Early-stage drug discovery involves the discovery of “hits” that affect the function of a drug target in disease states, subsequently undergoing a hit-to-lead development process prior to human testing and approval. Traditional high throughput screening (HTS) methods involve testing millions of molecules for binding to protein drug targets using biophysical, biochemical, and in silico assays. These methods rely heavily on robotic automation.
As an alternative to HTS, fragment screening has been increasingly employed for hit discovery in the last few decades. While HTS uses small molecules with drug-like molecular weights (~500 Daltons), fragment screening starts with smaller ligands (150-300 Daltons) that are developed into larger leads. Seven fragment-derived drugs are currently approved for human use.
Fragment libraries are smaller and simpler, making them more accessible. The hit rate in a fragment-based screening approach is typically higher, providing more starting points for lead development with smaller libraries. Fragment binding may be especially valuable to target protein-protein interactions, making them useful for previously intractable drug targets. The discovered hits have a weak binding affinity (uM-mM) and require sensitive techniques for detection. However, detectable fragment hits frequently display good pharmacological properties, providing ideal starting points for lead development.
Fragment-to-lead development involves merging, linking, or growing fragment hits, often aided by 3D structure information of fragment-protein interactions obtained through X-ray crystallography and NMR. This Methods Collection aims to compile the techniques used in a fragment-based drug discovery approach, from library design, screening, and validation to fragment-to-lead development.
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Cited by 78
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2021
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Alice Douangamath*1,2, Ailsa Powell*1,2, Daren Fearon*1,2, Patrick M. Collins1,2, Romain Talon1,2,3, Tobias Krojer3,4, Rachael Skyner1,2, Jose Brandao-Neto1,2, Louise Dunnett1,2, Alexandre Dias1,2, Anthony Aimon1,2,3, Nicholas M. Pearce1,3, Conor Wild3,5, Tyler Gorrie-Stone1, Frank von Delft1,2,3,4,6
1Diamond Light Source Ltd, Harwell Science and Innovation Campus, 2Research Complex at Harwell, Harwell Science and Innovation Campus, 3Structural Genomics Consortium, University of Oxford, 4Centre for Medicines Discovery, University of Oxford, 5Oxford Protein Informatics Group, Department of Statistics, Oxford University, 6Department of Biochemistry, University of Johannesburg
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Cited by 19
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2021
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Jan Wollenhaupt1, Tatjana Barthel1,2, Gustavo M. A. Lima3, Alexander Metz4, Dirk Wallacher5, Elmir Jagudin3, Franziska U. Huschmann1,4, Thomas Hauß1, Christian G. Feiler1, Martin Gerlach1, Michael Hellmig1, Ronald Förster1, Michael Steffien1, Andreas Heine4, Gerhard Klebe4, Uwe Mueller1, Manfred S. Weiss1
1Macromolecular Crystallography, Helmholtz-Zentrum Berlin, 2Structural Biochemistry Group, Institute for Chemistry and Biochemistry, Freie Universität Berlin, 3BioMAX, MAX IV Laboratory, 4Drug Design Group, Institute of Pharmaceutical Chemistry, Philipps-Universität Marburg, 5Department Sample Environment, Helmholtz-Zentrum Berlin
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Cited by 11
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2021
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Quantitative Irreversible Tethering for Covalent Protein Modifiers
Charles Brown1,
David Mann*2,
Alan Armstrong*1
1Department of Chemistry, Imperial College London,
2Department of Life Sciences, Imperial College London