This Project Grant award of $306,872.00 from the National Institute of General Medical Sciences (NIGMS), under the Biomedical Research and Research Training Program (CFDA 93.859), aims to develop a new 3D shape matching methodology that accounts for water molecules when comparing ligands during drug discovery. The key products and services to be delivered include: Adapting an existing algorithm (WATGEN) to predict water positions in unbound proteins and protein-ligand complexes, and calculate ligand-driven water displacement. Identifying water molecules relevant for shape matching using a combination of machine learning and empirical algorithms, and determining their "replaceability" and "displaceability" for hybrid ligand creation. Validating the new solvation-informed 3D shape matching methodology by comparing it to current waterless methods in two drug discovery contexts: evolving a first-generation sulfonylurea drug and ligand-based virtual screening. The goal is to integrate these solvation-accounting features into the existing ADMET Predictor software platform, which is freely available to academic researchers, to improve the accuracy of drug discovery and optimization processes.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $0 | 9/24/24 | ||
| Not listed | $306.9k | 9/6/24 |