Title:
Drug Discovery Accelerated by Computational Methods
Drug Discovery Accelerated by Computational Methods
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Author(s)
Jorgensen, William L.
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Abstract
Drug discovery is being pursued through computer-aided design, synthesis, biological assaying, and crystallography. Lead identification features de novo design with the ligand growing program BOMB or docking of commercial compound libraries. The cheminformatics program QikProp is applied to filter candidate molecules to ensure that they have drug-like properties. The focus of this lecture will be optimization of the resultant leads to yield potent inhibitors. Specifically, Monte Carlo/free-energy perturbation simulations are executed to identify the most promising choices for substituents on rings, heterocycles, and linking groups. The designed compounds are then synthesized and assayed. Successful application has been achieved for HIV reverse transcriptase, FGFR1 kinase, and human and Plasmodium falciparum macrophage migration inhibitory factor (MIF); micromolar leads have been rapidly advanced to low nanomolar or picomolar inhibitors.
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Date Issued
2013-04-30
Extent
68:48 minutes
Resource Type
Moving Image
Resource Subtype
Lecture