Molecular modeling of novel non-steroidal aromatase inhibitors containing 1,2,4-triazole

A. M. Andrianov ; G. I. Nikolaev ; I. A. Kashin ; Y. V. Kornoushenko ; S. A. Usanov

Matematičeskaâ biologiâ i bioinformatika, Tome 13 (2018) no. 1, pp. 290-307

Résumé

Computer-aided design of the high-affinity inhibitors of aromatase based on 1,2,4-triasole derivatives was performed by molecular modeling tools. Potential biological activity of the designed compounds was evaluated by molecular docking and quantum chemistry calculations. As a result, nine hits that form a coordinate bond with the iron atom of the enzyme hem and effectively interact with its substrate-binding site were identified. Analysis of intermolecular interactions appearing in the structural complexes of these ligands with aromatase was carried out and the enthalpies of their formation were calculated. Based on the data obtained, the identified compounds were suggested to present good scaffolds for the development of novel effective drugs against breast cancer.

Bibliographie

[1] L. F. Macedo, G. Sabnis, A. Brodie, “Aromatase inhibitors and breast cancer”, Ann. N. Y. Acad. Sci., 1155 (2009), 162–173 | DOI | DOI

[2] D. Ghosh, J. Griswold, M. Erman, W. Pangborn, “Structural basis for androgen specifity and oestrogen synthesis in human aromatase”, Nature, 457:7226 (2009), 219–223 | DOI | DOI

[3] Y. Hong, S. Chen, “Aromatase inhibitors: structural features and biochemical characterization”, Ann. N. Y. Acad. Sci., 1089 (2006), 237–251 | DOI | DOI

[4] U. Dutta, K. Pant, “Aromatase inhibitors: past, present and future in breast cancer therapy”, Med. Oncol., 25:2 (2008), 113–124 | DOI | DOI

[5] D. Ghosh, J. Lo, C. Egbuta, “Recent progress in the discovery of next generation inhibitors of aromatase from the structure-function perspective”, J. Med. Chem., 59 (2016), 5131–5148 | DOI | DOI

[6] D. Schuster, C. Laggner, T. M. Steindl, A. Palusczak, R. W. Hartmann, T. Langer, “Pharmacophore modeling and in silico screening for new P450 19 (aromatase) inhibitors”, J. Chem. Inf. Model., 46:3 (2006), 1301–1311 | DOI | DOI

[7] M. A. Neves, T. C. Dinis, G. Colombo, M. L. Sá e Melo, “Fast three dimensional pharmacophore virtual screening of new potent nonsteroid aromatase inhibitors”, J. Med. Chem., 52:1 (2009), 143–150 | DOI | DOI

[8] M. A. Neves, T. C. Dinis, G. Colombo, M. L. Sá e Melo, “An efficient steroid pharmacophore-based strategy to identify new aromatase inhibitors”, Eur. J. Med. Chem., 44:10 (2009), 4121–4127 | DOI | DOI

[9] D. Ghosh, J. Griswold, M. Erman, W. Pangborn, “X-ray structure of human aromatase reveals an androgen-specific active site”, J. Steroid Biochem. Mol. Biol., 118:4–5 (2010), 197–202 | DOI | DOI

[10] P. P. Roy, K. Roy, “Molecular docking and QSAR studies of aromatase inhibitor androstenedione derivatives”, J. Pharm. Pharmacol., 62 (2010), 1717–1728 | DOI | DOI

[11] D. Ghosh, J. Lo, D. Morton, D. Valette, J. Xi, J. Griswold, S. Hubbell, C. Egbuta, W. Jiang, J. An, H. M. Davies, “Novel aromatase inhibitors by structure-guided design”, J. Med. Chem., 55 (2012), 8464–8476 | DOI | DOI

[12] K. Bonfield, E. Amato, T. Bankemper, H. Agard, J. Steller, J. M. Keeler, D. Roy, A. McCallum, S. Paula, L. Ma, “Development of a new class of aromatase inhibitors: design, synthesis and inhibitory activity of 3-phenylchroman-4-one (isoflavanone) derivatives”, Bioorg. Med. Chem., 20 (2012), 2603–2613 | DOI | DOI

[13] H. Xie, K. Qiu, X. Xie, “3D QSAR studies, pharmacophore modeling and virtual screening on a series of steroidal aromatase inhibitors”, Int. J. Mol. Sci., 15 (2014), 20927–20947 | DOI | DOI

[14] S. Lee, M. G. Barron, “Development of 3D-QSAR model for acetylcholinesterase inhibitors using a combination of fingerprint, molecular docking, and structure-based pharmacophore approaches”, Toxicol. Sci., 148 (2015), 60–70 | DOI | DOI

[15] S. Chen, J. H. Hsieh, R. Huang, S. Sakamuru, L. Y. Hsin, M. Xia, K. R. Shockley, S. Auerbach, N. Kanaya, H. Lu, D. Svoboda, K. L. Witt, B. A. Merrick, C. T. Teng, R. R. Tice, “Cell-based high-throughput screening for aromatase inhibitors in the Tox21 10K library”, Toxicol. Sci., 147 (2015), 446–457 | DOI | DOI

[16] R. Ghodsi, B. Hemmateenejad, “QSAR study of diarylalkylimidazole and diarylalkyltriazole aromatase inhibitors”, Med. Chem. Res., 25 (2016), 834–842 | DOI | DOI

[17] S. Lee, M. G. Barron, “A mechanism-based 3D-QSAR approach for classification and prediction of acetylcholinesterase inhibitory potency of organophosphate and carbamate analogs”, J. Comput. Aided Mol. Des., 30 (2016), 347–36 | DOI | DOI

[18] A. M. Prior, X. Yu, Park E-J, T. P. Kondratyuk, Y. Lin, J. M. Pezzuto, D. Sun, “Structureactivity relationships and docking studies of synthetic 2-arylindole derivatives determined with aromatase and quinine reductase 1”, Bioorganic Med. Chem. Letters., 27 (2017), 5393–5399 | DOI | DOI

[19] A. Mojaddami, A. Sakhteman, M. Fereidoonnezhad, Z. Faghih, A. Najdian, S. Khabnadideh, H. Sadeghpour, Z. Rezaei, “Binding mode of triazole derivatives as aromatase inhibitors based on docking, protein ligand interaction fingerprinting, and molecular dynamics simulation studies”, Res. Pharm. Sci., 12:1 (2017), 21–30 | DOI | DOI

[20] M. Akram, W. Waratchareeyakul, J. Haupenthal, R. W. Hartmann, D. Schuster, “Pharmacophore Modeling and in Silico/in Vitro Screening for Human Cytochrome P450 11B1 and Cytochrome P450 11B2 Inhibitors”, Front. Chem., 5 (2017), 104 | DOI | DOI

[21] S. Lee, M. G. Barron, “3D-QSAR study of steroidal and azaheterocyclic human aromatase inhibitors using quantitative profile of protein-ligand interactions”, J. Cheminform., 10 (2018), 2 | DOI | DOI

[22] H. C. Kolb, M. G. Finn, K. B. Sharpless, “Click chemistry: Diverse chemical function from a few good reactions”, Angew. Chem. Int. Ed., 40:11 (2001), 2004–2021 | 3.0.CO;2-5 class='badge bg-secondary rounded-pill ref-badge extid-badge'>DOI | DOI

[23] C. A. Lipinski, F. Lombardo, B. W. Dominy, P. J. Feeney, “Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings”, Adv. Drug Deliv. Rev., 46:1–3 (2001), 3–26 | DOI | DOI

[24] J. J. Irwin, T. Sterling, M. M. Mysinger, E. S. Bolstad, R. G. Coleman, “ZINC: A free tool to discover chemistry for biology”, J. Chem. Inf. Model., 52:7 (2012), 1757–1768 | DOI | DOI

[25] T. Sander, J. Freyss, M. von Korff, C. Rufener, “DataWarrior: An open-source program for chemistry aware data visualization and analysis”, J. Chem. Inf. Model., 55:2 (2015), 460–473 | DOI | DOI

[26] J. D. Durrant, J. A. McCammon, “AutoClickChem: Click shemistry in silico”, PLoS Comput. Biol., 8:3 (2012), e1002397 | DOI | DOI

[27] D. S. Wishart, C. Knox, A. C. Guo, S. Shrivastava, M. Hassanali, P. Stothard, Z. Chang, J. Woolsey, “DrugBank: a comprehensive resource for in silico drug discovery and exploration”, Nucleic Acids Res., 34, Database issue (2006), D668–672 | DOI | DOI

[28] D. S. Wishart, Y. D. Feunang, A. C. Guo, E. J. Lo, A. Marcu, J. R. Grant, T. Sajed, D. Johnson, C. Li, Z. Sayeeda, N. Assempour, I. Iynkkaran, Y. Liu, A. Maciejewski, N. Gale, A. Wilson, L. Chin, R. Cummings, D. Le, A. Pon, C. Knox, M. Wilson, “DrugBank 5.0: a major update to the DrugBank database for 2018”, Nucleic Acids Res., 2017 | DOI | DOI

[29] S. D. Handoko, X. Ouyang, C. T.T. Su, C. K. Kwoh, Y. S. Ong, “QuickVina: Accelerating AutoDock Vina using gradient-based heuristics for global optimization”, TCBB, 9:5 (2012), 1266–1272

[30] Open Babel: The Open Source Chemistry Toolbox, (data obrascheniya: 09.06.2018) http://openbabel.org/wiki/Main_Page

[31] A. K. Rappe, C. J. Casewit, K. S. Colwell, W. A. Goddard III, Skiff W. M., “UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations”, J. Am. Chem. Soc., 114:25 (1992), 10024–10035 | DOI | DOI

[32] General Description of MORAC, (data obrascheniya: 09.06.2018) http://openmopac.net/manual

[33] J. D. Durrant, J. A. McCammon, “BINANA: A novel algorithm for ligand-binding characterization”, J. Mol. Graph. Model., 29 (2011), 888–893 | DOI | DOI

[34] I. K. McDonald, J. M. Thornton, “Satisfying hydrogen bonding potential in proteins”, J. Mol. Biol., 238 (1994), 777–793 | DOI | DOI

[35] Y. C. Kao, K. R. Korzekwa, C. A. Laughton, S. Chen, “Evaluation of the mechanism of aromatase cytochrome P450. A site-directed mutagenesis study”, Eur. J. Biochem., 268:2 (2001), 243–251 | DOI | DOI

[36] A. S. Christensen, T. Kubar, Q. Cui, M. Elstner, “Semiempirical quantum mechanical methods for noncovalent interactions for chemical and biochemical applications”, Chem. Rev., 116:9 (2016), 5301–5337 | DOI | DOI