NSF requires disclosure of AI tool usage in proposal preparation. Ensure you disclose the use of FindGrants' AI drafting in your application.
NSF
NON-TECHNICAL SUMMARY: Materials that accelerate reactions or selectively absorb chemicals are found in everyday household products, as well as industrial processes. Many of these materials are porous, with molecular structures resembling sponges, allowing them to trap molecules. Among them, frameworks are a large class of crystalline porous materials. Engineering the pore shape and chemical composition of a framework controls what molecules can be absorbed and what chemical reactions occur within it. Inspired by the modular architecture of proteins, there is growing interest in making frameworks out of peptides, which are simpler fragments of proteins. However, peptides are still relatively complex molecules and there are many unknowns regarding how to make them self-assemble them into porous materials. This proposal aims to append peptides with flat molecules that are prone to stacking, called aromatic π-stackers. Aromatic π-stackers are highly diverse in shape, size, and other properties, and they have well-established assembly rules that could be used to predictably guide the peptide assembly, allowing for more straightforward and rational synthesis of sophisticated peptide frameworks. Specifically, this proposal seeks to uncover the rules that will allow chemists to target peptide framework structure and dynamics through design of the π-stacker unit. If successful, these porous peptide frameworks can further evolve through mutations of the peptide sequence to meet a broad range of applications improving sustainability and health. In addition, this proposal will develop educational 3-D printed peptide model kits aimed at increasing intuition for complicated protein interactions through the power of touch. TECHNICAL SUMMARY: Porous crystalline materials (or “frameworks”) possess pores or channels that provide 3-D microenvironments for interacting with molecules, making these materials broadly useful in separation and catalytic processes. Most frameworks are composed of inorganic or organic building blocks, but there is significant interest in using bio-derived components to construct pores that better resemble the complex active sites of proteins, as these protein-mimicking frameworks could be well-suited for broadly important applications like stereoselective catalysis, chiral separations, molecular sensing, and drug-delivery. Small peptides are potentially ideal building blocks to achieve this objective since they are simpler fragments of proteins; however, it remains difficult to precisely control peptide assembly. The objective of this proposal is to establish predictable strategies for making porous peptide materials by combining peptides with tailored π-stacking aromatic groups that drive the assembly and provide added function. This proposal will develop new porous topologies by rationally tuning the π-stackers, which is expected to also impact framework conformational dynamics upon molecular recognition. Additionally, to better teach the complicated concepts of protein and peptide assembly, 3-D printed molecular puzzles will be developed to engage tactile skills. Tactile manipulation adds to visual learning, providing a multisensory approach to increase intuition for understanding intricate protein interactions. 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.
Up to $288K
2030-02-28
Detailed requirements not yet analyzed
Have the NOFO? Paste it below for AI-powered requirement analysis.
One-time $749 fee · Includes AI drafting + templates + PDF export
Category I: CloudBank 2: Accelerating Science and Engineering Research in the Commercial Cloud
NSF — up to $24M
Category I: Nexus: A Confluence of High-Performance AI and Scientific Computing with Seamless Scaling from Local to National Resources
NSF — up to $24.0M
Research Infrastructure: Mid-scale RI-1 (MI:IP): Dual-Doppler 3D Mobile Ka-band Rapid-Scanning Volume Imaging Radar for Earth System Science
NSF — up to $20.0M
A Scientific Ocean Drilling Coordinating Office for the US Community
NSF — up to $17.6M
Category I: AMA27: Sustainable Cyber-infrastructure for Expanding Participation
NSF — up to $13.8M
Graduate Research Fellowship Program (GRFP)
NSF — up to $9.0M