Lead Discovery

The structure-based drug design core performs lead discovery to aid in the development of new pharmaceutical compounds. Lead discovery typically begins with a biomedically relevant target protein. Ideally, X-ray crystallography or NMR data is available for the target protein, but this is not an absolute requirement where homology modeling is possible. The target receptor is discussed with the investigators to identify active sites or particular pockets known to be involved in protein function. The target protein is computationally analyzed and a three-dimensional complement of each target site is described and refined.

An example of a compound identified by molecular docking capable of inhibiting the activity of Focal Adhesion Kinase in vitro and inhibiting tumor growth in vivo.

Docking Process

Computational docking is performed with the UCSF DOCK package and other software developed here at the UFSCC Structure-Based Drug Design Core exclusively for drug discovery research. The Structure-Based Drug Design Core is affiliated with the UF High Performance Computing Center, and all lead discovery jobs are executed on the University supercomputing cluster. The computational power of the cluster allows us to screen chemical libraries ranging in size from hundreds of thousands to millions of small molecules rapidly, accurately and economically.


Results are presented to investigators as a list of the top several hundred small molecules estimated to have the highest binding affinity for the target site. Each targeted compound can be viewed in its predicted orientation in the target site, and all necessary information for compound ordering is provided. We routinely obtain the top 40 scoring compounds from the National Cancer Institute’s Developmental Therapeutics Program for functional in vitro and in vivo testing.

To make a lead discovery request please visit our Docking Request page.


Lead Optimization


Above: A series of images showing RACHEL optimizing an initial promising lead compound to improve the affinity for the active site. Many potential optimized leads are generated for further testing.

Lead Optimization is performed on compounds that have been discovered through computational and/or assay-based Lead Discovery. We utilize the two main tools for lead optimization that are most frequently used in large pharmaceutical companies:

RACHEL and CHARLIE are both modules of the SYBYL program package. These methods have a track record for success in the translation of lead compounds into FDA approved therapeutic agents.

RACHEL – (Real-time Automated Combinatorial Heuristic Enhancement of Lead compounds)

Starting from a ligand/receptor structure, RACHEL performs automated combinatorial optimization of lead compounds by systematically derivatizing user-defined sites on the ligand. These compounds are conformationally searched within the active site, evaluated, and only those that bind tightly with the receptor are retained. This new population of compounds is then processed to form the next generation of derivatives. Over time, a lead compound is iteratively refined into a set of high affinity structures.


CHARLIE allows the user to generate scaffolds to link separate, docked, high-affinity structures into complete compounds within the confines of the active site. CHARLIE is proficient in building bridges between structures and is useful when substructures that tightly bind different regions of the active site are present.

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