The ability of cells to care out complex functions arises from the flexibility of proteins, which assemble into organized structures and carry out various functions in a highly dynamic way. The investigators will attempt to discover new design rules to reproduce the activity of proteins using synthetic polymers. Machine learning will be coupled to automated polymer synthesis techniques to accomplish this goal. This approach will provide the necessary building blocks for synthetic cells while uncovering unsolved questions in the origins of life. The project will also engage high school and students at a nearby minority-serving institution, providing research and learning opportunities that will encourage students to pursue STEM careers.
Proteins should be reproducible using engineering techniques and materials. In practice, it is not yet possible to control the 3-D structure of synthetic polymers with such precision. Doing so would enable the de novo design of synthetic macromolecules that can be used for the bottom-up assembly of synthetic cells and cell components. The goal of this work is to discover synthetic polymers with protein-like features. Design criteria will be identified by implementing intelligent and data-driven Design-Build-Test-Learn cycles of experimentation. We will 1) develop quantitative models for data handling and reinforced machine learning, 2) implement intelligent ‘Design-Build-Test-Learn’ routines for polymer-DNA architectures, and 3) build programmable assemblies. Until recently, these objectives were not possible. Robust methods for making large libraries of well-defined polymers were not available. The recent discovery of oxygen tolerant and automated living polymer chemistry makes it possible to reliably and routinely Design-Build complex polymer architectures with features similar to proteins. In this project, the automation will be upgraded with high throughput analytics and machine learning to establish quantitative structure-activity relationship models for the de novo design of compact and organized structures. Such semi-automatic and reinforced exploration of the highly diverse landscape of macromolecular assembly will lead to the design of protein-like polymers and their use as molecular building blocks for the assembly of synthetic cells and cell components.
This project is being funding jointly between the Cellular and Biochemical Engineering Program in ENG/CBET and the Macromolecular, Supramolecular, and Nanochemistry Program in MPS/CHE.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
