Deep Learning-Guided Discovery and Structural Validation of Marine Toxin Inhibitors
Abstract
Understanding how antitoxins inhibit marine toxin activity and how to exploit this information to discover novel antitoxin medical countermeasures remains a significant knowledge gap. Here, we propose an integrated research program to develop a machine learning platform for in silico antitoxin discovery from vast chemical libraries of >1.5 B compounds. The machine learning platform will be guided by the empirical results of high-throughput chemical screens and structural models of toxin-antitoxin interactions based on cyro-electron microscopy (cryo-EM) and computational docking simulations.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 19, 2022
- Source ID
- HDTRA12210010
Entities
People
- James J. Collins
Organizations
- Defense Threat Reduction Agency
- Massachusetts Institute of Technology