Federal Grant Award Summary

The University of New Mexico received a $404,464 Project Grant from the National Institute of General Medical Sciences (NIGMS) under the Biomedical Research and Research Training program (CFDA 93.859), awarded August 1, 2026, with completion targeted for May 31, 2031. The research project focuses on improving multi-scale characterization of nucleic acids and DNA nanotechnology toward therapeutic design by developing integrated computational methods. The research team will pioneer a combination of quantum chemistry (QC), molecular dynamics (MD), and machine learning (ML) approaches to predict electron densities, energies, and forces of biologically relevant macromolecular systems, particularly solvated nucleic acid molecules and biomolecular ligand-receptor complexes.

The deliverables include development of a Euclidean neural network model trained to predict electron densities of nucleic acid systems using ab initio quantum chemistry calculations and molecular dynamics sampling, complemented by a secondary machine learning model to accurately predict atomic energies and forces. These predicted electronic-scale biophysical properties will enable binding energy studies of ligand-receptor complexes at the ab initio theoretical level, advancing beyond classical approximations typically used for binding domain calculations. The research addresses a critical bottleneck in translating generative artificial intelligence-derived biomolecular designs into therapeutic applications by providing accurate computational validation and characterization methodologies.