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Rational Development of MAGL Inhibitors

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Rational Drug Design

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1824))

Abstract

Hit identification and hit-to-lead optimization are key steps of the early drug discovery program. Starting from the X-ray crystal structure of the human monoacylglycerol lipase (hMAGL), we herein describe the computational and experimental procedures that we applied for identifying and optimizing a new active inhibitor of this target enzyme. A receptor-based virtual screening method is reported in details, together with enzymatic assays and a first round of hit optimization.

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References

  1. Labar G, Bauvois C, Borel F et al (2010) Crystal structure of the human monoacylglycerol lipase, a key actor in endocannabinoid signaling. Chembiochem 11(2):218–227. https://doi.org/10.1002/cbic.200900621

    Article  CAS  PubMed  Google Scholar 

  2. Nomura DK, Long JZ, Niessen S et al (2010) Monoacylglycerol lipase regulates a fatty acid network that promotes cancer pathogenesis. Cell 140(1):49–61. https://doi.org/10.1016/j.cell.2009.11.027

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Mulvihill MM, Nomura DK (2013) Therapeutic potential of monoacylglycerol lipase inhibitors. Life Sci 92(8-9):492–497. https://doi.org/10.1016/j.lfs.2012.10.025

    Article  CAS  PubMed  Google Scholar 

  4. Scalvini L, Piomelli D, Mor M (2016) Monoglyceride lipase: structure and inhibitors. Chem Phys Lipids 197:13–24. https://doi.org/10.1016/j.chemphyslip.2015.07.011

    Article  CAS  PubMed  Google Scholar 

  5. Schlosburg JE, Blankman JL, Long JZ et al (2010) Chronic monoacylglycerol lipase blockade causes functional antagonism of the endocannabinoid system. Nat Neurosci 13(9):1113–1119. https://doi.org/10.1038/nn.2616

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. King AR, Dotsey EY, Lodola A et al (2009) Discovery of potent and reversible monoacylglycerol lipase inhibitors. Chem Biol 16(10):1045–1052. https://doi.org/10.1016/j.chembiol.2009.09.012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Hernandez-Torres G, Cipriano M et al (2014) A reversible and selective inhibitor of monoacylglycerol lipase ameliorates multiple sclerosis. Angew Chem Int Ed Engl 53:13765–13770. https://doi.org/10.1002/anie.201407807

    Article  CAS  PubMed  Google Scholar 

  8. Berman HM, Westbrook J, Feng Z et al (2000) The Protein Data Bank. Nucleic Acids Res 28:235–242. https://doi.org/10.1093/nar/28.1.235

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Schalk-Hihi C, Schubert C, Alexander R et al (2011) Crystal structure of a soluble form of human monoglyceride lipase in complex with an inhibitor at 1.35 A resolution. Protein Sci 20(4):670–683. https://doi.org/10.1002/pro.596

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. OMEGA, version 2.4.6 (2013) Santa Fe, NM: OpenEye Scientific Software. www.eyesopen.com

  11. Hawkins PC, Nicholls A (2012) Conformer generation with OMEGA: learning from the data set and the analysis of failures. J Chem Inf Model 52(11):2919–2936. https://doi.org/10.1021/ci300314k

    Article  CAS  PubMed  Google Scholar 

  12. ROCS, version 3.2.1 (2013) Santa Fe, NM: OpenEye Scientific Software. www.eyesopen.com

  13. Tuccinardi T, Poli G, Romboli V et al (2014) Extensive consensus docking evaluation for ligand pose prediction and virtual screening studies. J Chem Inf Model 54(10):2980–2986. https://doi.org/10.1021/ci500424n

    Article  CAS  PubMed  Google Scholar 

  14. Poli G, Martinelli A, Tuccinardi T (2016) Reliability analysis and optimization of the consensus docking approach for the development of virtual screening studies. J Enzyme Inhib Med Chem 31:167–173. https://doi.org/10.1080/14756366.2016.1193736

    Article  CAS  PubMed  Google Scholar 

  15. Poli G, Giuntini N, Martinelli A, Tuccinardi T (2015) Application of a FLAP-consensus docking mixed strategy for the identification of new fatty acid amide hydrolase inhibitors. J Chem Inf Model 55(3):667–675. https://doi.org/10.1021/ci5006806

    Article  CAS  PubMed  Google Scholar 

  16. Granchi C, Capecchi A, Del Frate G et al (2015) Development and validation of a docking-based virtual screening platform for the identification of new lactate dehydrogenase inhibitors. Molecules 20(5):8772–8790. https://doi.org/10.3390/molecules20058772

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. DOCK, version 6.0 (1998) Molecular design institute. University of California, San Francisco, CA

    Google Scholar 

  18. Verdonk ML, Mortenson PN, Hall RJ et al (2008) Protein-ligand docking against non-native protein conformers. J Chem Inf Model 48(11):2214–2225. https://doi.org/10.1021/ci8002254

    Article  CAS  PubMed  Google Scholar 

  19. FRED, version 2.2 (2010) Santa Fe, NM, USA: OpenEye Scientific Software. www.eyesopen.com

  20. Morris GM, Huey R, Lindstrom W et al (2009) AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 30(16):2785–2791. https://doi.org/10.1002/jcc.21256

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Case DA, Darden TA, III TEC, Simmerling CL, Wang J, Duke RE et al (2010) AMBER 11. University of California, San Francisco, CA

    Google Scholar 

  22. Tuccinardi T, Granchi C, Rizzolio F et al (2014) Identification and characterization of a new reversible MAGL inhibitor. Bioorg Med Chem 22(13):3285–3291. https://doi.org/10.1016/j.bmc.2014.04.057

    Article  CAS  PubMed  Google Scholar 

  23. Granchi C, Rizzolio F, Bordoni V et al (2016) 4-Aryliden-2-methyloxazol-5(4H)-one as a new scaffold for selective reversible MAGL inhibitors. J Enzyme Inhib Med Chem 31(1):137–146. https://doi.org/10.3109/14756366.2015.1010530

    Article  CAS  PubMed  Google Scholar 

  24. Granchi C, Rizzolio F, Palazzolo S et al (2016) Structural optimization of 4-chlorobenzoylpiperidine derivatives for the development of potent, reversible, and selective monoacylglycerol lipase (MAGL) inhibitors. J Med Chem 59(22):10299–10314. https://doi.org/10.1021/acs.jmedchem.6b01459

    Article  CAS  PubMed  Google Scholar 

  25. Bertrand T, Auge F, Houtmann J et al (2010) Structural basis for human monoglyceride lipase inhibition. J Mol Biol 396(3):663–673. https://doi.org/10.1016/j.jmb.2009.11.060

    Article  CAS  PubMed  Google Scholar 

  26. Griebel G, Pichat P, Beeske S et al (2015) Selective blockade of the hydrolysis of the endocannabinoid 2-arachidonoylglycerol impairs learning and memory performance while producing antinociceptive activity in rodents. Sci Rep 5:7642. https://doi.org/10.1038/srep07642

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Baell JB, Holloway GA (2010) New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. J Med Chem 53(7):2719–2740. https://doi.org/10.1021/jm901137j

    Article  CAS  PubMed  Google Scholar 

  28. Dahlin JL, Nissink JW, Strasser JM et al (2015) PAINS in the assay: chemical mechanisms of assay interference and promiscuous enzymatic inhibition observed during a sulfhydryl-scavenging HTS. J Med Chem 58(5):2091–2113. https://doi.org/10.1021/jm5019093

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Pharmacy, University of Pisa, Pisa, Italy

    Carlotta Granchi, Marco Macchia, Adriano Martinelli, Filippo Minutolo & Tiziano Tuccinardi

  2. Division of Experimental and Clinical Pharmacology, Department of Molecular Biology and Translational Research, National Cancer Institute and Center for Molecular Biomedicine, IRCCS, Pordenone, Italy

    Flavio Rizzolio & Isabella Caligiuri

  3. Department of Molecular Science and Nanosystems, Ca’ Foscari Università di Venezia, Venezia-Mestre, Italy

    Flavio Rizzolio

Authors
  1. Carlotta Granchi
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  2. Flavio Rizzolio
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  3. Isabella Caligiuri
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  4. Marco Macchia
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  5. Adriano Martinelli
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  6. Filippo Minutolo
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  7. Tiziano Tuccinardi
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Corresponding author

Correspondence to Tiziano Tuccinardi .

Editor information

Editors and Affiliations

  1. Division of Organic Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis, Zografou, Athens, Greece

    Thomas Mavromoustakos

  2. Division of Organic Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis, Zografou, Athens, Greece

    Tahsin F. Kellici

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Granchi, C. et al. (2018). Rational Development of MAGL Inhibitors. In: Mavromoustakos, T., Kellici, T. (eds) Rational Drug Design. Methods in Molecular Biology, vol 1824. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8630-9_20

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  • DOI: https://doi.org/10.1007/978-1-4939-8630-9_20

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-8629-3

  • Online ISBN: 978-1-4939-8630-9

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