The Fragment Discovery Center (FDC) is a research consortium at the University of California-San Francisco (UCSF). The mission of the FDC is to bring innovative small-molecule discovery approaches to challenging targets, such as protein-protein interactions and allosteric regulation, with a strong focus on cancer. The functional areas in the FDC are shown in the following chart. Fragment-based lead discovery is a highly interdisciplinary process whereby computation, medicinal chemistry, and biophysics work closely to identify and optimize small compounds (<250 Da) through structure-guided design. The Structure/screening core of the FDC also collaborates with CBC centers to support hit validation and mechanism-of-action studies.
The administrative hub of the FDC is located in the Small Molecule Discovery Center (SMDC; http://smdc.ucsf.edu), a core facility at UCSF. Professor Jim Wells directs both the FDC and the larger core facility; Dr. Michelle Arkin is the associate director of the FDC and runs the screening and biochemistry groups in the SMDC. All FDC projects are managed by Dr. Preeti Chugha.
The FDC specializes in three fragment-screening technologies - high-throughput surface plasmon resonance (HT-SPR), NMR, and disulfide-trapping ( “Tethering ”). Both HT-SPR and NMR use the SMDC’s 3500-compound fragment library. Using the Biacore 4000 for HT-SPR, we are able to screen ~2000 fragments/day/target, thus completing a primary fragment screen and dose-response follow-up screen in one week. NMR methods include ligand-detected assays and protein-chemical shift measurements. Disulfide-trapping uses mass spectrometry and a proprietary library of disulfide-containing fragments to select molecules that bind to cysteine residues engineered into the target protein. The FDC benefits from the infrastructure of the SMDC, which includes high-performance servers and database management, a 170,000-compound library and fully HTS automation. Structural biologists in the FDC consortium include NMR spectroscopists Tom James and Mark Kelly, and crystallographers Robert Fletterick and Robert Stroud. The following table outlines the assays available from the Structure/Screening Core for fragment discovery and HTS hit characterization.
| Assay | Affinity Range | Advantages |
|---|---|---|
| SPR | 1 nM-1 mM | association rate, dissociation rate and stoichiometry can be determined |
| NMR | 1 µM-10 mM | protein-detected NMR can provide binding site information and utilize SAR by NMR |
| x-ray crystallography | 1 nM-10 mM | binding site information can be used for structure-based fragment optimization |
| Disulfide trapping | 1 µM-10 mM | Site-directed method for discovering small fragments; covalently stabilizes bound fragments for structure and function assays |
Computational chemistry plays a central role in fragment discovery and optimization. Matthew Jacobson, Brian Shoichet, and John Irwin use computational methods to select new fragments for each screening target, and also model binding poses for fragments that have been identified by SPR, NMR, and tethering. The Shoichet lab developed DOCK to identify purchasable fragment binders in their ZINC database. The Jacobson lab mainly uses PLOP, which was developed by Dr. Jacobson at Columbia University, for protein modeling using all-atom energy functions.
Developing fragments into viable leads requires chemical optimization through expansion or linking. Synthetic chemists Adam Renslo (SMDC, Pharmaceutical Chemistry) and Jack Taunton (HHMI, Pharmaceutical Chemistry) optimize fragments based on a combination of structural/modeling data and traditional medicinal chemistry. The deliverables from the fragment-discovery process are compounds with the properties of well-validated hits, directed towards challenging drug targets.
For more information please contact:
Preeti Chugha, PhD, PMP
Project Manager
Small Molecule Discovery Center
Department of Pharmaceutical Chemistry
University of California-San Francisco
1700 4th Street
Byers Hall, Room 501
San Francisco, CA 94158
(415) 514-1036
preeti.chugha@ucsf.edu