Skip to main content

Advertisement

SpringerLink
Log in

Quantitative structure–property relationship studies of gas-to-wet butyl acetate partition coefficient of some organic compounds using genetic algorithm and artificial neural network

  • Original Research
  • Published:
Structural Chemistry Aims and scope Submit manuscript

Abstract

A Quantitative Structure–Property Relationship (QSPR) study based on artificial neural network (ANN) was carried out for the prediction of the gas-to-wet butyl acetate partition coefficient of a set of 81 organic compounds of very different chemical nature. The genetic algorithm-partial least squares (GA-PLS) method was applied as a variable selection tool. A PLS method was used to select the best descriptors and the selected descriptors were used as input neurons in neural network model. These descriptors are: Randic index (order 2) (2χ), atomic charge weighted partial positively charged surface area (PPSA-3), difference between atomic charge weighted partial positive and negative surface areas (DPSA-3), minimum net atomic charge for a O atom (q min O) and hydrogen bonding donor ability of the molecule (HDSA1). The results obtained showed the ability of developed ANN for prediction of the gas-to-wet butyl acetate partition coefficients of various compounds. Also result reveals the superiority of the ANN over the PLS model.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Sato A, Nakajima T (1979) Toxicol Appl Pharmacol 47:41

    Article  CAS  Google Scholar 

  2. Gargas ML, Burgess RJ, Voisard DE, Cason GH, Andersen ME (1989) Toxicol Appl Pharmacol 98:87

    Article  CAS  Google Scholar 

  3. Lu W, Chen Y, Liu M, Chen X, Hu Z (2007) Chemosphere 69:469

    Article  CAS  Google Scholar 

  4. Toropov AA, Roy KJ (2004) Chem Inf Comput Sci 44:179

    CAS  Google Scholar 

  5. Katritzky AR, Kuanar M, Fara DC, Karelson M, Acree W E Jr (2004) Bioorg Med Chem 12:4735

    Article  CAS  Google Scholar 

  6. Luan F, Liu HT, Ma WP, Fan BT (2008) Ecotoxicol Environ Safe 71:731

    Article  CAS  Google Scholar 

  7. Chen J, Xue X, Schramm KW, Quan X, Yang F, Kettrup A (2002) Chemosphere 8:535

    Google Scholar 

  8. Zhang Q, Huang J, Yu G (2008) Prog Nat Sci 18:867

    Article  CAS  Google Scholar 

  9. Fatemi MH, Karimian FJ (2007) Colloid Interface Sci 314:665

    Article  CAS  Google Scholar 

  10. Vegas V, Zufiria PJ (2004) Neural Netw 17:233

    Article  Google Scholar 

  11. Schweitzer RC, Morris JB (1999) Anal Chem Acta 384:285

    Article  CAS  Google Scholar 

  12. Tong CS, Cheng KC (1999) Chemom Intell Lab Syst 49:135

    Article  CAS  Google Scholar 

  13. Lui F, Liang Y, Cao C (2006) Chemom Intell Lab Syst 81:120

    Article  Google Scholar 

  14. Golmohammadi H, Fatemi MH (2005) Electrophoresis 26:3438

    Article  CAS  Google Scholar 

  15. Baher E, Fatemi MH, Konoz E, Golmohammadi H (2007) Microchim Acta 158:117

    Article  CAS  Google Scholar 

  16. Konoz E, Golmohammadi H (2008) Anal Chim Acta 619:157

    Article  CAS  Google Scholar 

  17. Golmohammadi HJ (2009) Comput Chem 30:2455

    Article  CAS  Google Scholar 

  18. Dashtbozorgi Z, Golmohammadi H (2010) Eur J Med Chem 45:2182

    Article  CAS  Google Scholar 

  19. Golmohammadi H, Safdari M (2010) Microchem J 95:140

    Article  CAS  Google Scholar 

  20. Sprunger LM, Proctor A, Acree W E Jr, Abraham MH, Dakhamab NB (2008) Fluid Phase Equilib 270:30

    Article  CAS  Google Scholar 

  21. Katritzky AR, Lobanov VS, Karelson M (1994) Comprehensive descriptors for structural and statistical analysis. Version 1.1, Reference manual. University of Florida, Gainesville

  22. Katritzky AR, Lobabanov VS, Karelson M (1995) Chem Soc Rev 24:279

    Article  CAS  Google Scholar 

  23. Katritzky AR, Lobabanov VS, Karelson M (1997) Pure Appl Chem 69:245

    Article  CAS  Google Scholar 

  24. Autodesk Inc. (1995) Hyperchem, re. 4 for Windows. Autodesk Inc., Sansalito

  25. Stewart JJP (1990) Semiempirical molecular orbital program. QCPE 445 (1983), Version 6

  26. Leardi R, Gonzales AL (1998) Chemom Intell Lab Syst 41:195

    Article  CAS  Google Scholar 

  27. Goldberg DE (1989) Genetic algorithms in search. Optimization and machine learning. Addison-Wesley, New York

    Google Scholar 

  28. Kowalski B, Gerlach R, Joreskog KG, Wold H (eds) (1982) Systems under indirect observation. North Holland, Amsterdam

    Google Scholar 

  29. Yu R-Q (1992) Introduction to chemometrics. Human Education Publishing House, Changsha

    Google Scholar 

  30. Dayal BS, MacGregor JFJ (1997) Chemometrics 11:73

    Article  CAS  Google Scholar 

  31. Geladi P, Kowalski BR (1986) Anal Chim Acta 185:1

    Article  CAS  Google Scholar 

  32. Lorber A, Wangen L, Kowalsky BRJ (1987) Chemometrics 1:19

    Article  CAS  Google Scholar 

  33. Khayamian T, Ensafi AA, Hemmateenejad B (1999) Talanta 49:587

    Article  CAS  Google Scholar 

  34. Shamsipur M, Hemmateenejad B, Akhond M, Sharghi H (2001) Talanta 54:1113

    Article  CAS  Google Scholar 

  35. Hoskuldsson A (2001) Chemom Intell Lab Syst 55:23

    Article  CAS  Google Scholar 

  36. MATLAB 7.0. The Mathworks Inc., Natick. http://www.mathworks.com

  37. Bishop CM (1995) Neural networks for pattern recognition. Clarendon Press, Oxford

    Google Scholar 

  38. Rumelhart DE, Hinton GE, Williams RJ (1996) Learning internal representation by error propagation. Parallel distributed processing: explorations in the microstructure of cognition, vol 1. The MIT Press, Cambridge

  39. Blank TB, Brown ST (1993) Anal Chem 65:3081

    Article  CAS  Google Scholar 

  40. Jalali-Heravi M, Fatemi MHJ (2001) Chromatogr A 915:177

    Article  CAS  Google Scholar 

  41. Golbraikh A, Tropsha AJ (2002) Mol Graphics Model 20:269

    Article  CAS  Google Scholar 

  42. Roy PP, Roy K (2008) QSAR Comb Sci 27:302

    Article  CAS  Google Scholar 

  43. Maldonado AG, Doucet JP, Petitjean M, Fan BT (2006) Mol Divers 10:39

    Article  CAS  Google Scholar 

  44. Kier LB, Hall LH (1976) Molecular connectivity in chemistry and drug research. Academic Press, New York

    Google Scholar 

  45. Kier LB, Hall H (1986) Molecular connectivity in structure-activity analysis. Wiley, New York

    Google Scholar 

  46. El-Basil S, Randic M (1992) Adv Quant Chem 24:239

    Article  CAS  Google Scholar 

  47. Stankevich MI, Stankevich IV, Zefirov NS (1088) Russ Chem Rev 57:191

    Article  Google Scholar 

  48. Zefirov NS, Kirpichenok MA, Izmailov FF, Trofimov MI (1987) Dokl Akad Nauk SSSR 296:883

    CAS  Google Scholar 

  49. Kirpichenok MA, Zefirov NS (1987) Zh Org Khim 23:4

    Google Scholar 

  50. Stanton DT, Jurs PC (1990) Anal Chem 62:2323

    Article  CAS  Google Scholar 

  51. Stanton DT, Egolf LM, Jurs PC, Hicks MGJ (1992) Chem Inf Comput Sci 32:306

    CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Chemistry, Mazandaran University, Babolsar, Iran

    Hassan Golmohammadi

  2. Department of Chemistry, Science and Research Branch, Young Researchers Club, Islamic Azad University, Tehran, Iran

    Zahra Dashtbozorgi

Authors
  1. Hassan Golmohammadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zahra Dashtbozorgi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hassan Golmohammadi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Golmohammadi, H., Dashtbozorgi, Z. Quantitative structure–property relationship studies of gas-to-wet butyl acetate partition coefficient of some organic compounds using genetic algorithm and artificial neural network. Struct Chem 21, 1241–1252 (2010). https://doi.org/10.1007/s11224-010-9669-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11224-010-9669-8

Keywords

Search

Navigation