Fragment-based drug design (FBDD)

A. P. Kryshchyshyn

Abstract


Fragment-based drug design (FBDD) is one of the modern techniques used for developing new drugs, and an alternative to the widely used high throughput screening. The main methodological approaches of FBDD, as well as the methods of optimization for the identified “fragments“ when transferring them to the drug-like molecules have been described. The basic principles of the biophysical methods for analysis of the fragment – bio-target complexes and their application have been shown. Advantages and disadvantages of such methods as fluorescence-based thermal shift, NMR-spectroscopy, mass spectrometry, surface plasmon resonance are discussed. The most informative and efficient tool for the complex screening is X-ray crystallography. The main approaches to development of the pharmacologically active molecules based on the identified fragments, namely the methods of “fragment merging”, “fragment linking” and “fragment growing”, are given. The prospects and importance of the given method has been confirmed by the specific examples of drug candidates and the antitumor drug Vemurafenib approved and developed using FBDD.

Keywords


fragment-based drug design FBDD; molecular fragment; ligand efficiency

References


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GOST Style Citations


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2.   Hajduk, P. J., Greer, J. (2007). A decade of fragment–based drug design: strategic advances and lessons learned. Nature Reviews Drug Discovery, 6 (3), 211–219. doi: 10.1038/nrd2220.

3.   Erlanson, D. A. (2011). Introduction to fragment–based drug discovery. Fragment–based drug discovery and X–ray crystallography. Springer Berlin Heidelberg, 1–32. doi: 10.1007/128_2011_180.

4.   Fink, T., Reymond, J.–L. (2007). Virtual Exploration of the Chemical Universe up to 11 Atoms of C, N, O, F:  Assembly of 26.4 Million Structures (110.9 Million Stereoisomers) and Analysis for New Ring Systems, Stereochemistry, Physicochemical Properties, Compound Classes, and Drug Discovery. Journal of Chemical Information and Modeling, 47 (2), 342–353. doi: 10.1021/ci600423u.

5.   Scott, D. E., Coyne, A. G., Hudson, S. A., Abell, C. (2012). Fragment–based approaches in drug discovery and chemical biology. Biochemistry, 51 (25), 4990–5003. doi: 10.1021/bi3005126.

6.   Jencks, W. P. (1981). On the attribution and additivity of binding energies. Proceedings of the National Academy of Sciences, 78 (7), 4046–4050. doi: 10.1073/pnas.78.7.4046.

7.   Shuker, S. B., Hajduk, P. J., Meadows, R. P., Fesik, S. W. (1996). Discovering High–Affinity Ligands for Proteins: SAR by NMR. Science, 274 (5292), 1531–1534. doi: 10.1126/science.274.5292.1531.

8.   Chung, S., Parker, J. B., Bianchet, M., Amzel, L. M., Stivers, J. T. (2009). Impact of linker strain and flexibility in the design of a fragment–based inhibitor. Nature Chemical Biology, 5 (6), 407–413. doi: 10.1038/nchembio.163.

9.   Huth, J. R., Park, C., Petros, A. M., Kunzer, A. R., Wendt, M. D., Wang, X., Hajduk, P. J. (2007). Discovery and Design of Novel HSP90 Inhibitors Using Multiple Fragment–based Design Strategies. Chemical Biology & Drug Design, 70 (1), 1–12. doi: 10.1111/j.1747–0285.2007.00535.x.

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11. Rishton, G. M. (2003). Nonleadlikeness and leadlikeness in biochemical screening. Drug Discovery Today, 8 (2), 86–96. doi: 10.1016/s1359644602025722.

12. Baell, J. B., Holloway, G. A. (2010). New Substructure Filters for Removal of Pan Assay Interference Compounds (PAINS) from Screening Libraries and for Their Exclusion in Bioassays. Journal of Medicinal Chemistry, 53 (7), 2719–2740. doi: 10.1021/jm901137j.

13. Guertin, K. R. et al. (2003). Identification of a Novel Class of Orally Active Pyrimido[5,4–3][1,2,4]triazine–5,7–diamine–Based Hypoglycemic Agents with Protein Tyrosine Phosphatase Inhibitory Activity. ChemInform, 34 (46). doi: 10.1002/chin.200346171.

14. Tjernberg, A., Hallén, D., Schultz, J., James, S., Benkestock, K., Byström, S., Weigelt, J. (2004). Mechanism of action of pyridazine analogues on protein tyrosine phosphatase 1B (PTP1B). Bioorganic & Medicinal Chemistry Letters, 14 (4), 891–895. doi: 10.1016/j.bmcl.2003.12.014.

15. Yi, F., Regan, L. (2008). A Novel Class of Small Molecule Inhibitors of Hsp90. ACS Chemical Biology, 3 (10), 645–654. doi: 10.1021/cb800162x.

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17. Soares, K. M., Blackmon, N., Shun, T. Y., Shinde, S. N., Takyi, H. K., Wipf, P., Johnston, P. A. (2010). Profiling the NIH Small Molecule Repository for Compounds That Generate H 2 O 2 by Redox Cycling in Reducing Environments. ASSAY and Drug Development Technologies, 8 (2), 152–174. doi: 10.1089/adt.2009.0247.

18. McGovern, S. L., Caselli, E., Grigorieff, N., Shoichet, B. K. (2002). A Common Mechanism Underlying Promiscuous Inhibitors from Virtual and High–Throughput Screening. Journal of Medicinal Chemistry, 45 (8), 1712–1722. doi: 10.1021/jm010533y.

19. Seidler, J., McGovern, S. L., Doman, T. N., Shoichet, B. K. (2003). Identification and Prediction of Promiscuous Aggregating Inhibitors among Known Drugs. Journal of Medicinal Chemistry, 46 (21), 4477–4486. doi: 10.1021/jm030191r.

20. Babaoglu, K., Simeonov, A., Irwin, J. J., Nelson, M. E., Feng, B., Thomas, C. J., Shoichet, B. K. (2008). Comprehensive Mechanistic Analysis of Hits from High–Throughput and Docking Screens against β–Lactamase. Journal of Medicinal Chemistry, 51 (8), 2502–2511. doi: 10.1021/jm701500e.

21. Ferreira, R. S., Bryant, C., Ang, K. K. H., McKerrow, J. H., Shoichet, B. K., Renslo, A. R. (2009). Divergent Modes of Enzyme Inhibition in a Homologous Structure−Activity Series. Journal of Medicinal Chemistry, 52 (16), 5005–5008. doi: 10.1021/jm9009229.

22. Feng, B. Y., Shoichet, B. K. (2006). A detergent–based assay for the detection of promiscuous inhibitors. Nature Protocols, 1 (2), 550–553. doi: 10.1038/nprot.2006.77.

23. Shoichet, B. K. (2006). Screening in a spirit haunted world. Drug Discovery Today, 11 (13–14), 607–615. doi: 10.1016/j.drudis.2006.05.014.

24. Hopkins, A. L., Groom, C. R., Alex, A. (2004). Ligand efficiency: a useful metric for lead selection. Drug Discovery Today, 9 (10), 430–431. doi: 10.1016/s1359–6446(04)03069–7.

25. Kuntz, I.D., Chen, K., Sharp, K. A., Kollman, P. A. (1999). The maximal affinity of ligands. Proceedings of the National Academy of Sciences, 96 (18), 9997–10002. doi: 10.1073/pnas.96.18.9997.

26. Congreve, M., Carr, R., Murray, C., Jhoti, H. (2003). A “Rule of Three” for fragment–based lead discovery? Drug Discovery Today, 8 (19), 876–877. doi: 10.1016/s1359–6446(03)02831–9.

27. Lipinski, C. A., Lombardo, F., Dominy, B. W., Feeney, P. J. (2012). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 64, 4–17. doi: 10.1016/j.addr.2012.09.01.

28. Hann, M. M., Leach, A. R., Harper, G. (2001). Molecular Complexity and Its Impact on the Probability of Finding Leads for Drug Discovery. Journal of Chemical Information and Computer Sciences, 41 (3), 856–864. doi: 10.1021/ci000403i.

29. Oprea, T. I., Davis, A. M., Teague, S. J., Leeson, P. D. (2001). Is There a Difference between Leads and Drugs? A Historical Perspective. Journal of Chemical Information and Computer Sciences, 41 (5), 1308–1315. doi: 10.1021/ci010366a.

30. Teague, S. J., Davis, A. M., Leason, P. D., Oprea, T. (1999).The design of leadlike combinatorial libraries. Angewandte Chemie International Edition, 38 (24), 3743–3748. doi: 10.1002/(sici)1521–3773(19991216)38:24<3743::aid–anie3743>3.3.co;2–l. 

31. Carr, R. A. E., Congreve, M., Murray, C. W., Rees, D. C. (2005). Fragment–based lead discovery: leads by design. Drug Discovery Today, 10 (14), 987–992. doi: 10.1016/s1359–6446(05)03511–7.

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DOI: https://doi.org/10.24959/ophcj.17.913

Abbreviated key title: Ž. org. farm. hìm.

ISSN 2518-1548 (Online), ISSN 2308-8303 (Print)