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Journal of Chemistry
Volume 2015, Article ID 879238, 13 pages
http://dx.doi.org/10.1155/2015/879238
Research Article

Study on Molecular Recognition between Euphorbia Factor L713283 and β-Tubulin via Molecular Simulation Methods

1Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China
2Chongqing High-Tech Industrial Development Zone, Chongqing 400039, China
3Faculty of Biotechnology Industry, Chengdu University, Chengdu 610106, China
4College of Chemistry, Leshan Normal University, Leshan 614004, China

Received 26 August 2015; Revised 25 October 2015; Accepted 28 October 2015

Academic Editor: Teodorico C. Ramalho

Copyright © 2015 Shan Chang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. D. J. Hunter and K. S. Reddy, “Noncommunicable diseases,” The New England Journal of Medicine, vol. 369, no. 14, pp. 1336–1343, 2013. View at Publisher · View at Google Scholar · View at Scopus
  2. C. E. Desantis, C. C. Lin, A. B. Mariotto et al., “Cancer treatment and survivorship statistics, 2014,” CA: A Cancer Journal for Clinicians, vol. 64, no. 4, pp. 252–271, 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. R. C. Haydon, L. Zhou, and T.-C. He, “Tyrosine kinase inhibitor STI-571: the new wonder drug of cancer therapy,” Cancer Biology & Therapy, vol. 3, no. 4, pp. 393–394, 2004. View at Publisher · View at Google Scholar · View at Scopus
  4. T. S. Reid and L. S. Beese, “Crystal structures of the anticancer clinical candidates R115777 (Tipifarnib) and BMS-214662 complexed with protein farnesyltransferase suggest a mechanism of FTI selectivity,” Biochemistry, vol. 43, no. 22, pp. 6877–6884, 2004. View at Publisher · View at Google Scholar · View at Scopus
  5. L. F. Allen, J. Sebolt-Leopold, and M. B. Meyer, “CI-1040 (PD184352), a targeted signal transduction inhibitor of MEK (MAPKK),” Seminars in Oncology, vol. 30, no. 5, pp. 105–116, 2003. View at Publisher · View at Google Scholar · View at Scopus
  6. R. M. Reguera, Y. Perez-Pertejo, C. M. Redondo, R. Diaz-Gonzalez, and R. Balaña-Fouce, “Type I DNA topoisomerase from protozoan pathogens as a potential target for anti-tumoral drugs,” Medicina, vol. 67, no. 6, pp. 747–757, 2007. View at Google Scholar · View at Scopus
  7. L.-H. Meng and J. Ding, “Salvicine, a novel topoisomerase II inhibitor, exerts its potent anticancer activity by ROS generation,” Acta Pharmacologica Sinica, vol. 28, no. 9, pp. 1460–1465, 2007. View at Publisher · View at Google Scholar · View at Scopus
  8. F. D. Liechti, F. Bachtold, D. Grandgirard, D. Leppert, and S. L. Leib, “The matrix metalloproteinase inhibitor RS-130830 attenuates brain injury in experimental pneumococcal meningitis,” Journal of Neuroinflammation, vol. 12, article 43, 2015. View at Publisher · View at Google Scholar
  9. A. Kamal, L. Thao, J. Sensintaffar et al., “A high-affinity conformation of Hsp90 confers tumour selectivity on Hsp90 inhibitors,” Nature, vol. 425, no. 6956, pp. 407–410, 2003. View at Publisher · View at Google Scholar · View at Scopus
  10. M. N. Islam, Y. Q. Song, and M. N. Iskander, “Investigation of structural requirements of anticancer activity at the paclitaxel/tubulin binding site using CoMFA and CoMSIA,” Journal of Molecular Graphics & Modelling, vol. 21, no. 4, pp. 263–272, 2003. View at Publisher · View at Google Scholar · View at Scopus
  11. M. L. Gupta Jr., C. J. Bode, G. I. Georg, and R. H. Himes, “Understanding tubulin-Taxol interactions: mutations that impart Taxol binding to yeast tubulin,” Proceedings of the National Academy of Sciences of the United States of America, vol. 100, no. 11, pp. 6394–6397, 2003. View at Publisher · View at Google Scholar · View at Scopus
  12. W. D. Jarvis and S. Grant, “Protein kinase C targeting in antineoplastic treatment strategies,” Investigational New Drugs, vol. 17, no. 3, pp. 227–240, 1999. View at Publisher · View at Google Scholar · View at Scopus
  13. R. T. Pillich, G. Scarsella, G. Galati et al., “The diimide drug PIPER has a cytotoxic dose-dependent effect in vitro and inhibits telomere elongation in HELA cells,” Anticancer Research, vol. 25, no. 5, pp. 3341–3346, 2005. View at Google Scholar · View at Scopus
  14. B. Das and G. Satyalakshmi, “Natural products based anticancer agents,” Mini-Reviews in Organic Chemistry, vol. 9, no. 2, pp. 169–177, 2012. View at Publisher · View at Google Scholar · View at Scopus
  15. N. K. Prasad, V. Kanakaveti, S. Eadlapalli, R. Vadde, A. P. Meetei, and V. Vindal, “Ligand-based pharmacophore modeling and virtual screening of RAD9 inhibitors,” Journal of Chemistry, vol. 2013, Article ID 679459, 7 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus
  16. S. L. Man, W. Y. Gao, C. L. Wei, and C. X. Liu, “Anticancer drugs from traditional toxic Chinese medicines,” Phytotherapy Research, vol. 26, no. 10, pp. 1449–1465, 2012. View at Publisher · View at Google Scholar · View at Scopus
  17. J. Lu, G. Li, J. Huang et al., “Lathyrane-type diterpenoids from the seeds of Euphorbia lathyris,” Phytochemistry, vol. 104, pp. 79–88, 2014. View at Publisher · View at Google Scholar · View at Scopus
  18. J. Hohmann, J. Molnár, D. Rédei et al., “Discovery and biological evaluation of a new family of potent modulators of multidrug resistance: reversal of multidrug resistance of mouse lymphoma cells by new natural jatrophane diterpenoids isolated from Euphorbia species,” Journal of Medicinal Chemistry, vol. 45, no. 12, pp. 2425–2431, 2002. View at Publisher · View at Google Scholar · View at Scopus
  19. D. L. Lu, Y. Q. Liu, and H. A. Aisa, “Jatrophane diterpenoid esters from Euphorbia sororia serving as multidrug resistance reversal agents,” Fitoterapia, vol. 92, pp. 244–251, 2014. View at Publisher · View at Google Scholar · View at Scopus
  20. A. Vasas, D. Rédei, D. Csupor, J. Molnár, and J. Hohmann, “Diterpenes from European Euphorbia species serving as prototypes for natural-product-based drug discovery,” European Journal of Organic Chemistry, no. 27, pp. 5115–5130, 2012. View at Publisher · View at Google Scholar · View at Scopus
  21. A. R. Jassbi, “Chemistry and biological activity of secondary metabolites in Euphorbia from Iran,” Phytochemistry, vol. 67, no. 18, pp. 1977–1984, 2006. View at Publisher · View at Google Scholar · View at Scopus
  22. W. Jiao, W. Dong, Z. Li, M. Deng, and R. Lu, “Lathyrane diterpenes from Euphorbia lathyris as modulators of multidrug resistance and their crystal structures,” Bioorganic & Medicinal Chemistry, vol. 17, no. 13, pp. 4786–4792, 2009. View at Publisher · View at Google Scholar · View at Scopus
  23. N. Duarte and M.-J. U. Ferreira, “Lagaspholones A and B: two new jatropholane-type diterpenes from Euphorbia lagascae,” Organic Letters, vol. 9, no. 3, pp. 489–492, 2007. View at Publisher · View at Google Scholar · View at Scopus
  24. N. Duarte, A. Varga, G. Cherepnev, R. Radics, J. Molnár, and M.-J. U. Ferreira, “Apoptosis induction and modulation of P-glycoprotein mediated multidrug resistance by new macrocyclic lathyrane-type diterpenoids,” Bioorganic & Medicinal Chemistry, vol. 15, no. 1, pp. 546–554, 2007. View at Publisher · View at Google Scholar · View at Scopus
  25. Z.-Q. Lu, S.-H. Guan, X.-N. Li et al., “Cytotoxic diterpenoids from Euphorbia helioscopia,” Journal of Natural Products, vol. 71, no. 5, pp. 873–876, 2008. View at Publisher · View at Google Scholar · View at Scopus
  26. C. R. Groom and F. H. Allen, “The Cambridge structural database in retrospect and prospect,” Angewandte Chemie—International Edition, vol. 53, no. 3, pp. 662–671, 2014. View at Publisher · View at Google Scholar · View at Scopus
  27. M. C. Hutter, “Graph-based similarity concepts in virtual screening,” Future Medicinal Chemistry, vol. 3, no. 4, pp. 485–501, 2011. View at Publisher · View at Google Scholar · View at Scopus
  28. C. Q. Cai, J. Y. Gong, X. F. Liu, D. Q. Gao, and H. L. Li, “Molecular similarity: methods and performance,” Chinese Journal of Chemistry, vol. 31, no. 9, pp. 1123–1132, 2013. View at Publisher · View at Google Scholar · View at Scopus
  29. D. A. Evans, “History of the Harvard ChemDraw project,” Angewandte Chemie International Edition, vol. 53, no. 42, pp. 11140–11145, 2014. View at Publisher · View at Google Scholar · View at Scopus
  30. J. Wang, P. Cieplak, and P. A. Kollman, “How well does a restrained electrostatic potential (RESP) model perform in calculating conformational energies of organic and biological molecules?” Journal of Computational Chemistry, vol. 21, no. 12, pp. 1049–1074, 2000. View at Publisher · View at Google Scholar · View at Scopus
  31. M. J. Vainio, J. S. Puranen, and M. S. Johnson, “ShaEP: molecular overlay based on shape and electrostatic potential,” Journal of Chemical Information and Modeling, vol. 49, no. 2, pp. 492–502, 2009. View at Publisher · View at Google Scholar · View at Scopus
  32. J. Löwe, H. Li, K. H. Downing, and E. Nogales, “Refined structure of αβ-tubulin at 3.5 Å resolution,” Journal of Molecular Biology, vol. 313, no. 5, pp. 1045–1057, 2001. View at Publisher · View at Google Scholar · View at Scopus
  33. A. V. Knyazev and I. Lashuk, “Steepest descent and conjugate gradient methods with variable preconditioning,” SIAM Journal on Matrix Analysis and Applications, vol. 29, no. 4, pp. 1267–1280, 2007. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  34. G. M. Morris, H. Ruth, W. Lindstrom et al., “Software news and updates AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility,” Journal of Computational Chemistry, vol. 30, no. 16, pp. 2785–2791, 2009. View at Publisher · View at Google Scholar · View at Scopus
  35. G. M. Morris, D. S. Goodsell, R. S. Halliday et al., “Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function,” Journal of Computational Chemistry, vol. 19, no. 14, pp. 1639–1662, 1998. View at Publisher · View at Google Scholar · View at Scopus
  36. J.-P. Hu, H.-Q. He, D.-Y. Tang et al., “Study on the interactions between diketo-acid inhibitors and prototype foamy virus integrase-DNA complex via molecular docking and comparative molecular dynamics simulation methods,” Journal of Biomolecular Structure and Dynamics, vol. 31, no. 7, pp. 734–747, 2013. View at Publisher · View at Google Scholar · View at Scopus
  37. F. Wang, H. Wan, J.-P. Hu, and S. Chang, “Molecular dynamics simulations of wild type and mutants of botulinum neurotoxin A complexed with synaptic vesicle protein 2C,” Molecular BioSystems, vol. 11, no. 1, pp. 223–231, 2015. View at Publisher · View at Google Scholar · View at Scopus
  38. H. Wan, J.-P. Hu, K.-S. Li, X.-H. Tian, and S. Chang, “Molecular dynamics simulations of DNA-free and DNA-bound TAL effectors,” PLoS ONE, vol. 8, no. 10, Article ID e76045, 2013. View at Publisher · View at Google Scholar · View at Scopus
  39. A. Manivannan, P. Soundararajan, Y. G. Park, S. Sakkiah, and B. R. Jeong, “Binding mode investigation of polyphenols from Scrophularia targeting human aldose reductase using molecular docking and molecular dynamics simulations,” Journal of Chemistry, vol. 2015, Article ID 434256, 12 pages, 2015. View at Publisher · View at Google Scholar
  40. E. F. F. da Cunha, J. E. Resende, T. C. C. Franca et al., “Molecular modeling studies of piperidine derivatives as new acetylcholinesterase inhibitors against neurodegenerative diseases,” Journal of Chemistry, vol. 2013, Article ID 278742, 7 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus
  41. D. A. Case, T. E. Cheatham III, T. Darden et al., “The Amber biomolecular simulation programs,” Journal of Computational Chemistry, vol. 26, no. 16, pp. 1668–1688, 2005. View at Publisher · View at Google Scholar · View at Scopus
  42. R. Salomon-Ferrer, D. A. Case, and R. C. Walker, “An overview of the Amber biomolecular simulation package,” Wiley Interdisciplinary Reviews: Computational Molecular Science, vol. 3, no. 2, pp. 198–210, 2013. View at Publisher · View at Google Scholar · View at Scopus
  43. J. W. Ponder, D. A. Case, and D. Valerie, “Force fields for protein simulation,” in Advances in Protein Chemistry, pp. 27–85, Academic Press, 2003. View at Google Scholar
  44. W. D. Cornell, P. Cieplak, C. I. Bayly et al., “A second generation force field for the simulation of proteins, nucleic acids, and organic molecules,” Journal of the American Chemical Society, vol. 117, no. 19, pp. 5179–5197, 1995. View at Publisher · View at Google Scholar · View at Scopus
  45. J.-P. Ryckaert, G. Ciccotti, and H. J. C. Berendsen, “Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes,” Journal of Computational Physics, vol. 23, no. 3, pp. 327–341, 1977. View at Publisher · View at Google Scholar · View at Scopus
  46. W. Humphrey, A. Dalke, and K. Schulten, “VMD: visual molecular dynamics,” Journal of Molecular Graphics, vol. 14, no. 1, pp. 33–38, 1996. View at Publisher · View at Google Scholar · View at Scopus
  47. P. A. Kollman, I. Massova, C. Reyes et al., “Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models,” Accounts of Chemical Research, vol. 33, no. 12, pp. 889–897, 2000. View at Publisher · View at Google Scholar · View at Scopus
  48. W. Wang, O. Donini, C. M. Reyes, and P. A. Kollman, “Biomolecular simulations: recent developments in force fields, simulations of enzyme catalysis, protein-ligand, protein-protein, and protein-nucleic acid noncovalent interactions,” Annual Review of Biophysics and Biomolecular Structure, vol. 30, no. 1, pp. 211–243, 2001. View at Publisher · View at Google Scholar · View at Scopus
  49. S. Genheden, O. Kuhn, P. Mikulskis, D. Hoffmann, and U. Ryde, “The normal-mode entropy in the MM/GBSA method: effect of system truncation, buffer region, and dielectric constant,” Journal of Chemical Information and Modeling, vol. 52, no. 8, pp. 2079–2088, 2012. View at Publisher · View at Google Scholar · View at Scopus
  50. D. Bashford and D. A. Case, “Generalized born models of macromolecular solvation effects,” Annual Review of Physical Chemistry, vol. 51, no. 1, pp. 129–152, 2000. View at Publisher · View at Google Scholar · View at Scopus
  51. T. Simonson, “Macromolecular electrostatics: continuum models and their growing pains,” Current Opinion in Structural Biology, vol. 11, no. 2, pp. 243–252, 2001. View at Publisher · View at Google Scholar · View at Scopus
  52. V. Tsui and D. A. Case, “Theory and applications of the generalized born solvation model in macromolecular simulations,” Biopolymers, vol. 56, no. 4, pp. 275–291, 2000. View at Publisher · View at Google Scholar · View at Scopus
  53. D. Sitkoff, K. A. Sharp, and B. Honig, “Accurate calculation of hydration free energies using macroscopic solvent models,” The Journal of Physical Chemistry, vol. 98, no. 7, pp. 1978–1988, 1994. View at Publisher · View at Google Scholar · View at Scopus
  54. W.-H. Liu, D. He, and G.-X. Xu, “Current status of novel anti-tumor targets and their targeting drugs,” Progress in Pharmaceutical Sciences, vol. 31, no. 12, pp. 535–542, 2007. View at Google Scholar
  55. M. C. Wani and S. B. Horwitz, “Nature as a remarkable chemist: a personal story of the discovery and development of Taxol,” Anti-Cancer Drugs, vol. 25, no. 5, pp. 482–487, 2014. View at Publisher · View at Google Scholar · View at Scopus
  56. X. Q. Wang, L. Y. Pan, N. Mao, L. F. Sun, X. J. Qin, and J. Yin, “Cell-cycle synchronization reverses Taxol resistance of human ovarian cancer cell lines,” Cancer Cell International, vol. 13, article 77, 2013. View at Publisher · View at Google Scholar · View at Scopus
  57. Z.-Y. Ni, Y. Li, Y.-F. Wang, S.-M. Wang, M. Dong, and Q.-W. Shi, “Cancer-fighting molecules-Taxol and its analogs,” Current Organic Chemistry, vol. 16, no. 17, pp. 2038–2052, 2012. View at Publisher · View at Google Scholar · View at Scopus
  58. A. Khaleghian, G. H. Riazi, M. Ghafari et al., “Effect of inganen anticancer properties on microtobule organization,” Pakistan Journal of Pharmaceutical Sciences, vol. 23, no. 3, pp. 273–278, 2010. View at Google Scholar · View at Scopus
  59. A. Miglietta, L. Gabriel, G. Appendino, and C. Bocca, “Biological properties of jatrophane polyesters, new microtubule-interacting agents,” Cancer Chemotherapy and Pharmacology, vol. 51, no. 1, pp. 67–74, 2003. View at Publisher · View at Google Scholar · View at Scopus
  60. J. P. Snyder, J. H. Nettles, B. Cornett, K. H. Downing, and E. Nogales, “The binding conformation of Taxol in β-tubulin: a model based on electron crystallographic density,” Proceedings of the National Academy of Sciences of the United States of America, vol. 98, no. 9, pp. 5312–5316, 2001. View at Publisher · View at Google Scholar · View at Scopus
  61. J. H. Nettles, H. L. Li, B. Cornett, J. M. Krahn, J. P. Snyder, and K. H. Downing, “The binding mode of epothilone A on alpha,beta-tubulin by electron crystallography,” Science, vol. 305, no. 5685, pp. 866–869, 2004. View at Publisher · View at Google Scholar · View at Scopus
  62. H. Xiao, P. Verdier-Pinard, N. Fernandez-Fuentes et al., “Insights into the mechanism of microtubule stabilization by Taxol,” Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 27, pp. 10166–10173, 2006. View at Publisher · View at Google Scholar · View at Scopus
  63. Y.-W. Li, Y.-J. Zhou, J. Zhu et al., “Property analysis of taxol-binding site in beta-tubulin,” Chemical Journal of Chinese Universities-Chinese, vol. 27, no. 11, pp. 2084–2087, 2006. View at Google Scholar
  64. J. Hu, M. Liu, D. Tang, and S. Chang, “Substrate recognition and motion mode analyses of PFV integrase in complex with viral DNA via coarse-grained models,” PLoS ONE, vol. 8, no. 1, Article ID e54929, 2013. View at Publisher · View at Google Scholar · View at Scopus
  65. J.-P. Hu, W. Liu, D.-Y. Tang, Y.-Q. Zhang, and S. Chang, “Study on the binding mode and mobility of HIV-1 integrase with L708, 906 inhibitor,” Progress in Biochemistry and Biophysics, vol. 38, no. 4, pp. 338–346, 2011. View at Publisher · View at Google Scholar · View at Scopus
  66. C. Elie-Caille, F. Severin, J. Helenius, J. Howard, D. J. Muller, and A. A. Hyman, “Straight GDP-tubulin protofilaments form in the presence of taxol,” Current Biology, vol. 17, no. 20, pp. 1765–1770, 2007. View at Publisher · View at Google Scholar · View at Scopus
  67. A. Mitra and D. Sept, “Taxol allosterically alters the dynamics of the tubulin dimer and increases the flexibility of microtubules,” Biophysical Journal, vol. 95, no. 7, pp. 3252–3258, 2008. View at Publisher · View at Google Scholar · View at Scopus