College of Pharmacy
Li Lab
Led by Chenglong Li · Medicinal Chemistry
What we study
The Li Lab studies molecular recognition and drug design, using methods like molecular simulation, AI, and crystallography to develop drugs targeting diseases like cystic fibrosis and cancer.
What working here is like
- Wet lab
- Computational
- Coding helps
- Projects
- 5
- Paper
- 1
Current projects
Multiple Ligand Simultaneous Docking (MLSD) strategy
Develops a computer method that docks several small drug fragments onto a protein at the same time, so researchers can build new drug candidates from fragments more efficiently.
AI-based deep learning models for molecular design
Builds deep learning models that propose and evaluate new molecule designs, aiming to speed up the search for drug candidates alongside the lab's simulation and crystallography work.
Show 3 more projectsShow fewer
Drugs targeting IL-6/STAT3 pathway
Designing drugs for autoimmune, inflammatory, and oncogenic diseases.
PRMT5 inhibitors
Developing drugs targeting epigenetic histone arginine methylation enzymes.
Chemical chaperones for cystic fibrosis
Designs small-molecule drugs that help a misfolded cystic fibrosis protein (deltaF508 NBD1) fold correctly, using molecular simulation and structure-based methods to find compounds that stabilize it.
Summaries are written by AI in plain language from public symposium abstracts and may be imperfect.
Recent papers, explained
- SMARTFlexDB: a paired apo–holo RNA structure database and analysis platform for RNA conformational flexibility and small-molecule recognition
2026 · Nucleic Acids Research
Builds a database of RNA structures to study how small molecules change RNA shape.
Plain-language summaries are AI-written and reviewed by us; check the paper for details.
How to reach out
Chenglong Li hasn't set up this page yet. Their UF Scholars profile lists their publications.