AI-driven Molecular Docking

Establishing Infrastructure for AI-Driven Discovery of Small Molecules to Combat Antibiotic Resistance, Biofilms, and Aflatoxin Contamination

Summary

This research aims to investigates the fundamental interactions between small molecules and proteins to identify compounds capable of combating bacteria, biofilm maintenance, and fungal aflatoxin contamination. An interjurisdictional (SDSU, SDMT, UNLV), interdisciplinary (biologists, mathematicians, statisticians, and computer scientists) team will collaborate to leverage cutting-edge generative artificial intelligence (AI) and machine learning (ML) technologies, accelerating the discovery of bioactive molecules.

Funding Agency:
NSF | EPSCoR RII: FEC

Team:
(Only AI/ML Teams are listed) Eun Heui Kim (Co-PI) | Dept. of Mathematics and Statistics, SDSU
Xijin Ge (Co-PI) | Dept. of Mathematics and Statistics, SDSU
Kwanghee Won (Co-I) | McComish Dept. of EECS, SDSU
Chulwoo Pack (Co-I) | McComish Dept. of EECS, SDSU

Duration:
2025-2029

Total Funding:
$2,190,786

External Resources: