Russian version English version
Volume 13   Issue 1   Year 2018
Andrianov A.M., Nikolaev G.I., Kashyn I.A., Kornoushenko Y.V., Usanov S.A.

Molecular Modeling Of Novel Non-Steroidal Aromatase Inhibitors Containing 1,2,4-Triazole

Mathematical Biology & Bioinformatics. 2018;13(1):290-307.

doi: 10.17537/2018.13.290.



  1. Macedo L.F., Sabnis G., Brodie A. Aromatase inhibitors and breast cancer. Ann. N. Y. Acad. Sci. 2009;1155:162-173. doi: 10.1111/j.1749-6632.2008.03689.x
  2. Ghosh D., Griswold J., Erman M., Pangborn W. Structural basis for androgen specifity and oestrogen synthesis in human aromatase. Nature. 2009;457(7226):219-223. doi: 10.1038/nature07614
  3. Hong Y., Chen S. Aromatase inhibitors: structural features and biochemical characterization. Ann. N. Y. Acad. Sci. 2006;1089:237-251. doi: 10.1196/annals.1386.022
  4. Dutta U., Pant K. Aromatase inhibitors: past, present and future in breast cancer therapy. Med. Oncol. 2008;25(2):113-124. doi: 10.1007/s12032-007-9019-x
  5. Ghosh D., Lo J., Egbuta C. Recent progress in the discovery of next generation inhibitors of aromatase from the structure-function perspective. J. Med. Chem. 2016;59:5131-5148. doi: 10.1021/acs.jmedchem.5b01281
  6. Schuster D., Laggner C., Steindl T.M., Palusczak A., Hartmann R.W., Langer T. Pharmacophore modeling and in silico screening for new P450 19 (aromatase) inhibitors. J. Chem. Inf. Model. 2006;46(3):1301-1311. doi: 10.1021/ci050237k
  7. Neves M.A., Dinis T.C., Colombo G., Sá e Melo M.L. Fast three dimensional pharmacophore virtual screening of new potent nonsteroid aromatase inhibitors. J. Med. Chem. 2009;52(1):143-150. doi: 10.1021/jm800945c
  8. Neves M.A., Dinis T.C., Colombo G., Sá e Melo M.L. An efficient steroid pharmacophore-based strategy to identify new aromatase inhibitors. Eur. J. Med. Chem. 2009;44(10):4121-4127. doi: 10.1016/j.ejmech.2009.05.003
  9. Ghosh D., Griswold J., Erman M., Pangborn W. X-ray structure of human aromatase reveals an androgen-specific active site. J. Steroid Biochem. Mol. Biol. 2010;118(4-5):197-202. doi: 10.1016/j.jsbmb.2009.09.012
  10. Roy P.P., Roy K. Molecular docking and QSAR studies of aromatase inhibitor androstenedione derivatives. J. Pharm. Pharmacol. 2010;62:1717-1728. doi: 10.1111/j.2042-7158.2010.01154.x
  11. Ghosh D., Lo J., Morton D., Valette D., Xi J., Griswold J., Hubbell S., Egbuta C., Jiang W., An J., Davies H.M. Novel aromatase inhibitors by structure-guided design. J. Med. Chem. 2012;55:8464-8476. doi: 10.1021/jm300930n
  12. Bonfield K., Amato E., Bankemper T., Agard H., Steller J., Keeler J.M., Roy D., McCallum A., Paula S., Ma L. Development of a new class of aromatase inhibitors: design, synthesis and inhibitory activity of 3-phenylchroman-4-one (isoflavanone) derivatives. Bioorg. Med. Chem. 2012;20:2603-2613. doi: 10.1016/j.bmc.2012.02.042
  13. Xie H., Qiu K., Xie X. 3D QSAR studies, pharmacophore modeling and virtual screening on a series of steroidal aromatase inhibitors. Int. J. Mol. Sci. 2014;15:20927-20947. doi: 10.3390/ijms151120927
  14. Lee S., Barron M.G. Development of 3D-QSAR model for acetylcholinesterase inhibitors using a combination of fingerprint, molecular docking, and structure-based pharmacophore approaches. Toxicol. Sci. 2015;148:60-70. doi: 10.1093/toxsci/kfv160
  15. Chen S., Hsieh J.H., Huang R., Sakamuru S., Hsin L.Y., Xia M., Shockley K.R., Auerbach S., Kanaya N., Lu H., Svoboda D., Witt K.L., Merrick B.A., Teng C.T., Tice R.R. Cell-based high-throughput screening for aromatase inhibitors in the Tox21 10K library. Toxicol. Sci. 2015;147:446-457. doi: 10.1093/toxsci/kfv141
  16. Ghodsi R., Hemmateenejad B. QSAR study of diarylalkylimidazole and diarylalkyltriazole aromatase inhibitors. Med. Chem. Res. 2016;25:834-842. doi: 10.1007/s00044-016-1530-1
  17. Lee S., Barron M.G. A mechanism-based 3D-QSAR approach for classification and prediction of acetylcholinesterase inhibitory potency of organophosphate and carbamate analogs. J. Comput. Aided Mol. Des. 2016;30:347-36. doi: 10.1007/s10822-016-9910-7
  18. Prior A.M., Yu X., Park E-J., Kondratyuk T.P., Lin Y., Pezzuto J.M., Sun D. Structure-activity relationships and docking studies of synthetic 2-arylindole derivatives determined with aromatase and quinine reductase 1. Bioorganic Med. Chem. Letters. 2017;27:5393-5399. doi: 10.1016/j.bmcl.2017.11.010
  19. Mojaddami A., Sakhteman A., Fereidoonnezhad M., Faghih Z., Najdian A., Khabnadideh S., Sadeghpour H., Rezaei Z. Binding mode of triazole derivatives as aromatase inhibitors based on docking, protein ligand interaction fingerprinting, and molecular dynamics simulation studies. Res. Pharm. Sci. 2017;12(1):21-30. doi: 10.4103/1735-5362.199043
  20. Akram M., Waratchareeyakul W., Haupenthal J., Hartmann R.W., Schuster D. Pharmacophore Modeling and in Silico/in Vitro Screening for Human Cytochrome P450 11B1 and Cytochrome P450 11B2 Inhibitors. Front. Chem. 2017;5:104. doi: 10.3389/fchem.2017.00104
  21. Lee S., Barron M.G. 3D-QSAR study of steroidal and azaheterocyclic human aromatase inhibitors using quantitative profile of protein-ligand interactions. J. Cheminform. 2018;10:2. doi: 10.1186/s13321-017-0253-8
  22. Kolb H.C., Finn M.G., Sharpless K.B. Click chemistry: Diverse chemical function from a few good reactions. Angew. Chem. Int. Ed. 2001;40(11):2004-2021. doi: 10.1002/1521-3773(20010601)40:11<2004::AID-ANIE2004>3.0.CO;2-5
  23. Lipinski C.A., Lombardo F., Dominy B.W., Feeney P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 2001;46(1-3):3-26. doi: 10.1016/S0169-409X(00)00129-0
  24. Irwin J.J., Sterling T., Mysinger M.M., Bolstad E.S., Coleman R.G. ZINC: A free tool to discover chemistry for biology. J. Chem. Inf. Model. 2012;52(7):1757-1768. doi: 10.1021/ci3001277
  25. Sander T., Freyss J., von Korff M., Rufener C. DataWarrior: An open-source program for chemistry aware data visualization and analysis. J. Chem. Inf. Model. 2015;55(2):460-473. doi: 10.1021/ci500588j
  26. Durrant J.D., McCammon J.A. AutoClickChem: Click ˝hemistry in silico. PLoS Comput. Biol. 2012;8(3):e1002397. doi: 10.1371/journal.pcbi.1002397
  27. Wishart D.S., Knox C., Guo A.C., Shrivastava S., Hassanali M., Stothard P., Chang Z., Woolsey J. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res. 2006;34 (Database issue):D668-672. doi: 10.1093/nar/gkj067
  28. Wishart D.S., Feunang Y.D., Guo A.C., Lo E.J., Marcu A., Grant J.R., Sajed T., Johnson D., Li C., Sayeeda Z., Assempour N., Iynkkaran I., Liu Y., Maciejewski A., Gale N., Wilson A., Chin L., Cummings R., Le D., Pon A., Knox C., Wilson M. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 2017.
  29. Handoko S.D., Ouyang X., Su C.T.T., Kwoh C.K., Ong Y.S. QuickVina: Accelerating AutoDock Vina using gradient-based heuristics for global optimization. TCBB. 2012;9(5):1266-1272. doi: 10.1109/TCBB.2012.82
  30. Open Babel: The Open Source Chemistry Toolbox. (accessed 09 June 2018).
  31. Rappe A.K., Casewit C.J., Colwell K.S., Goddard III W.A., Skiff W.M. UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations. J. Am. Chem. Soc. 1992;114(25):10024-10035. doi: 10.1021/ja00051a040
  32. General Description of MORA. (accessed 09 June 2018).
  33. Durrant J.D., McCammon J.A. BINANA: A novel algorithm for ligand-binding characterization. J. Mol. Graph. Model. 2011;29:888-893. doi: 10.1016/j.jmgm.2011.01.004
  34. McDonald I.K., Thornton J.M. Satisfying hydrogen bonding potential in proteins. J. Mol. Biol. 1994;238:777-793. doi: 10.1006/jmbi.1994.1334
  35. Kao Y.C., Korzekwa K.R., Laughton C. A., Chen S. Evaluation of the mechanism of aromatase cytochrome P450. A site-directed mutagenesis study. Eur. J. Biochem. 2001;268(2):243-251. doi: 10.1046/j.1432-1033.2001.01886.x
  36. Christensen A.S., Kubař T., Cui Q., Elstner M. Semiempirical quantum mechanical methods for noncovalent interactions for chemical and biochemical applications. Chem. Rev. 2016;116(9):5301-5337. doi: 10.1021/acs.chemrev.5b00584
Table of Contents Original Article
Math. Biol. Bioinf.
doi: 10.17537/2018.13.290
published in Russian

Abstract (rus.)
Abstract (eng.)
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