Designing Luminescent Biomaterials from First Principles
INSTITUTION
University of North Carolina at Charlotte, NC
PRINCIPAL INVESTIGATOR
Shunji Egusa
FUNDING
$438K
YEAR
2024
MOONBASE SCORE
Still being scored
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Abstract
NON-TECHNICAL SUMMARY: Cells are the amazing machinery in living organisms that enable life by biological function through chemical and physical processes. It all happens within their tiny size of one to ten microns, but these tiny cells are visually transparent. To understand their internal structures and processes in detail while they are doing their work, special agents are needed along with a microscope. One such agent is green fluorescent protein, or GFP, which revolutionized the way biological processes at sub-cellular scale are visualized and understood today. In addition to GFP, countless natural or synthetic proteins are expected to have untapped potential for enabling visualization of live cells as well as for other technological applications. However, identifying a protein structure optimal for a particular technological application is not trivial. The goal of this project is to tackle this challenge and discover new protein materials by characterizing the chemical and physical properties of known protein materials with desired properties. This will be done in combination with the screening of other related proteins aided by machine learning. Finally, this project also provides graduate and undergraduate students with interdisciplinary training in biomaterials field and extends the hands-on research experience to local K-12 teachers through outreach programs. TECHNICAL SUMMARY: This project aims to investigate a new class of luminescent protein materials. Luminescent protein-metal compounds are important materials with demonstrated versatile applications in imaging, sensing, as well as tracking agents for biological and environmental studies. These compounds exhibit luminescence that is stable in wide range of pH, but via mechanisms that are unknown. In this project, multi-protein time-resolved spectroscopic measurements are combined with pan-protein analyses via machine learning using iterative Bayesian optimization for the model training, prediction, and experiments. The combined analyses allow determination of the mechanistic origin of the luminescence and the structure of the luminophore in proteins. The elucidated mechanism and the structural origin of luminescence enable the ability to identify, design, and develop novel biological luminophores. This project provides graduate and undergraduate students with interdisciplinary research opportunities and training as future workforce in biomaterials field and extends the hands-on research experience to local K-12 teachers through outreach programs at the PI’s university. 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.
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