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Journal of Chemistry
Volume 2013, Article ID 560415, 12 pages
http://dx.doi.org/10.1155/2013/560415
Research Article

Exploring QSAR for Antimalarial Activities and Drug Distribution within Blood of a Series of 4-Aminoquinoline Drugs Using Genetic-MLR

1Young Researchers Club, Hamedan Branch, Islamic Azad University, Hamedan 65181-15743, Iran
2Department of Environment, Hamedan Branch, Islamic Azad University, Hamedan 65181-15743, Iran
3Department of Clinical Sciences, Faculty of Veterinary Medicine, Karaj Branch, Islamic Azad University, Karaj 65181-15743, Iran

Received 28 November 2011; Revised 19 June 2012; Accepted 5 July 2012

Academic Editor: Georgia Melagraki

Copyright © 2013 Amir Najafi 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. World Health Organization, “World malaria report,” 2009, http://www.who.int/malaria/publications/atoz/9789241563901/en/index.html.
  2. A. R. Katritzky, O. V. Kulshyn, I. Stoyanova-Slavova et al., “Antimalarial activity: a QSAR modeling using CODESSA PRO software,” Bioorganic and Medicinal Chemistry, vol. 14, no. 7, pp. 2333–2357, 2006. View at Publisher · View at Google Scholar · View at Scopus
  3. R. García-Domenech, W. López-Peña, Y. Sanchez-Perdomo et al., “Application of molecular topology to the prediction of the antimalarial activity of a group of uracil-based acyclic and deoxyuridine compounds,” International Journal of Pharmaceutics, vol. 363, no. 1-2, pp. 78–84, 2008. View at Publisher · View at Google Scholar · View at Scopus
  4. H. Ojha, P. Gahlot, A. K. Tiwari, M. Pathak, and R. Kakkar, “Quantitative structure activity relationship study of 2,4,6-trisubstituted-s-triazine derivatives as antimalarial inhibitors of Plasmodium falciparum dihydrofolate reductase,” Chemical Biology and Drug Design, vol. 77, no. 1, pp. 57–62, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. P. K. Ojha and K. Roy, “Chemometric modeling, docking and in silico design of triazolopyrimidine-based dihydroorotate dehydrogenase inhibitors as antimalarials,” European Journal of Medicinal Chemistry, vol. 45, pp. 4645–4656, 2010. View at Publisher · View at Google Scholar
  6. P. K. Ojha and K. Roy, “Chemometric modelling of antimalarial activity of aryltriazolylhydroxamates,” Molecular Simulation, vol. 36, no. 12, pp. 939–952, 2010. View at Publisher · View at Google Scholar · View at Scopus
  7. P. Shah and M. I. Siddiqi, “3D-QSAR studies on triclosan derivatives as Plasmodium falciparum enoyl acyl carrier reductase inhibitors,” SAR and QSAR in Environmental Research, vol. 21, no. 5-6, pp. 527–545, 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. S. C. Basak, D. Mills, D. M. Hawkins, and A. K. Bhattacharjee, “Quantitative structure-activity relationship studies of antimalarial compounds from their calculated mathematical descriptors,” SAR and QSAR in Environmental Research, vol. 21, no. 1-2, pp. 103–125, 2010. View at Publisher · View at Google Scholar · View at Scopus
  9. K. Roy and P. K. Ojha, “Advances in quantitative structureactivity relationship models of antimalarials,” Expert Opinion on Drug Discovery, vol. 5, no. 8, pp. 751–778, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. K. Roy and P. P. Roy, “QSAR of cytochrome inhibitors,” Expert Opinion on Drug Metabolism and Toxicology, vol. 5, no. 10, pp. 1245–1266, 2009. View at Publisher · View at Google Scholar · View at Scopus
  11. W. Asawamahasakda, A. Benakis, and S. R. Meshnick, “The interaction of artemisinin with red cell membranes,” Journal of Laboratory and Clinical Medicine, vol. 123, no. 5, pp. 757–762, 1994. View at Google Scholar · View at Scopus
  12. R. J. Riley, D. F. McGinnity, and R. P. Austin, “A unified model for predicting human hepatic, metabolic clearance from in vitro intrinsic clearance data in hepatocytes and microsomes,” Drug Metabolism and Disposition, vol. 33, no. 9, pp. 1304–1311, 2005. View at Publisher · View at Google Scholar · View at Scopus
  13. P. Paixão, L. F. Gouveiaa, and J. A. G. Moraisa, “Prediction of drug distribution within blood,” European Journal of Pharmaceutical Sciences, vol. 36, pp. 544–554, 2009. View at Publisher · View at Google Scholar
  14. HyperChem. 7.0, Hypercube Incorporation, http://www.hyper.com.
  15. R. Todeschini, Milano Chemometrics and QSAR Group, http://www.talete.mi.it.
  16. SPSS, 16.0, SPSS Incorporation, http://www.spss.com.
  17. MATLAB, 7.0, MathWorks Incorporation, http://www.mathworks.com.
  18. S. Ray, B. Madrid, P. Catz et al., “Development of a new generation of 4-aminoquinoline antimalarial compounds using predictive pharmacokinetic and toxicology models,” Journal of Medicinal Chemistry, vol. 53, pp. 3685–3695, 2010. View at Publisher · View at Google Scholar
  19. P. B. Madrid, A. P. Liou, J. L. DeRisi, and R. K. Guy, “Incorporation of an intramolecular hydrogen-bonding motif in the side chain of 4-aminoquinolines enhances activity against drug-resistant P. falciparum,” Journal of Medicinal Chemistry, vol. 49, no. 15, pp. 4535–4543, 2006. View at Publisher · View at Google Scholar · View at Scopus
  20. P. B. Madrid, J. Sherrill, A. P. Liou, J. L. Weisman, J. L. DeRisi, and R. K. Guy, “Synthesis of ring-substituted 4-aminoquinolines and evaluation of their antimalarial activities,” Bioorganic and Medicinal Chemistry Letters, vol. 15, no. 4, pp. 1015–1018, 2005. View at Publisher · View at Google Scholar · View at Scopus
  21. R. Todeschini and V. Consonni, Handbook of Molecular Descriptors, Wiley- VCH, London, UK, 2000.
  22. R. B. Darlington, Regression and Linear Models, McGraw-Hill, New York, NY, USA, 1990.
  23. A. Najafi and S. S. Ardakani, “2D autocorrelation modelling of the anti-HIV HEPT analogues using multiple linear regression approaches,” Molecular Simulation, vol. 37, no. 1, pp. 72–83, 2011. View at Publisher · View at Google Scholar
  24. QSAR Modeling, 2010, Theoretical and Applied Chemometrics Laboratory, State University of Campinas, Campinas, Brazil, http://lqta.iqm.unicamp.br.
  25. A. Najafi, S. S. Ardakani, and M. Marjani, “Quantitative structure-activity relationship analysis of the anticonvulsant activity of some benzylacetamides based on genetic algorithm-based multiple linear regression,” Tropical Journal of Pharmaceutical Research, vol. 10, no. 4, p. 483, 2011. View at Publisher · View at Google Scholar
  26. R. Ghavami, A. Najafi, M. Sajadi, and F. Djannaty, “Genetic algorithm as a variable selection procedure for the simulation of 13C nuclear magnetic resonance spectra of flavonoid derivatives using multiple linear regression,” Journal of Molecular Graphics and Modelling, vol. 27, no. 2, pp. 105–115, 2008. View at Publisher · View at Google Scholar · View at Scopus
  27. K. Baumann and N. Stiefl, “Validation tools for variable subset regression,” Journal of Computer-Aided Molecular Design, vol. 18, no. 7–9, pp. 549–562, 2004. View at Publisher · View at Google Scholar · View at Scopus
  28. L. Eriksson, J. Jaworska, A. P. Worth, M. T. D. Cronin, R. M. McDowell, and P. Gramatica, “Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs,” Environmental Health Perspectives, vol. 111, no. 10, pp. 1361–1375, 2003. View at Google Scholar · View at Scopus
  29. A. Tropsha, P. Gramatica, and V. K. Gombar, “The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models,” QSAR and Combinatorial Science, vol. 22, no. 1, pp. 69–77, 2003. View at Google Scholar · View at Scopus
  30. E. B. D. Melo and M. M. C. Ferreira, “Multivariate QSAR study of 4,5-dihydroxypyrimidine carboxamides as HIV-1 integrase inhibitors,” European Journal of Medicinal Chemistry, vol. 44, no. 9, pp. 3577–3583, 2009. View at Publisher · View at Google Scholar