 Publications
0 Field Sites
Field Sites

Project Progress

The goal of our research program is to design, discover, and understand the primary factors responsible for directing the self-organization of inanimate molecules into the animate chemistry of living systems. We have envisioned that a rational process that can be used to design, predict, and manipulate complex self-organized nonlinear chemical systems would be an invaluable tool in this regard as well as for modeling network architectures of biological processes and for better understanding of the collective behavior of large networks of interacting dynamical systems. In the past year we have succeeded in developing the first de novo synthetic system that can be theoretically and experimentally analyzed at various desired levels of complexity. The self-organized nonlinear chemical system is based on template-directed coiled-coil peptide fragment condensation reactions that we have previously shown to exhibit substrate specific ligase and replicase activities. A scoring algorithm was devised to analyze and graph plausible coiled-coil interactions resulting from 81×81 template-directed auto- and cross-catalytic reaction pathways. The resulting “small-world” network was predicted to have global and local efficiencies similar to the natural systems and appear to be clustered and have hierarchical organization. Nine nodes were selected from the graph and their network formation was experimentally analyzed. The resulting self-organized chemical system displays 21 edges, including three autocatalytic processes in close agreement with the graph analysis predictions. The synthetic network shows graph architecture that is strikingly similar to the organization of complex biological systems. Our studies indicate that complex networks can be rationally designed and constructed and their properties experimentally verified in order to gain insights into the dynamics of complex nonlinear chemical networks. We hope that this synthetic “bottom-up” approach would serve as a model for addressing the large-scale structural and functional organization of cellular networks and their plausible origins. This approach should allow rigorous experimental and theoretical analysis of network architecture and aid in better understanding of factors contributing to system self-organization and display of emergent phenomena in living systems.