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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Rochester |
| Country | United States |
| Start Date | Jun 01, 2021 |
| End Date | May 31, 2023 |
| Duration | 729 days |
| Number of Grantees | 3 |
| Roles | Principal Investigator; Co-Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2103553 |
Non-Technical Summary:
This project will explore the use of computationally designed peptides to enhance drug delivery systems, aligning with NSF’s mission ‘To promote the progress of science’ and ‘to advance the national health prosperity, and welfare’. Nanoparticles have tremendous potential for delivering new, highly promising therapeutics to specific locations withing the body, enhancing drug potency, and reducing side-effects.
However, blood proteins adsorb to nanoparticles, resulting in clearance. Protein adsorption reduces the ability of nanoparticles to reach tissue targets organs and tumors. Existing materials to control nanoparticle protein adsorption are limited in number.
Furthermore, they are implicated in allergy-like immune system responses after repeated exposures, which has been highlighted recently by the mRNA vaccines for COVID19. This project explores computationally designed peptides with partially randomized sequences to make a new class of diverse anti-protein adsorption options, which, through randomized design, will avoid allergic reactions and other long-term immunological side effects.
These materials are expected to be versatile for multiple nanoparticle systems and will enable improved drug delivery. The research activities will be integrated with Rochester’s ongoing K-12 education and outreach efforts, including the “Teach for Teachers” program and graduate/undergraduate researcher mentorship.
Technical Summary:
Non-specific protein adsorption to nanoparticle (NP) drug delivery systems (DDS) has challenged the tremendous promise of NP therapeutics by reducing target tissue accumulation and NP delivery function and increasing off-target accumulation in the mononuclear phagocyte system (MPS). Anti-fouling materials currently used to combat protein adsorption, such as poly(ethylene glycol), have limited chemical diversity and have been recently demonstrated to be antigenic, as highlighted by adverse reactions to PEGylated mRNA vaccine approaches for COVID19.
This project seeks to develop computationally designed anti-fouling zwitterionic peptides (ZIPs) with semi-randomized sequences to create a diverse new class of anti-fouling materials (srZIPs) resistant to adaptive immunity. The computational design considers peptide-peptide and peptide-protein interactions and evaluates potential ZIPs with the lowest interaction potential, as well as amino acid substitutions that maintain overall interaction character to allow semi-randomization of ZIP composition for diversity. srZIPs will be tested in existing NP formulations and compared directly to PEGylation.
By investigating links between design parameters, in vitro behavior, biodistribution, pharmacokinetics, and immunogenicity, this project will further the understanding of the interplay between anti-fouling material composition and clinically relevant NP performance parameters while establishing a new category of anti-fouling functionalities.
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.
University of Rochester
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