Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Twenty years on: the impact of fragments on drug discovery

Key Points

  • Fragment-based drug discovery (FBDD) is playing an increasingly important part in delivering candidates to the clinic.

  • Compared with screens of lead- or drug-sized molecules, fragments allow for a more thorough search of chemical space and can lead to superior molecules.

  • Fragments can provide fundamental insights into molecular recognition between proteins and ligands.

  • Rigorous use of multiple biophysical techniques is essential to identify and validate fragments.

  • Early and creative medicinal chemistry is needed to transform a low-affinity fragment into a lead molecule.

  • FBDD can be integrated with other lead discovery methods to tackle difficult problems.

Abstract

After 20 years of sometimes quiet growth, fragment-based drug discovery (FBDD) has become mainstream. More than 30 drug candidates derived from fragments have entered the clinic, with two approved and several more in advanced trials. FBDD has been widely applied in both academia and industry, as evidenced by the large number of papers from universities, non-profit research institutions, biotechnology companies and pharmaceutical companies. Moreover, FBDD draws on a diverse range of disciplines, from biochemistry and biophysics to computational and medicinal chemistry. As the promise of FBDD strategies becomes increasingly realized, now is an opportune time to draw lessons and point the way to the future. This Review briefly discusses how to design fragment libraries, how to select screening techniques and how to make the most of information gleaned from them. It also shows how concepts from FBDD have permeated and enhanced drug discovery efforts.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Discovery of vemurafenib.
Figure 2: Discovery of AZD5363.
Figure 3: Discovery of new ligand chemotypes for the β1 adrenergic receptor.
Figure 4: Discovery of the B cell lymphoma 2-selective candidate ABT-199.
Figure 5: Fragments binding to RAS.
Figure 6: Discovery of a novel binding site in Hepatitis C virus NS3.

Similar content being viewed by others

References

  1. Macarron, R. et al. Impact of high-throughput screening in biomedical research. Nat. Rev. Drug Discov. 10, 188–195 (2011).

    Article  CAS  PubMed  Google Scholar 

  2. Barker, A., Kettle, J. G., Nowak, T. & Pease, J. E. Expanding medicinal chemistry space. Drug Discov. Today 18, 298–304 (2013).

    Article  CAS  PubMed  Google Scholar 

  3. McGovern, S. L., Caselli, E., Grigorieff, N. & Shoichet, B. K. A common mechanism underlying promiscuous inhibitors from virtual and high-throughput screening. J. Med. Chem. 45, 1712–1722 (2002).

    Article  CAS  PubMed  Google Scholar 

  4. Irwin, J. J. et al. An aggregation advisor for ligand discovery. J. Med. Chem. 58, 7076–7087 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Bohacek, R. S., McMartin, C. & Guida, W. C. The art and practice of structure-based drug design: a molecular modeling perspective. Med. Res. Rev. 16, 3–50 (1996).

    Article  CAS  PubMed  Google Scholar 

  6. Ruddigkeit, L., van Deursen, R., Blum, L. C. & Reymond, J. L. Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17. J. Chem. Inform. Mod. 52, 2864–2875 (2012).

    Article  CAS  Google Scholar 

  7. Doak, B. C., Morton, C. J., Simpson, J. S. & Scanlon, M. J. Design and evaluation of the performance of an NMR screening fragment library. Aus. J. Chem. 66, 1465–1472 (2013).

    Article  CAS  Google Scholar 

  8. Ferenczy, G. G. & Keseru, G. M. How are fragments optimized? A retrospective analysis of 145 fragment optimizations. J. Med. Chem. 56, 2478–2486 (2013).

    Article  CAS  PubMed  Google Scholar 

  9. Hann, M. M., Leach, A. R. & Harper, G. Molecular complexity and its impact on the probability of finding leads for drug discovery. J. Chem. Inf. Comput. Sci. 41, 856–864 (2001).

    Article  CAS  PubMed  Google Scholar 

  10. Leach, A. R. & Hann, M. M. Molecular complexity and fragment-based drug discovery: ten years on. Curr. Opin. Chem. Biol. 15, 489–496 (2011). References 9 and 10 discuss the concept of molecular complexity, which is part of the theoretical framework underlying FBDD.

    Article  CAS  PubMed  Google Scholar 

  11. Hann, M. M. Molecular obesity, potency and other addictions in drug discovery. Med. Chem. Commun. 2, 349–255 (2011).

    Article  CAS  Google Scholar 

  12. Leeson, P. D. & St-Gallay, S. A. The influence of the 'organizational factor' on compound quality in drug discovery. Nat. Rev. Drug Discov. 10, 749–765 (2011).

    Article  CAS  PubMed  Google Scholar 

  13. Young, R. J. in Tactics in Contemporary Drug Design. Vol. 9 (ed. Meanwell, N. A.) 1–68 (Springer-Verlag Berlin Heidelberg, 2014).

    Book  Google Scholar 

  14. Jencks, W. P. On the attribution and additivity of binding energies. Proc. Nat. Acad. Sci. USA 78, 4046–4050 (1981). This paper is often considered to mark the theoretical origin of FBDD.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Shuker, S. B., Hajduk, P. J., Meadows, R. P. & Fesik, S. W. Discovering high-affinity ligands for proteins: SAR by NMR. Science 274, 1531–1534 (1996). This paper, arguably the first practical demonstration of FBDD, is widely viewed as having jump-started the field.

    Article  CAS  PubMed  Google Scholar 

  16. Hajduk, P. J. et al. Discovery of potent nonpeptide inhibitors of stromelysin using SAR by NMR. J. Am. Chem. Soc. 119, 5818–5827 (1997).

    Article  CAS  Google Scholar 

  17. Erlanson, D. A. & Jahnke, W. (eds) Fragment-based Drug Discovery: Lessons and Outlook. Vol. 67 (Wiley-VCH, 2016). This book is the most recent of 8 books devoted to FBDD, and its 19 chapters cover all aspects of the field.

    Book  Google Scholar 

  18. Harner, M. J., Frank, A. O. & Fesik, S. W. Fragment-based drug discovery using NMR spectroscopy. J. Biol. NMR 56, 65–75 (2013).

    Article  CAS  Google Scholar 

  19. Wang, F. & Fesik, S. W. in Fragment-based Drug Discovery: Lessons and Outlook. Vol. 67 (eds Erlanson, D. A. & Jahnke, W.) 371–390 (Wiley-VCH, 2016).

    Book  Google Scholar 

  20. Keseru, G. M. et al. Design principles for fragment libraries: maximizing the value of learnings from Pharma fragment based drug discovery (FBDD) programs for use in academia. J. Med. Chem. http://dx.doi.org/10.1021/acs.jmedchem.6b00197 (2016).

  21. Congreve, M., Carr, R., Murray, C. & Jhoti, H. A 'rule of three' for fragment-based lead discovery? Drug Discov. Today 8, 876–877 (2003).

    Article  PubMed  Google Scholar 

  22. Jhoti, H., Williams, G., Rees, D. C. & Murray, C. W. The 'rule of three' for fragment-based drug discovery: where are we now? Nat. Rev. Drug Discov. 12, 644–645 (2013). This paper and reference 21establish practical and theoretical guidelines for defining fragments.

    Article  CAS  PubMed  Google Scholar 

  23. Hall, R. J., Mortenson, P. N. & Murray, C. W. Efficient exploration of chemical space by fragment-based screening. Prog. Biophys. Mol. Biol. 116, 82–91 (2014).

    Article  CAS  PubMed  Google Scholar 

  24. Hajduk, P. J., Bures, M., Praestgaard, J. & Fesik, S. W. Privileged molecules for protein binding identified from NMR-based screening. J. Med. Chem. 43, 3443–3447 (2000).

    Article  CAS  PubMed  Google Scholar 

  25. Hajduk, P. J. et al. NMR-based screening of proteins containing 13C-labeled methyl groups. J. Am. Chem. Soc. 122, 7898–7904 (2000).

    Article  CAS  Google Scholar 

  26. Erlanson, D. A. in Fragment-based Drug Discovery. Vol. 47 (eds Howard, S. & Abell, C.) 19–30 (Royal Society of Chemistry, 2015).

    Google Scholar 

  27. Friberg, A. et al. Discovery of potent myeloid cell leukemia 1 (Mcl-1) inhibitors using fragment-based methods and structure-based design. J. Med. Chem. 56, 15–30 (2013).

    Article  CAS  PubMed  Google Scholar 

  28. Davis, B. J. & Erlanson, D. A. Learning from our mistakes: the 'unknown knowns' in fragment screening. Bioorg. Med. Chem. Lett. 23, 2844–2852 (2013).

    Article  CAS  PubMed  Google Scholar 

  29. Dalvit, C., Caronni, D., Mongelli, N., Veronesi, M. & Vulpetti, A. NMR-based quality control approach for the identification of false positives and false negatives in high throughput screening. Curr. Drug Discov. Technol. 3, 115–124 (2006).

    Article  CAS  PubMed  Google Scholar 

  30. Huth, J. R. et al. ALARM NMR: a rapid and robust experimental method to detect reactive false positives in biochemical screens. J. Am. Chem. Soc. 127, 217–224 (2005).

    Article  CAS  PubMed  Google Scholar 

  31. Baell, J. B. & Holloway, G. A. New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. J. Med. Chem. 53, 2719–2740 (2010).

    Article  CAS  PubMed  Google Scholar 

  32. Baell, J. B. Observations on screening-based research and some concerning trends in the literature. Future Med. Chem. 2, 1529–1546 (2010).

    Article  CAS  PubMed  Google Scholar 

  33. Baell, J. & Walters, M. A. Chemistry: chemical con artists foil drug discovery. Nature 513, 481–483 (2014).

    Article  CAS  PubMed  Google Scholar 

  34. Seidler, J., McGovern, S. L., Doman, T. N. & Shoichet, B. K. Identification and prediction of promiscuous aggregating inhibitors among known drugs. J. Med. Chem. 46, 4477–4486 (2003).

    Article  CAS  PubMed  Google Scholar 

  35. Feng, B. Y., Shelat, A., Doman, T. N., Guy, R. K. & Shoichet, B. K. High-throughput assays for promiscuous inhibitors. Nat. Chem. Biol. 1, 146–148 (2005).

    Article  CAS  PubMed  Google Scholar 

  36. Morley, A. D. et al. Fragment-based hit identification: thinking in 3D. Drug Discov. Today 18, 1221–1227 (2013).

    Article  PubMed  Google Scholar 

  37. Davies, D. R. et al. Discovery of leukotriene A4 hydrolase inhibitors using metabolomics biased fragment crystallography. J. Med. Chem. 52, 4694–4715 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Over, B. et al. Natural-product-derived fragments for fragment-based ligand discovery. Nat. Chem. 5, 21–28 (2013).

    Article  CAS  PubMed  Google Scholar 

  39. Vulpetti, A. & Dalvit, C. Design and generation of highly diverse fluorinated fragment libraries and their efficient screening with improved 19F NMR methodology. ChemMedChem. 8, 2057–2069 (2013).

    Article  CAS  PubMed  Google Scholar 

  40. Akritopoulou-Zanze, I. & Hajduk, P. J. Kinase-targeted libraries: the design and synthesis of novel, potent, and selective kinase inhibitors. Drug Discov. Today 14, 291–297 (2009).

    Article  CAS  PubMed  Google Scholar 

  41. Ostermann, N. et al. A novel class of oral direct renin inhibitors: highly potent 3,5-disubstituted piperidines bearing a tricyclic p3-p1 pharmacophore. J. Med. Chem. 56, 2196–2206 (2013).

    Article  CAS  PubMed  Google Scholar 

  42. Rüdisser, S., Vangrevelinghe, E. & Maibaum, J. in Fragment-based Drug Discovery: Lessons and Outlook. Vol. 67 (eds Erlanson, D. A. & Jahnke, W.) 447–486 (Wiley-VCH, 2016).

    Book  Google Scholar 

  43. Lepre, C. A. Practical aspects of NMR-based fragment screening. Methods Enzymol. 493, 219–239 (2011).

    Article  CAS  PubMed  Google Scholar 

  44. Stockman, B. J. & Dalvit, C. NMR screening techniques in drug discovery and drug design. Prog. Nucl. Mag. Res. Spectrosc. 41, 183–231 (2002).

    Article  Google Scholar 

  45. Cala, O. & Krimm, I. Ligand-orientation based fragment selection in STD NMR screening. J. Med. Chem. 58, 8739–8742 (2015).

    Article  CAS  PubMed  Google Scholar 

  46. Dalvit, C., Fagerness, P. E., Hadden, D. T., Sarver, R. W. & Stockman, B. J. Fluorine-NMR experiments for high-throughput screening: theoretical aspects, practical considerations, and range of applicability. J. Am. Chem. Soc. 125, 7696–7703 (2003).

    Article  CAS  PubMed  Google Scholar 

  47. Giannetti, A. M. From experimental design to validated hits a comprehensive walk-through of fragment lead identification using surface plasmon resonance. Methods Enzymol. 493, 169–218 (2011).

    Article  CAS  PubMed  Google Scholar 

  48. Danielson, U. H. Integrating surface plasmon resonance biosensor-based interaction kinetic analyses into the lead discovery and optimization process. Future Med. Chem. 1, 1399–1414 (2009).

    Article  CAS  PubMed  Google Scholar 

  49. Jhoti, H., Cleasby, A., Verdonk, M. & Williams, G. Fragment-based screening using X-ray crystallography and NMR spectroscopy. Curr. Opin. Chem. Biol. 11, 485–493 (2007).

    Article  CAS  PubMed  Google Scholar 

  50. Schiebel, J. et al. Six biophysical screening methods miss a large proportion of crystallographically discovered fragment hits: a case study. ACS Chem. Biol. 11, 1693–1701 (2016).

    Article  CAS  PubMed  Google Scholar 

  51. Davies, T. G. et al. Monoacidic inhibitors of the Kelch-like ECH-associated protein 1: nuclear factor erythroid 2–related factor 2 (KEAP1:NRF2) protein–protein interaction with high cell potency identified by fragment-based discovery. J. Med. Chem. 59, 3991–4006 (2016).

    Article  CAS  PubMed  Google Scholar 

  52. Hartshorn, M. J. et al. Fragment-based lead discovery using X-ray crystallography. J. Med. Chem. 48, 403–413 (2005).

    Article  CAS  PubMed  Google Scholar 

  53. Koh, C. Y. et al. A binding hotspot in Trypanosoma cruzi histidyl-tRNA synthetase revealed by fragment-based crystallographic cocktail screens. Acta Crystallogr. D Biol. Crystallogr. 71, 1684–1698 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Mashalidis, E. H., Sledz, P., Lang, S. & Abell, C. A three-stage biophysical screening cascade for fragment-based drug discovery. Nat. Prot. 8, 2309–2324 (2013).

    Article  CAS  Google Scholar 

  55. Scott, D. E., Spry, C. & Abell, C. in Fragment-based drug discovery: Lessons and outlook (eds Erlanson, D. A. & Jahnke, W.) 139–172 (Wiley-VCH, 2016).

    Book  Google Scholar 

  56. Jerabek-Willemsen, M., Wienken, C. J., Braun, D., Baaske, P. & Duhr, S. Molecular interaction studies using microscale thermophoresis. Assay Drug Dev. Technol. 9, 342–353 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Meiby, E. et al. Fragment screening by weak affinity chromatography: comparison with established techniques for screening against HSP90. Anal. Chem. 85, 6756–6766 (2013).

    Article  CAS  PubMed  Google Scholar 

  58. Wielens, J. et al. Parallel screening of low molecular weight fragment libraries: do differences in methodology affect hit identification? J. Biomol. Screen. 18, 147–159 (2013).

    Article  PubMed  Google Scholar 

  59. Schiebel, J. et al. One question, multiple answers: biochemical and biophysical screening methods retrieve deviating fragment hit lists. ChemMedChem. 10, 1511–1521 (2015).

    Article  CAS  PubMed  Google Scholar 

  60. Kutchukian, P. S. et al. Large scale meta-analysis of fragment-based screening campaigns: privileged fragments and complementary technologies. J. Biomol. Screen. 20, 588–596 (2015).

    Article  CAS  PubMed  Google Scholar 

  61. Ludlow, R. F., Verdonk, M. L., Saini, H. K., Tickle, I. J. & Jhoti, H. Detection of secondary binding sites in proteins using fragment screening. Proc. Nat. Acad. Sci. USA 112, 15910–15915 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Murray, C. W., Verdonk, M. L. & Rees, D. C. Experiences in fragment-based drug discovery. Trends Pharmacol. Sci. 33, 224–232 (2012).

    Article  CAS  PubMed  Google Scholar 

  63. Hopkins, A. L., Groom, C. R. & Alex, A. Ligand efficiency: a useful metric for lead selection. Drug Discov. Today 9, 430–431 (2004).

    Article  PubMed  Google Scholar 

  64. Hopkins, A. L., Keseru, G. M., Leeson, P. D., Rees, D. C. & Reynolds, C. H. The role of ligand efficiency metrics in drug discovery. Nat. Rev. Drug Discov. 13, 105–121 (2014). This review discusses the appropriate uses of various metrics such as ligand efficiency.

    Article  CAS  PubMed  Google Scholar 

  65. Bamborough, P., Brown, M. J., Christopher, J. A., Chung, C. W. & Mellor, G. W. Selectivity of kinase inhibitor fragments. J. Med. Chem. 54, 5131–5143 (2011).

    Article  CAS  PubMed  Google Scholar 

  66. Allen, C., Welford, A., Matthews, T., Caldwell, J. & Collins, I. Fragment growing to retain or alter the selectivity of anchored kinase hinge-binding fragments. Med. Chem. Commun. 5, 180–185 (2014).

    Article  CAS  Google Scholar 

  67. Woolford, A. J. Experiences with fragment libraries at Astex. Presented at the Fragment-based Lead Discovery (FBLD) Conference. (2014).

  68. Hubbard, R. E. in Fragment-based Drug Discovery: Lessons and Outlook. Vol. 67 (eds Erlanson, D. A. & Jahnke, W.) 3–36 (Wiley-VCH, 2016).

    Google Scholar 

  69. Devine, S. M. et al. Promiscuous 2-aminothiazoles (PrATs): a frequent hitting scaffold. J. Med. Chem. 58, 1205–1214 (2015).

    Article  CAS  PubMed  Google Scholar 

  70. Bauman, J. D., Harrison, J. J. & Arnold, E. Rapid experimental SAD phasing and hot-spot identification with halogenated fragments. IUCrJ 3, 51–60 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Bauman, J. D. et al. Detecting allosteric sites of HIV-1 reverse transcriptase by X-ray crystallographic fragment screening. J. Med. Chem. 56, 2738–2746 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Kozakov, D. et al. Ligand deconstruction: why some fragment binding positions are conserved and others are not. Proc. Nat. Acad. Sci. USA 112, E2585–E2594 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Saalau-Bethell, S. M. et al. Discovery of an allosteric mechanism for the regulation of HCV NS3 protein function. Nat. Chem. Biol. 8, 920–925 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Murray, J. et al. Tailoring small molecules for an allosteric site on procaspase-6. ChemMedChem. 9, 73–77 (2014).

    Article  CAS  PubMed  Google Scholar 

  75. Hajduk, P. J., Huth, J. R. & Fesik, S. W. Druggability indices for protein targets derived from NMR-based screening data. J. Med. Chem. 48, 2518–2525 (2005).

    Article  CAS  PubMed  Google Scholar 

  76. Chen, I. J. & Hubbard, R. E. Lessons for fragment library design: analysis of output from multiple screening campaigns. J. Comput. Aided Mol. Des. 23, 603–620 (2009).

    Article  PubMed  CAS  Google Scholar 

  77. Lau, W. F. et al. Design of a multi-purpose fragment screening library using molecular complexity and orthogonal diversity metrics. J. Comput. Aided Mol. Des. 25, 621–636 (2011).

    Article  CAS  PubMed  Google Scholar 

  78. Borsi, V., Calderone, V., Fragai, M., Luchinat, C. & Sarti, N. Entropic contribution to the linking coefficient in fragment based drug design: a case study. J. Med. Chem. 53, 4285–4289 (2010).

    Article  CAS  PubMed  Google Scholar 

  79. Ichihara, O., Barker, J., Law, R. J. & Whittaker, M. Compound design by fragment-linking. Mol. Informat. 30, 298–306 (2011).

    Article  CAS  Google Scholar 

  80. Ward, R. A. et al. Design and synthesis of novel lactate dehydrogenase a inhibitors by fragment-based lead generation. J. Med. Chem. 55, 3285–3306 (2012).

    Article  CAS  PubMed  Google Scholar 

  81. Korczynska, M. et al. Docking and linking of fragments to discover jumonji histone demethylase inhibitors. J. Med. Chem. 59, 1580–1598 (2016).

    Article  CAS  PubMed  Google Scholar 

  82. Czaplewski, L. G. et al. Antibacterial alkoxybenzamide inhibitors of the essential bacterial cell division protein FtsZ. Bioorg. Med. Chem. Lett. 19, 524–527 (2009).

    Article  CAS  PubMed  Google Scholar 

  83. Murray, C. W. & Rees, D. C. Opportunity knocks: organic chemistry for fragment-based drug discovery (FBDD). Angew. Chem. Int. 55, 488–492 (2016).

    Article  CAS  Google Scholar 

  84. Bollag, G. et al. Vemurafenib: the first drug approved for BRAF-mutant cancer. Nat. Rev. Drug Discov. 11, 873–886 (2012). This review discusses the discovery of the first approved FBDD-derived drug.

    Article  CAS  PubMed  Google Scholar 

  85. Addie, M. et al. Discovery of 4-amino-N-[(1S)-1-(4-chlorophenyl)-3-hydroxypropyl]-1-(7H-pyrrolo[2,3- d]pyrimidin -4-yl)piperidine-4-carboxamide (AZD5363), an orally bioavailable, potent inhibitor of Akt kinases. J. Med. Chem. 56, 2059–2073 (2013).

    Article  CAS  PubMed  Google Scholar 

  86. Caldwell, J. J. et al. Identification of 4-(4-aminopiperidin- 1-yl)-7H-pyrrolo[2,3-d]pyrimidines as selective inhibitors of protein kinase B through fragment elaboration. J. Med. Chem. 51, 2147–2157 (2008).

    Article  CAS  PubMed  Google Scholar 

  87. Albert, J. S. et al. An integrated approach to fragment-based lead generation: philosophy, strategy and case studies from AstraZeneca's drug discovery programmes. Curr. Top. Med. Chem. 7, 1600–1629 (2007).

    Article  CAS  PubMed  Google Scholar 

  88. de Graaf, C. et al. Small and colorful stones make beautiful mosaics: fragment-based chemogenomics. Drug Discov. Today 18, 323–330 (2013).

    Article  CAS  PubMed  Google Scholar 

  89. Rasmussen, S. G. et al. Crystal structure of the human β2 adrenergic G-protein-coupled receptor. Nature 450, 383–387 (2007).

    Article  CAS  PubMed  Google Scholar 

  90. Warne, T. et al. Structure of a β1-adrenergic G-protein-coupled receptor. Nature 454, 486–491 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Christopher, J. A. et al. Biophysical fragment screening of the β1-adrenergic receptor: identification of high affinity arylpiperazine leads using structure-based drug design. J. Med. Chem. 56, 3446–3455 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Wolkenberg, S. E. et al. High concentration electrophysiology-based fragment screen: discovery of novel acid-sensing ion channel 3 (ASIC3) inhibitors. Bioorg. Med. Chem. Lett. 21, 2646–2649 (2011).

    Article  CAS  PubMed  Google Scholar 

  93. Szollosi, E. et al. Cell-based and virtual fragment screening for adrenergic α2C receptor agonists. Bioorg. Med. Chem. 23, 3991–3999 (2015).

    Article  CAS  PubMed  Google Scholar 

  94. Oltersdorf, T. et al. An inhibitor of Bcl-2 family proteins induces regression of solid tumours. Nature 435, 677–681 (2005).

    Article  CAS  PubMed  Google Scholar 

  95. Souers, A. J. et al. ABT-199, a potent and selective BCL-2 inhibitor, achieves antitumor activity while sparing platelets. Nat. Med. 19, 202–208 (2013). This paper discusses the discovery of the second approved FBDD-derived drug.

    Article  CAS  PubMed  Google Scholar 

  96. Petros, A. M. et al. Fragment-based discovery of potent inhibitors of the anti-apoptotic MCL-1 protein. Bioorg. Med. Chem. Lett. 24, 1484–1488 (2014).

    Article  CAS  PubMed  Google Scholar 

  97. Burke, J. P. et al. Discovery of tricyclic indoles that potently inhibit Mcl-1 using fragment-based methods and structure-based design. J. Med. Chem. 58, 3794–3805 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Maurer, T. et al. Small-molecule ligands bind to a distinct pocket in Ras and inhibit SOS-mediated nucleotide exchange activity. Proc. Nat. Acad. Sci. USA 109, 5299–5304 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Sun, Q. et al. Discovery of small molecules that bind to K-Ras and inhibit Sos-mediated activation. Angew. Chem. Int. Ed. 51, 6140–6143 (2012).

    Article  CAS  Google Scholar 

  100. Ostrem, J. M., Peters, U., Sos, M. L., Wells, J. A. & Shokat, K. M. K-Ras(G12C) inhibitors allosterically control GTP affinity and effector interactions. Nature 503, 548–551 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Winter, J. J. et al. Small molecule binding sites on the Ras:SOS complex can be exploited for inhibition of Ras activation. J. Med. Chem. 58, 2265–2274 (2015).

    Article  CAS  PubMed  Google Scholar 

  102. Patricelli, M. P. et al. Selective inhibition of oncogenic KRAS output with small molecules targeting the inactive state. Cancer Discov. 6, 316–329 (2016).

    Article  CAS  PubMed  Google Scholar 

  103. Darby, J. F. et al. Discovery of selective small-molecule activators of a bacterial glycoside hydrolase. Angew. Chem. Int. Ed. 53, 13419–13423 (2014). This paper describes the rare discovery of enzyme activators using FBDD.

    Article  CAS  Google Scholar 

  104. Jahnke, W. et al. Binding or bending: distinction of allosteric Abl kinase agonists from antagonists by an NMR-based conformational assay. J. Am. Chem. Soc. 132, 7043–7048 (2010). This study uses NMR to differentiate allosteric agonists from antagonists.

    Article  CAS  PubMed  Google Scholar 

  105. Davies, T. G., Jhoti, H., Pathuri, P. & Williams, G. in Fragment-based Drug Discovery: Lessons and Outlook. Vol. 67 (eds Erlanson, D. A. & Jahnke, W.) 37–56 (Wiley-VCH, 2016).

    Book  Google Scholar 

  106. Folmer, R. H. Integrating biophysics with HTS-driven drug discovery projects. Drug Discov. Today 21, 491–498 (2016).

    Article  CAS  PubMed  Google Scholar 

  107. Whittaker, M. Picking up the pieces with FBDD or FADD: invest early for future success. Drug Discov. Today 14, 623–624 (2009).

    Article  PubMed  Google Scholar 

  108. Taylor, S. J. et al. Discovery of potent, selective chymase inhibitors via fragment linking strategies. J. Med. Chem. 56, 4465–4481 (2013).

    Article  CAS  PubMed  Google Scholar 

  109. Palmer, N., Peakman, T. M., Norton, D. & Rees, D. C. Design and synthesis of dihydroisoquinolones for fragment-based drug discovery (FBDD). Org. Biomol. Chem. 14, 1599–1610 (2016).

    Article  CAS  PubMed  Google Scholar 

  110. Murray, J. B., Roughley, S. D., Matassova, N. & Brough, P. A. Off-rate screening (ORS) by surface plasmon resonance. An efficient method to kinetically sample hit to lead chemical space from unpurified reaction products. J. Med. Chem. 57, 2845–2850 (2014).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The Authors thank U. Schopfer and the anonymous reviewers for helpful comments and suggestions on the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Daniel A. Erlanson.

Ethics declarations

Competing interests

D.A.E. is a co-founder, employee and shareholder of Carmot Therapeutics, Inc. R.H. is an employee and shareholder of Vernalis (R&D) Ltd. W.J. is an employee and shareholder of Novartis AG. H.J. is an employee of Astex Pharmaceuticals.

PowerPoint slides

Glossary

cLogP

The logarithm of partition coefficient between n-octanol and water. cLogP is a measure of lipophilicity.

Chemotype

A chemical structure motif or primary substructure that is common to a group of compounds.

Michael acceptors

An activated carbon–carbon double bond that is susceptible to nucleophilic attack.

Surface plasmon resonance

(SPR). An assay that detects binding between a surface- immobilized molecule (such as a protein) and a molecule in solution (such as a fragment).

Ligand-observed NMR

Detection of ligand binding by nuclear magnetic resonance (NMR) spectroscopy using methods such as saturation transfer difference (STD) NMR (to measure transfer of magnetization between protein and ligand), T1ρ relaxation (to exploit faster relaxation of bound ligands), waterLOGSY (to detect binding by transfer of magnetization between ligand and bound water) or 19F T2 (to detect faster relaxation of fluorinated bound ligands).

ALARM

A nuclear magnetic resonance (NMR)-based method to detect false positives, such as pan-assay interference compounds (PAINS).

Pan-assay interference compounds

(PAINS). Compounds containing substructures that give rise to apparent but artefactual activity in assays. The specific mechanisms vary and are not always known, but include forming covalent adducts with the protein or producing hydrogen peroxide.

Thermal shift assays

(TSAs). Assays, such as differential scanning fluorimetry, that measure the denaturation (or melting) temperature of a protein, which is often increased in the presence of a binding partner.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Erlanson, D., Fesik, S., Hubbard, R. et al. Twenty years on: the impact of fragments on drug discovery. Nat Rev Drug Discov 15, 605–619 (2016). https://doi.org/10.1038/nrd.2016.109

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrd.2016.109

This article is cited by

Search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research