Nanoparticle Materials as Chemical and Biological Tools for Peptides and Proteins

NON-TECHNICAL SUMMARY Proteins carry out many of the most important tasks in living cells, but their functions often depend on small chemical changes made at exactly the right location on the protein. In nature, specialized enzymes perform these changes with remarkable precision. Chemists, however, still lack general and selective methods for modifying common proteins at chosen sites under mild conditions. This project develops new synthetic materials that mimic the selectivity of natural protein-modifying enzymes, making it possible to attach useful chemical groups to proteins or join protein pieces together in ways that are not currently possible. These advances can open new opportunities for studying how proteins function, tracking them in complex biological settings, and preparing improved protein-based materials and medicines. The research focuses on small, water-compatible nanoparticles that recognize short protein sequences with high selectivity and direct chemical reactions to a chosen amino acid site. If successful, the work will provide broadly useful tools for biochemistry, cell biology, biotechnology, and protein therapeutics, while making advanced protein modification more accessible to researchers who are not specialists in synthetic chemistry. The multidisciplinary nature of the project trains student researchers in biomaterials science, biology, synthetic chemistry, and polymer chemistry, helping prepare them for a wide range of scientific careers. The project also supports education and public engagement through outreach activities and training that introduces students to innovation and intellectual property alongside research. These efforts strengthen the scientific workforce, expand public understanding of science, and serve the national interest by promoting scientific progress and enabling technologies relevant to health and prosperity. TECHNICAL SUMMARY This project develops molecularly imprinted nanoparticles as synthetic mimics of post-translational modification enzymes for site-selective transformation of proteins in water under physiological conditions. These protein-sized receptors bind peptide sequences with high affinity and discriminate among closely related amino acid side chains, providing a platform for reaction control at a single site on complex protein substrates. The central research objective is to convert these recognition elements into catalytic systems for selective modification of off-the-shelf proteins. Two specific aims are pursued: first, catalytic site-specific labeling of proteins with one or multiple tags, including fluorescent, affinity, and polymeric groups; second, sequence-selective ligation of peptides and proteins under mild aqueous conditions. The work defines the molecular recognition features required for selective binding, incorporates reactive functionality into the imprinted nanoparticles, and evaluates how binding-guided catalysis enables precise protein labeling and ligation that current peptide and protein chemistry cannot achieve. The resulting methodology is expected to establish a general approach to synthetic protein modification with relevance to chemical biology, biomaterials, biotechnology, and protein therapeutics. Broader impacts are integrated through graduate and student training, outreach through Iowa State University, and instruction in patent literacy and innovation, which prepares trainees for both academic and industrial careers while broadening access to biomimetic chemistry concepts. 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. NSF Award ID: 2615570 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Yan Zhao | Institution: Iowa State University, AMES, IA | Award Amount: $450,000 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2615570 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2615570.html