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Novel DOT1L ReceptorNatural Inhibitors Involved in Mixed Lineage Leukemia: a Virtual Screening, Molecular Docking and Dynamics Simulation Study

  • Raj, Utkarsh (Bioinformatics, Information Technology, Indian Institute of Information Technology) ;
  • Kumar, Himansu (Bioinformatics, Information Technology, Indian Institute of Information Technology) ;
  • Gupta, Saurabh (Bioinformatics, Information Technology, Indian Institute of Information Technology) ;
  • Varadwaj, Pritish Kumar (Bioinformatics, Information Technology, Indian Institute of Information Technology)
  • Published : 2015.05.18

Abstract

Background: The human protein methyl-transferase DOT1L catalyzes the methylation of histone H3 on lysine 79 (H3K79) at homeobox genes and is also involved in a number of significant processes ranging from gene expression to DNA-damage response and cell cycle progression. Inhibition of DOT1L activity by shRNA or small-molecule inhibitors has been established to prevent proliferation of various MLL-rearranged leukemia cells in vitro, establishing DOT1L an attractive therapeutic target for mixed lineage leukemia (MLL). Most of the drugs currently in use for the MLL treatment are reported to have low efficacy, hence this study focused on various natural compounds which exhibit minimal toxic effects and high efficacy for the target receptor. Materials and Methods: Structures of human protein methyl-transferase DOT1L and natural compound databases were downloaded from various sources. Virtual screening, molecular docking, dynamics simulation and drug likeness studies were performed for those natural compounds to evaluate and analyze their anti-cancer activity. Results: The top five screened compounds possessing good binding affinity were identified as potential high affinity inhibitors against DOT1L's active site. The top ranking molecule amongst the screened ligands had a Glide g-score of -10.940 kcal/mol and Glide e-model score of -86.011 with 5 hydrogen bonds and 12 hydrophobic contacts. This ligand's behaviour also showed consistency during the simulation of protein-ligand complex for 20000 ps, which is indicative of its stability in the receptor pocket. Conclusions: The ligand obtained out of this screening study can be considered as a potential inhibitor for DOT1L and further can be treated as a lead for the drug designing pipeline.

Keywords

DOT1L;mixed lineage leukemia;virtual screening;docking;dynamics

References

  1. Basavapathruni A, Jin L, Daigle SR, et al (2012). Conformational adaptation drives potent, selective and durable inhibition of the human protein methyltransferase DOT1L. Chemical Biology Drug Design, 80, 971-80. https://doi.org/10.1111/cbdd.12050
  2. Berman, HM, Westbrook J, Feng Z, et al (2002). The protein data bank. Biological Crystallography, 58, 899-907. https://doi.org/10.1107/S0907444902003451
  3. Bernt KM, Zhu N, Sinha AU, et al (2011). MLL-rearranged leukemia is dependent on aberrant H3K79 methylation by DOT1L. Cancer Cell, 20, 66-78 https://doi.org/10.1016/j.ccr.2011.06.010
  4. Bitoun E, Oliver PL, Davies KE (2007). The mixed-lineage leukemia fusion partner AF4 stimulates RNA polymerase II transcriptional elongation and mediates coordinated chromatin remodeling. Hum Mol Genet, 16, 92-106.
  5. Bowers KJ, Dror RO, Shaw DE (2006). The midpoint method for parallelization of particle simulations. J Chem Phys, 124, 184109-11. https://doi.org/10.1063/1.2191489
  6. Cacabelos R (2014). Epigenomic networking in drug development: from pathogenic mechanisms to pharmacogenomics. Drug Development Res, 75, 348-365. https://doi.org/10.1002/ddr.21219
  7. Chen CS, Sorensen PH, Domer PH, et al (1993). Molecular rearrangements on chromosome 11q23 predominate in infant acute lymphoblastic leukemia and are associated with specific biologic variables and poor outcome. Blood, 81, 2386-93.
  8. Chen SJ (2014). A Potential target of tanshinone iia for acute promyelocytic leukemia revealed by inverse docking and drug repurposing. Asian Pac J Cancer Prev, 15, 4301. https://doi.org/10.7314/APJCP.2014.15.10.4301
  9. Chen, SJ, Ren JL (2014). Identification of a potential anticancer target of danshensu by inverse docking. Asian Pacific J Cancer Prev, 15, 111-116. https://doi.org/10.7314/APJCP.2014.15.1.111
  10. Daigle SR, Olhava EJ, Therkelsen CA, et al (2011). Selective killing of mixed lineage leukemia cells by a potent small-molecule DOT1L inhibitor. Cancer Cell, 20, 53-65. https://doi.org/10.1016/j.ccr.2011.06.009
  11. Daigle SR, Olhava EJ, Therkelsen CA, et al (2013). Potent inhibition of DOT1L as treatment of MLL-fusion leukemia. Blood, 122, 1017-25. https://doi.org/10.1182/blood-2013-04-497644
  12. Daser A, Rabbitts TH (2005). The versatile mixed lineage leukaemia gene MLL and its many associations in leukaemogenesis. Semin Cancer Biol, 15, 175-188. https://doi.org/10.1016/j.semcancer.2005.01.007
  13. Dimri M, Bommi PV, Sahasrabuddhe AA, et al (2010). Dietary omega-3 polyunsaturated fatty acids suppress expression of EZH2 in breast cancer cells. Carcinogenesis, 31, 489-495. https://doi.org/10.1093/carcin/bgp305
  14. Felix CA, Hosler MR, Winick NJ, et al (1995). ALL-1 gene rearrangements in DNA topoisomerase II inhibitor-related leukemia in children. Blood, 85, 3250-6.
  15. Forsberg M, Lehtonen M, Heikkinen M, et al (2003). Pharmacokinetics and pharmacodynamics of entacapone and tolcapone after acute and repeated administration: a comparative study in the rat. J Pharmacol Exp Ther, 304, 498-506. https://doi.org/10.1124/jpet.102.042846
  16. Halgren T (2009). Identifying and characterizing binding sites and assessing druggability. J Chem. Inf. Model, 49, 377-389.
  17. Helin, K, Dhanak D (2013). Chromatin proteins and modifications as drug targets. Nature, 502, 480-488. https://doi.org/10.1038/nature12751
  18. Knutson SK, Warholic NM, Wigle TJ, et al (2013). Durable tumor regression in genetically altered malignant rhabdoid tumors by inhibition of methyltransferase EZH2. Proceed National Academy Scien, 110, 7922-27. https://doi.org/10.1073/pnas.1303800110
  19. Krivtsov AV, Armstrong SA (2007). MLL translocations, histone modifications and leukaemia stem-cell development. Nat Rev Cancer, 7, 823-833. https://doi.org/10.1038/nrc2253
  20. Krivtsov AV, Feng Z, Lemieux ME, et al (2008). H3K79 methylation profiles define murine and human MLL-AF4 leukemias. Cancer Cell, 14, 355-68. https://doi.org/10.1016/j.ccr.2008.10.001
  21. Liedtke M, Cleary ML (2009). Therapeutic targeting of MLL. Blood, 113, 6061-8. https://doi.org/10.1182/blood-2008-12-197061
  22. Lu D (2013). Epigenetic modification enzymes: catalytic mechanisms and inhibitors. Acta Pharmaceutica Sinica B, 3, 141-9. https://doi.org/10.1016/j.apsb.2013.04.007
  23. McLean CM, Karemaker ID, van Leeuwen F (2014). The emerging roles of DOT1L in leukemia and normal development. Leukemia, 28, 2131-8. https://doi.org/10.1038/leu.2014.169
  24. Mrozek K, Heinonen K, Lawrence D, et al (1997). Adult patients with de novo acute myeloid leukemia and t (9; 11) (p22; q23) have a superior outcome to patients with other translocations involving band 11q23: a cancer and leukemia group B study. Blood, 90, 4532-8.
  25. Mueller D, Bach C, Zeisig D, et al (2007). A role for the MLL fusion partner ENL in transcriptional elongation and chromatin modification. Blood, 110, 4445-54. https://doi.org/10.1182/blood-2007-05-090514
  26. Mueller D, Garcia-Cuellar MP, Bach C, et al (2009). Misguided transcriptional elongation causes mixed lineage leukemia. PLoS Biol, 7, 1000249 https://doi.org/10.1371/journal.pbio.1000249
  27. Okada Y, Feng Q, Lin Y, et al (2005). hDOT1L links histone methylation to leukemogenesis. Cell, 121, 167-178. https://doi.org/10.1016/j.cell.2005.02.020
  28. Onder TT, Kara N, Cherry A, et al (2012). Chromatin-modifying enzymes as modulators of reprogramming. Nature, 483, 598-602. https://doi.org/10.1038/nature10953
  29. Popovic R, Licht JD (2012). Emerging epigenetic targets and therapies in cancer medicine. Cancer discovery, 2, 405-413. https://doi.org/10.1158/2159-8290.CD-12-0076
  30. Puzyn T, Leszczynski J, Cronin MTD (2010). In silico approaches for predicting ADME properties. Recent Advances in QSAR Studies, 8, 283-304.
  31. Radha M, Suganya J, Naorem DL, Nishandhini M (2014). In silico docking studies of selected flavonoids-natural healing agents against breast cancer. Asian Pac J Cancer Prev, 15, 8155-9. https://doi.org/10.7314/APJCP.2014.15.19.8155
  32. Rajamani R, Good AC (2007). Ranking poses in structure-based lead discovery and optimization: current trends in scoring function development. Curr Opin Drug Discov Devel, 10, 308-15.
  33. Raj U, Varadwaj PK (2015). Flavonoids as multi-target inhibitors for proteins associated with ebola virus: in-silico discovery using virtual screening and molecular docking studies. interdisciplinary sciences: computational life sciences, 1-10. DOI: 10.1007/s12539-014-0246-5. https://doi.org/10.1007/s12539-014-0246-5
  34. Ross ME, Mahfouz R, Onciu M, et al (2004). Gene expression profiling of pediatric acute myelogenous leukemia. Blood, 104, 3679-3687. https://doi.org/10.1182/blood-2004-03-1154
  35. Sastry, GM, Adzhigirey M, Day T, Annabhimoju, R, Sherman W (2013). Protein and ligand preparation: Parameters, protocols, and influence on virtual screening enrichments. J Comput Aid Mol Des, 27, 221-34. https://doi.org/10.1007/s10822-013-9644-8
  36. Shaw David E, Kresten Lindorff-Larsen, Stefano Piana, et al (2010). Improved Side-Chain Torsion Potentials for the Amber ff99SB Protein Force Field. Proteins: Structure Function Bioinformatics, 78, 1950-8.
  37. Shaw DE. Yibing S, John LK, Michael PE, Ron OD (2005). Gaussian split ewald: a fast ewald mesh method for molecular simulation. J Chem Phys, 122, 1-13.
  38. Tummino PJ, Campbell RM (2014). Cancer epigenetics drug discovery and development: the challenge of hitting the mark. J Clin Invest, 124, 64-9. https://doi.org/10.1172/JCI71605
  39. Verma SK (2015). Recent progress in the discovery of epigenetic inhibitors for the treatment of cancer. Cancer Epigenetics, 1238, 677-88.
  40. Verma A (2012). Lead finding from Phyllanthus debelis with hepatoprotective potentials. Asian Pac J Trop Biomedicine, 2, 1735-7. https://doi.org/10.1016/S2221-1691(12)60486-9
  41. Woo J, Kim HY, Byun BJ, et al (2014). Biological evaluation of tanshindiols as EZH2 histone methyltransferase inhibitors. Bioorganic Med Chem Letters, 24, 2486-92. https://doi.org/10.1016/j.bmcl.2014.04.010
  42. Yu W, Chory EJ, Wernimont AK, et al (2012). Catalytic site remodelling of the DOT1L methyltransferase by selective inhibitors. Nature Communications, 3, 1288. https://doi.org/10.1038/ncomms2304
  43. Yu W, Tempel W, Smil D, et al (2012). Crystal structure of Dot1l in complex with 5-iodotubercidin. DOI:10.2210/pdb3uwp/pdb. https://doi.org/10.2210/pdb3uwp/pdb
  44. Zhang W, Xia X, Reisenauer MR, Hemenway CS, Kone BC (2006). Dot1a-AF9 complex mediates histone H3 Lys-79 hypermethylation and repression of ENaCalpha in an aldosterone-sensitive manner. J Biol Chem, 281, 18059-18068. https://doi.org/10.1074/jbc.M601903200

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