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Insights from comprehensive multiple receptor docking to HDAC8

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Abstract

A systematic investigation of the available crystal structures of HDAC8 and of the influence of different receptor structures and docking protocols is presented. The study shows that the open conformation of HDAC8 may be preferred by ligands with flexible surface binding groups, as such a conformation allows the ligands to minimize their exposure to solvent upon binding. This observation allowed us to rationalize the excellent potency of pyrazole-based inhibitors compared to that of isoxazole-based inhibitors.

Multiple receptor scoring: Accuracies obtained for test set compounds with different combinations of two receptor structures. Each row and column is labeled according to the PDB code of the crystal structure the receptor was based upon. In each single column and row, three entries represent the different water occupancies. A preference for HDAC8 structures with an open binding site is observed

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References

  1. Rundlett SE, Carmen AA, Kobayashi R, Bavykin S, Turner BM, Grunstein M (1996) HDA1 and RPD3 are members of distinct yeast histone deacetylase complexes that regulate silencing and transcription. Proc Natl Acad Sci USA 93:14503–14508

    Google Scholar 

  2. Kouzarides T (2000) Acetylation: a regulatory modification to rival phosphorylation? EMBO J 19:1176–1179. doi:10.1093/emboj/19.6.1176

    Article  CAS  Google Scholar 

  3. Villar-Garea A, Esteller M (2004) Histone deacetylase inhibitors: understanding a new wave of anticancer agents. Int J Cancer 112:171–178. doi:10.1002/ijc.20372

    Article  CAS  Google Scholar 

  4. Balasubramanian S, Verner E, Buggy JJ (2009) Isoform-specific histone deacetylase inhibitors: the next step? Cancer Lett 280:211–221. doi:10.1016/j.canlet.2009.02.013

    Google Scholar 

  5. Khan N, Jeffers M, Kumar S, Hackett C, Boldog F, Khramtsov N, Qian X, Mills E, Berghs SC, Carey N, Finn PW, Collins LS, Tumber A, Ritchie JW, Jensen PB, Lichenstein HS, Sehested M (2008) Determination of the class and isoform selectivity of small-molecule histone deacetylase inhibitors. Biochem J 409:581–589. doi:10.1042/BJ20070779

    Article  CAS  Google Scholar 

  6. Chen YD, Jiang YJ, Zhou JW, Yu QS, You QD (2008) Identification of ligand features essential for HDACs inhibitors by pharmacophore modeling. J Mol Graph Model 26:1160–1168. doi:10.1016/j.jmgm.2007.10.007

    Article  CAS  Google Scholar 

  7. Guo Y, Xiao J, Guo Z, Chu F, Cheng Y, Wu S (2005) Exploration of a binding mode of indole amide analogues as potent histone deacetylase inhibitors and 3D-QSAR analyses. Bioorg Med Chem 13:5424–5434. doi:10.1016/j.bmc.2005.05.016

    Article  CAS  Google Scholar 

  8. Ragno R, Simeoni S, Rotili D, Caroli A, Botta G, Brosch G, Massa S, Mai A (2008) Class II-selective histone deacetylase inhibitors. Part 2: alignment-independent GRIND 3-D QSAR, homology and docking studies. Eur J Med Chem 43:621–632. doi:10.1016/j.ejmech.2007.05.004

    Article  CAS  Google Scholar 

  9. Ragno R, Simeoni S, Valente S, Massa S, Mai A (2006) 3-D QSAR studies on histone deacetylase inhibitors. A GOLPE/GRID approach on different series of compounds. J Chem Info Model 46:1420–1430. doi:10.1021/ci050556b

    Article  CAS  Google Scholar 

  10. Zhu Y, Li HF, Lu S, Zheng YX, Wu Z, Tang WF, Zhou X, Lu T (2010) Investigation on the isoform selectivity of histone deacetylase inhibitors using chemical feature based pharmacophore and docking approaches. Eur J Med Chem 45:1777–1791. doi:10.1016/j.ejmech.2010.01.010

    Article  CAS  Google Scholar 

  11. Tang H, Wang XS, Huang XP, Roth BL, Butler KV, Kozikowski AP, Jung M, Tropsha A (2009) Novel inhibitors of human histone deacetylase (HDAC) identified by QSAR modeling of known inhibitors, virtual screening, and experimental validation. J Chem Info Model 49:461–476. doi:10.1021/ci800366f

    Article  CAS  Google Scholar 

  12. Di Micco S, Terracciano S, Bruno I, Rodriquez M, Riccio R, Taddei M, Bifulco G (2008) Molecular modeling studies toward the structural optimization of new cyclopeptide-based HDAC inhibitors modeled on the natural product FR235222. Bioorg Med Chem 16:8635–8642. doi:10.1016/j.bmc.2008.08.003

    Article  Google Scholar 

  13. Grolla AA, Podesta V, Chini MG, Di Micco S, Vallario A, Genazzani AA, Canonico PL, Bifulco G, Tron GC, Sorba G, Pirali T (2009) Synthesis, biological evaluation, and molecular docking of Ugi products containing a zinc-chelating moiety as novel inhibitors of histone deacetylases. J Med Chem 52:2776–2785. doi:10.1021/jm801529c

    Article  CAS  Google Scholar 

  14. Huang WJ, Chen CC, Chao SW, Lee SS, Hsu FL, Lu YL, Hung MF, Chang CI (2010) Synthesis of N-hydroxycinnamides capped with a naturally occurring moiety as inhibitors of histone deacetylase. Chem Med Chem 5:598–607. doi:10.1002/cmdc.200900494

    CAS  Google Scholar 

  15. Lu Q, Wang DS, Chen CS, Hu YD (2005) Structure-based optimization of phenylbutyrate-derived histone deacetylase inhibitors. J Med Chem 48:5530–5535. doi:10.1021/jm0503749

    Article  CAS  Google Scholar 

  16. Mai A, Valente S, Nebbioso A, Simeoni S, Ragno R, Massa S, Brosch G, De Bellis F, Manzo F, Altucci L (2009) New pyrrole-based histone deacetylase inhibitors: binding mode, enzyme- and cell-based investigations. Int J Biochem Cell Biol 41:235–247. doi:10.1016/j.biocel.2008.09.002

    Article  CAS  Google Scholar 

  17. Pirali T, Faccio V, Mossetti R, Grolla AA, Di Micco S, Bifulco G, Genazzani AA, Tron GC (2010) Synthesis, molecular docking and biological evaluation as HDAC inhibitors of cyclopeptide mimetics by a tandem three-component reaction and intramolecular [3 + 2] cycloaddition. Mol Divers 14:109–121. doi:10.1007/s11030-009-9153-9

    Article  CAS  Google Scholar 

  18. Wang DF, Wiest O, Helquist P, Lan-Hargest HY, Wiech NL (2004) On the function of the 14 A long internal cavity of histone deacetylase-like protein: implications for the design of histone deacetylase inhibitors. J Med Chem 47:3409–3417. doi:10.1021/jm0498497

    Article  CAS  Google Scholar 

  19. Ortore G, Di CF, Martinelli A (2009) Docking of hydroxamic acids into HDAC1 and HDAC8: a rationalization of activity trends and selectivities. J Chem Info Model 49:2774–2785. doi:10.1021/ci900288e

    Article  CAS  Google Scholar 

  20. Wang DF, Helquist P, Wiech NL, Wiest O (2005) Toward selective histone deacetylase inhibitor design: homology modeling, docking studies, and molecular dynamics simulations of human class I histone deacetylases. J Med Chem 48:6936–6947. doi:10.1021/jm0505011

    Article  CAS  Google Scholar 

  21. Estiu G, West N, Mazitschek R, Greenberg E, Bradner JE, Wiest O (2010) On the inhibition of histone deacetylase 8. Bioorg Med Chem 18:4103–4110. doi:10.1016/j.bmc.2010.03.080

    Article  CAS  Google Scholar 

  22. Raha K, Merz KM Jr (2004) A quantum mechanics-based scoring function: study of zinc ion-mediated ligand binding. J Am Chem Soc 126:1020–1021. doi:10.1021/ja038496i

    Article  CAS  Google Scholar 

  23. Irwin JJ, Raushel FM, Shoichet BK (2005) Virtual screening against metalloenzymes for inhibitors and substrates. Biochemistry 44:12316–12328. doi:10.1021/bi050801k

    Article  CAS  Google Scholar 

  24. Park H, Lee S (2004) Homology modeling, force field design, and free energy simulation studies to optimize the activities of histone deacetylase inhibitors. J Comput Aided Mol Des 18:375–388. doi:10.1007/s10822-004-2283-3

    Article  CAS  Google Scholar 

  25. Ryde U (1995) Molecular dynamics simulations of alcohol dehydrogenase with a four- or five-coordinate catalytic zinc ion. Proteins 21(1):40–56. doi:10.1002/prot.340210106

    Article  CAS  Google Scholar 

  26. Somoza JR, Skene RJ, Katz BA, Mol C, Ho JD, Jennings AJ, Luong C, Arvai A, Buggy JJ, Chi E, Tang J, Sang BC, Verner E, Wynands R, Leahy EM, Dougan DR, Snell G, Navre M, Knuth MW, Swanson RV, McRee DE, Tari LW (2004) Structural snapshots of human HDAC8 provide insights into the class I histone deacetylases. Structure 12:1325–1334. doi:10.1016/j.str.2004.04.012

    Article  CAS  Google Scholar 

  27. Sherman W, Day T, Jacobson MP, Friesner RA, Farid R (2006) Novel procedure for modeling ligand/receptor induced fit effects. J Med Chem 49:534–553. doi:10.1021/Jm050540c

    Article  CAS  Google Scholar 

  28. Verdonk ML, Cole JC, Hartshorn MJ, Murray CW, Taylor RD (2003) Improved protein-ligand docking using GOLD. Proteins Struct Funct Gen 52:609–623. doi:10.1002/Prot.10465

    Article  CAS  Google Scholar 

  29. Dowling DP, Gantt SL, Gattis SG, Fierke CA, Christianson DW (2008) Structural studies of human histone deacetylase 8 and its site-specific variants complexed with substrate and inhibitors. Biochemistry 47:13554–13563. doi:10.1021/bi801610c

    Article  CAS  Google Scholar 

  30. Vannini A, Volpari C, Filocamo G, Casavola EC, Brunetti M, Renzoni D, Chakravarty P, Paolini C, De Francesco R, Gallinari P, Steinkuhler C, Di Marco S (2004) Crystal structure of a eukaryotic zinc-dependent histone deacetylase, human HDAC8, complexed with a hydroxamic acid inhibitor. Proc Natl Acad Sci USA 101:15064–15069. doi:10.1073/pnas.0404603101

    Google Scholar 

  31. Vannini A, Volpari C, Gallinari P, Jones P, Mattu M, Carfi A, De Francesco R, Steinkuhler C, Di Marco S (2007) Substrate binding to histone deacetylases as shown by the crystal structure of the HDAC8–substrate complex. EMBO Rep 8:879–884. doi:10.1038/sj.embor.7401047

    Google Scholar 

  32. He B, Velaparthi S, Pieffet G, Pennington C, Mahesh A, Holzle DL, Brunsteiner M, van Breemen R, Blond SY, Petukhov PA (2009) Binding ensemble profiling with photoaffinity labeling (BEProFL) approach: mapping the binding poses of HDAC8 inhibitors. J Med Chem 52:7003–7013. doi:10.1021/jm9005077

    Article  CAS  Google Scholar 

  33. Neelarapu R, Holzle DL, Velaparthi S, Bai H, Brunsteiner M, Blond SY, Petukhov PA (2011) Design, synthesis, docking, and biological evaluation of novel diazide-containing isoxazole- and pyrazole-based histone deacetylase probes. J Med Chem 54:4350–4364. doi:10.1021/jm2001025

    Article  CAS  Google Scholar 

  34. Bora-Tatar G, Dayangac-Erden D, Demir AS, Dalkara S, Yelekci K, Erdem-Yurter H (2009) Molecular modifications on carboxylic acid derivatives as potent histone deacetylase inhibitors: activity and docking studies. Bioorg Med Chem 17:5219–5228. doi:10.1016/j.bmc.2009.05.042

    Google Scholar 

  35. Kirchmair J, Markt P, Distinto S, Schuster D, Spitzer GM, Liedl KR, Langer T, Wolber G (2008) The protein data bank (PDB), its related services and software tools as key components for in silico guided drug discovery. J Med Chem 51:7021–7040. doi:10.1021/Jm8005977

    Article  CAS  Google Scholar 

  36. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE (2004) UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612. doi:10.1002/jcc.20084

    Google Scholar 

  37. Eswar N, Webb B, Marti-Renom MA, Madhusudhan MS, Eramian D, Shen MY, Pieper U, Sali A (2007) Comparative protein structure modeling using MODELLER. Curr Protoc Prot Sci 2:2.9. doi:10.1002/0471140864.ps0209s50

  38. Word JM, Lovell SC, Richardson JS, Richardson DC (1999) Asparagine and glutamine: using hydrogen atom contacts in the choice of side-chain amide orientation. J Mol Biol 285:1735–1747

    Article  CAS  Google Scholar 

  39. Chemical Computing Group Inc. (2010) Molecular Operating Environment (MOE). Chemical Computing Group Inc., Montreal. http://www.chemcomp.com. 2010

  40. Vanommeslaeghe K, Loverix S, Geerlings P, Tourwe D (2005) DFT-based ranking of zinc-binding groups in histone deacetylase inhibitors. Biorg Med Chem 13:6070–6082. doi:10.1016/j.bmc.2005.06.009

    Article  CAS  Google Scholar 

  41. Jones G, Willett P, Glen RC (1995) Molecular recognition of receptor-sites using a genetic algorithm with a description of desolvation. J Mol Biol 245:43–53. doi:10.1016/S0022-2836(95)80037-9

    Article  CAS  Google Scholar 

  42. Jain AN (2007) Surflex-Dock 2.1: robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search. J Comput Aided Mol Des 21:281–306. doi:10.1007/s10822-007-9114-2

  43. Mayo SL, Olafson BD, Goddard WA (1990) Dreiding—a generic force-field for molecular simulations. J Phys Chem 94:8897–8909. doi:10.1021/j100389a010

    Google Scholar 

  44. Pieffet G, Petukhov PA (2009) Parameterization of aromatic azido groups: application as photoaffinity probes in molecular dynamics studies. J Mol Model 15:1291–1297. doi:10.1007/s00894-009-0488-z

    Article  CAS  Google Scholar 

  45. Jakalian A, Jack DB, Bayly CI (2002) Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J Comput Chem 23:1623–1641. doi:10.1002/Jcc.10128

    Article  CAS  Google Scholar 

  46. Openeye Scientific Software (2010) molcharge. Openeye Scientific Software, Santa Fe

  47. Guha R, Howard MT, Hutchison GR, Murray-Rust P, Rzepa H, Steinbeck C, Wegner J, Willighagen EL (2006) The Blue Obelisk—interoperability in chemical informatics. J Chem Info Model 46:991–998. doi:10.1021/ci050400b

    Google Scholar 

  48. R Foundation for Statistical Computing (2009) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

  49. Huang N, Shoichet BK (2008) Exploiting ordered waters in molecular docking. J Med Chem 51:4862–4865. doi:10.1021/jm8006239

    Article  CAS  Google Scholar 

  50. Barril X, Fradera X (2006) Incorporating protein flexibility into docking and structure-based drug design. Expert Opin Drug Discov 1:1–14

    Google Scholar 

  51. Rueda M, Bottegoni G, Abagyan R (2010) Recipes for the selection of experimental protein conformations for virtual screening. J Chem Info Model 50:186–193. doi:10.1021/ci9003943

    Article  CAS  Google Scholar 

  52. Yoon S, Welsh WJ (2004) Identification of a minimal subset of receptor conformations for improved multiple conformation docking and two-step scoring. J Chem Inf Comput Sci 44:88–96. doi:10.1021/ci0341619

    CAS  Google Scholar 

  53. Zhong H, Tran LM, Stang JL (2009) Induced-fit docking studies of the active and inactive states of protein tyrosine kinases. J Mol Graph Model 28:336–346. doi:10.1016/j.jmgm.2009.08.012

    Article  CAS  Google Scholar 

  54. Barril X, Morley SD (2005) Unveiling the full potential of flexible receptor docking using multiple crystallographic structures. J Med Chem 48:4432–4443. doi:10.1021/Jm048972v

    Article  CAS  Google Scholar 

  55. Wu R, Lu Z, Cao Z, Zhang Y (2011) Zinc chelation with hydroxamate in histone deacetylases modulated by water access to the linker binding channel. J Am Chem Soc 133:6110–6113. doi:10.1021/ja111104p

    Article  CAS  Google Scholar 

  56. Wang D, Helquist P, Wiest O (2007) Zinc binding in HDAC inhibitors: a DFT study. J Org Chem 72:5446–5449. doi:10.1021/jo070739s

    Article  CAS  Google Scholar 

  57. Gantt SL, Gattis SG, Fierke CA (2006) Catalytic activity and inhibition of human histone deacetylase 8 is dependent on the identity of the active site metal ion. Biochemistry 45:6170–6178. doi:10.1021/bi060212u

    Article  CAS  Google Scholar 

  58. Chen Y, Lopez-Sanchez M, Savoy DN, Billadeau DD, Dow GS, Kozikowski AP (2008) A series of potent and selective, triazolylphenyl-based histone deacetylases inhibitors with activity against pancreatic cancer cells and Plasmodium falciparum. J Med Chem 51:3437–3448. doi:10.1021/jm701606b

    Google Scholar 

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Acknowledgments

This study was in part funded by the National Cancer Institute/National Institute of Health grant R01 CA131970 and Alzheimer’s Drug Discovery Foundation grant 20101103. We also thank Ajay Jane for providing a free academic version of Surflex-dock. Molecular modeling was in part conducted using free academic licenses for the UCSF Chimera package from the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco (supported by NIH grant P41 RR-01081) and OpenEye Scientific Software, Santa Fe, NM, USA.

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  1. Michael Brunsteiner

    Present address: Institute of Biotechnology and Biochemical Engineering, Graz University of Technology, Petersgasse 12/1, 8010, Graz, Austria

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  1. Department of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, University of Illinois at Chicago, 833 South Wood Street, Chicago, IL, 60612, USA

    Michael Brunsteiner & Pavel A. Petukhov

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  1. Michael Brunsteiner
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Correspondence to Pavel A. Petukhov.

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Brunsteiner, M., Petukhov, P.A. Insights from comprehensive multiple receptor docking to HDAC8. J Mol Model 18, 3927–3939 (2012). https://doi.org/10.1007/s00894-011-1297-8

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