Introduction into Fragment Based Drug Discovery

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Introduction into Fragment Based Drug Discovery

Published on ‎11-10-2022 10:18 AM by

Fragment-based drug discovery (FBDD) is a method used for finding hit compounds as one strategy of hit identification in the drug discovery process. Fragments are small molecules with a low molecular weight, smaller than lead molecules or druglike molecules. The FBDD technology is based on identifying small chemical fragments, which bind to the biological target and which are then optimized into leadlike and druglike molecules. In contrast to high throughput screening (HTS) where libraries of millions of compounds with molecular weights of around 500 Da are tested and nanomolar binding affinities are found, fragments come from much smaller libraries and show weaker binding affinities. They still make good starting points for drug discovery. 
In contrast to hit identification by HTS the conditions for FBDD are different. A smaller fragment library, fragment hits with weaker affinities, the need for guidance by structure information and the use of compound metrics in the optimization are central elements of FBDD. The webinar will give insight into this technology and will show how FBDD can be successfully applied for the identification of novel and potent lead compounds
Key Learning Objectives:
  • Basics of how the FBDD works 
  • How FBDD can be successfully applied
  • Well established assays for FBDD 
Who Should Attend:
  • Senior project managers of drug discovery/R&D 
  • Senior directors of drug discovery/R&D 
  • Senior scientists of drug discovery/R&D, including senior medicinal chemist, senior biology/protein science scientist, etc.
  • Drug discovery researchers (Professors/PIs from academy) 

Brought to you by:




Moran Jerabek-Willemsen, PhD
Head of Biophysics & Screening,
WuXi AppTec HitS

%7B1aed7e6e-6cc5-4465-90c8-4badfd591d60%7D_Andreas_100x100Andreas Schoop, PhD
Head of Medicinal Chemistry,
WuXi AppTec HitS


Jeff Huber
Contributing Editor,
C&EN Media Group

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Tue, Nov 29, 2022 01:00 PM EST
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