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Quantitative Structure-Property Relationship for Predicting Surface Tension of Organic Compounds Using Associative Neural Networks
Corresponding Author(s) : P. Neelamegam
Asian Journal of Chemistry,
Vol. 25 No. 5 (2013): Vol 25 Issue 5
Abstract
This paper explains associative neural network based quantitative structure property relationship study for prediction of surface tension of organic compounds using molecular descriptors derived from molecular structures. A set of 116 organic compounds, which includes 48 alkanes, 31 alcohols, 20 amines, 14 alkenes and 3 aldehydes as data series are selected for the present study. Unsupervized forward selection strategy is used for descriptor selection from the large set of descriptors using E-DRAGON software and six descriptors are selected for model development for surface tension. Associative neural network method is used to construct the non-linear prediction model for surface tension. The selected descriptors are used as input data for training and testing the associative neural network. The predicted results are in good agreement with the experimental surface tension of organic compounds with squared correlation co-efficient (R2) of 0.98 for training and 0.932 for testing. The results are cross-validated by leave-one-out procedure. The model is suitable to a large variety of compounds, which predicts better than other models reported in previous studies.
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- A.W. Adamson, Physical Chemistry of Surfaces, Interscience Publishers, New York, edn 5 (1990).
- B.E. Poling, J.M. Prausnitz and J.P. O'Connell, The Properties of Gases and Liquids, McGraw-Hill, USA (2004).
- A.J. Quiemada, I.M. Marrucho, J.A.P. Coutinho and E.H. Stenby, Proceedings of the 15 th Symposium on Thermophysical Properties, Boulder (USA), June 22-27 (2003).
- H.Y. Erbil, Surface Chemistry of Solid and Liquid Interfaces, Oxford, Blackwell (2006).
- R. Katritzky, U. Maran, US Lobanov and M. Karelson, J. Chem. Inf. Comput. Sci., 40, 1 (2000).
- A.R. Katritzky, V.S. Lobanov and M. Karelson, Chem. Soc. Rev., 24, 279 (1995).
- A.R. Katritzky, M. Karelson and V.S. Lobanov, Pure. Appl. Chem., 69, 245 (1997).
- F. Ashrafi, R. Saadati and A.B. Amlashi, Afr. J. Pure Appl. Chem., 2, 116 (2008).
- R. Todeschini and V. Consonni, Handbook of Molecular Descriptors, Wiley-VCH Verlag, Weinheim (2000).
- P.X. Liu and W. King, Int. J. Mol. Sci. Rev., 10, 1978 (2009).
- J. Devillers, Neural Networks in QSAR Drug Design, Academic Press, London (1996).
- D.T. Stanton and P.C. Jurs, Anal. Chem., 62, 2323 (1990).
- G.W. Kaffman and P.C. Jurs, J. Chem. Inf. Comput. Sci., 41, 408 (2001).
- E.J. Delgado and G.A. Diaz, SAR and QSAR Environ. Res., 17, 483 (2006).
- E.-Dragon, 1.0 On-line software; Virtual Computational Chemistry Laboratory. http://146.107.217.178/lab/edragon/index.html.
- J.J. Jasper, J. Phys. Chem. Ref. Data, 1, 841 (1972).
- http://www.chemaxon.com/Marvin/Sketch/index.php
- D.C. Whitley and M.G. Ford, J. Chem. Inf. Comput. Sci., 40, 1160 (2000).
- T.E. Quantrille and Y.A. Liu, Artificial Intelligence in Chemical Engineering, Academic Press, New York (1992).
- I.V. Tetko, J. Chem. Inf. Comput. Sci., 42, 717 (2002).
- http://www.vcclab.org/asnn/
References
A.W. Adamson, Physical Chemistry of Surfaces, Interscience Publishers, New York, edn 5 (1990).
B.E. Poling, J.M. Prausnitz and J.P. O'Connell, The Properties of Gases and Liquids, McGraw-Hill, USA (2004).
A.J. Quiemada, I.M. Marrucho, J.A.P. Coutinho and E.H. Stenby, Proceedings of the 15 th Symposium on Thermophysical Properties, Boulder (USA), June 22-27 (2003).
H.Y. Erbil, Surface Chemistry of Solid and Liquid Interfaces, Oxford, Blackwell (2006).
R. Katritzky, U. Maran, US Lobanov and M. Karelson, J. Chem. Inf. Comput. Sci., 40, 1 (2000).
A.R. Katritzky, V.S. Lobanov and M. Karelson, Chem. Soc. Rev., 24, 279 (1995).
A.R. Katritzky, M. Karelson and V.S. Lobanov, Pure. Appl. Chem., 69, 245 (1997).
F. Ashrafi, R. Saadati and A.B. Amlashi, Afr. J. Pure Appl. Chem., 2, 116 (2008).
R. Todeschini and V. Consonni, Handbook of Molecular Descriptors, Wiley-VCH Verlag, Weinheim (2000).
P.X. Liu and W. King, Int. J. Mol. Sci. Rev., 10, 1978 (2009).
J. Devillers, Neural Networks in QSAR Drug Design, Academic Press, London (1996).
D.T. Stanton and P.C. Jurs, Anal. Chem., 62, 2323 (1990).
G.W. Kaffman and P.C. Jurs, J. Chem. Inf. Comput. Sci., 41, 408 (2001).
E.J. Delgado and G.A. Diaz, SAR and QSAR Environ. Res., 17, 483 (2006).
E.-Dragon, 1.0 On-line software; Virtual Computational Chemistry Laboratory. http://146.107.217.178/lab/edragon/index.html.
J.J. Jasper, J. Phys. Chem. Ref. Data, 1, 841 (1972).
http://www.chemaxon.com/Marvin/Sketch/index.php
D.C. Whitley and M.G. Ford, J. Chem. Inf. Comput. Sci., 40, 1160 (2000).
T.E. Quantrille and Y.A. Liu, Artificial Intelligence in Chemical Engineering, Academic Press, New York (1992).
I.V. Tetko, J. Chem. Inf. Comput. Sci., 42, 717 (2002).