Federal Grant Award Summary

The University of Virginia received a $815,002 Project Grant award from the National Science Foundation's Division of Biological Infrastructure under the Biological Sciences program (CFDA 47.074), effective August 15, 2026 through July 31, 2029. The award supports development of an integrated graph machine learning platform designed to accelerate peptide discovery and design by leveraging both two-dimensional topological and three-dimensional geometric structural data. The platform will employ novel graph neural network architectures tailored to peptides, including amino acid-aware message passing that respects the hierarchical organization of atoms within amino acids, enabling researchers to predict peptide properties with greater accuracy and speed than current methods.

The project delivers open-source software tools intended to lower barriers for interdisciplinary research communities pursuing peptide-based innovations in antimicrobial compounds, advanced biomaterials, medicines, and biomanufacturing. Deliverables include integration of research findings into undergraduate and graduate curricula and K-12 outreach activities designed to build the scientific workforce pipeline. By reducing the time and cost associated with peptide design and discovery processes, this work directly supports national priorities in artificial intelligence and biotechnology while advancing the foundational science that underpins next-generation biomedical and materials applications.