Federal Grant Award Summary

The National Institute of General Medical Sciences (NIGMS) awarded Howard University a Project Grant of $566,094 under the Biomedical Research and Research Training program (CFDA 93.859) for the period May 1, 2026 through April 30, 2029. The award supports development of a novel computational framework using Graph Attention Networks (GATs) to predict gene essentiality and identify functional protein substructures. The research will create advanced GAT models incorporating interpretable biochemical features—such as amino acid charge and hydrophobicity—and employ variational graph partitioning approaches to identify cohesive protein modules analogous to catalytic sites or interaction interfaces. The models will move beyond binary essential/non-essential classifications to capture continuous fitness effects across curated datasets from yeast, human, and model organisms.

The anticipated deliverables include more accurate and interpretable computational models for predicting gene essentiality, novel biological insights into disease mechanisms, and identification of potential therapeutic targets. The project will validate findings against evolutionary, disease, and functional data while engaging undergraduate students in interdisciplinary research. This work addresses a critical gap in current experimental and computational methods by providing context-specific gene essentiality predictions with biological clarity, thereby advancing fundamental understanding of cellular processes and supporting the development of targeted therapies for conditions such as cancer and infections.