Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Open Chemistry

formerly Central European Journal of Chemistry


IMPACT FACTOR 2017: 1.425
5-year IMPACT FACTOR: 1.511

CiteScore 2017: 1.45

SCImago Journal Rank (SJR) 2017: 0.349
Source Normalized Impact per Paper (SNIP) 2017: 0.812

ICV 2017: 165.27

Open Access
Online
ISSN
2391-5420
See all formats and pricing
More options …
Volume 7, Issue 3

Issues

Volume 13 (2015)

QSPR study for the prediction of half-wave potentials of benzoxazines by heuristic method and radial basis function neural network

Huitao Liu / Yingying Wen / Feng Luan / Yuan Gao / Xiuyong Li
Published Online: 2009-06-21 | DOI: https://doi.org/10.2478/s11532-009-0033-z

Abstract

The half-wave potential (E1/2) is an important electrochemical property of organic compounds. In this work, a quantitative structure-property relationship (QSPR) analysis has been conducted on the half-wave reduction potential (E1/2) of 40 substituted benzoxazines by means of both a heuristic method (HM) and a non-linear radial basis function neural network (RBFNN) modeling method. The statistical parameters provided by the HM model (R2 =0.946; F=152.576; RMSCV=0.0141) and the RBFNN model (R2=0.982; F=1034.171 and RMS =0.0209) indicated satisfactory stability and predictive ability. The obtained models showed that benzoxazines with larger Min valency of a S atom (MVSA), lower Relative number of H atom (RNHA) and Min n-n repulsion for a C-H bond (MnnRCHB) and Minimal Electrophilic Reactivity Index for a C atom (MERICA) can be more easily reduced. This QSPR approach can contribute to a better understanding of structural factors of the organic compounds that contribute to the E1/2, and can be useful in predicting the E1/2 of other compounds.

Keywords: Heuristic method; Radial basis function neural network (RBFNN); Quantitative structure-property relationship (QSPR); Half-wave potential; Benzoxazine

  • [1] B.B. Xia, W.P. Ma, B. Zheng, X.Y. Zhang, B.T. Fan, Eur. J. Med. Chem. 43, 1489 (2008) http://dx.doi.org/10.1016/j.ejmech.2007.09.004CrossrefGoogle Scholar

  • [2] J. Ghasemi, S. Saaidpour, J. Inclusion Phenom. Macrocyclic Chem. 60, 339 (2008) http://dx.doi.org/10.1007/s10847-007-9383-3CrossrefGoogle Scholar

  • [3] S.S. Godavarthy, R.L. Robinson, K.A.M. Gasem, Fluid Phase Equilib. 264, 122 (2008) http://dx.doi.org/10.1016/j.fluid.2007.11.003CrossrefGoogle Scholar

  • [4] A.R. Katritzky, I.B. Stoyanova-Slavova, D.A. Dobchev, M. Karelson, J. Mol. Graphics Modell. 26, 529 (2007) http://dx.doi.org/10.1016/j.jmgm.2007.03.006CrossrefGoogle Scholar

  • [5] B. Hemmateenejad, M. Shamsipur, Internet Electronic J. Mol. Des. 2, 1 (2003) Google Scholar

  • [6] M. Shamsipur, A. Siroueinejad, B. Hemmateenejad, A. Abbaspour, H. Sharghi, K. Alizadeh, S. Arshadi, J. Electroanal. Chem. 600, 345 (2007) http://dx.doi.org/10.1016/j.jelechem.2006.09.006CrossrefGoogle Scholar

  • [7] S. Yuan, M. Xiao, G. Zheng, M. Tian, X. Lu, SAR QSAR Environ. Res. 17, 473 (2006) http://dx.doi.org/10.1080/10629360600934044CrossrefGoogle Scholar

  • [8] S. Nikolic, A. Milicevic, N. Trinajstic, Croat. Chem. Acta 79, 155 (2006) Google Scholar

  • [9] M.H. Fatemi, M.R. Hadjmohammadi, K. Kamel, P. Biparva, Bull. Chem. Soc. Jpn. 80, 303 (2007) http://dx.doi.org/10.1246/bcsj.80.303CrossrefGoogle Scholar

  • [10] K. Nesmerak, I. Nemec, M. Sticha, K. Waisser, K. Palat, Electrochim. Acta 50, 1431 (2005) http://dx.doi.org/10.1016/j.electacta.2004.08.031CrossrefGoogle Scholar

  • [11] A. Toropov, K. Nesmerak, I. Ralka, K. Waisser, K. Palat, Comput. Biol. Chem. 30, 434 (2006) http://dx.doi.org/10.1016/j.compbiolchem.2006.09.003CrossrefGoogle Scholar

  • [12] HyperChem 4.0, Hypercube Inc., Gainesville, FL, 1994 Google Scholar

  • [13] HyperChem 6.01, Hypercube, Inc., 2000 Google Scholar

  • [14] M.J.S. Dewar, E.G. Zoebisch, E.F. Healy, J.J.P. Stewart, J. Am. Chem. Soc. 107, 3898 (1985) http://dx.doi.org/10.1021/ja00299a023CrossrefGoogle Scholar

  • [15] J.J.P. Stewart, MOPAC, v.6.0 Quantum Chemistry Program Exchange, Program 455 (Indiana University, Bloomington, IN, 1989) Google Scholar

  • [16] A.R. Katritzky, V.S. Lobanov, M. Karelson, CODESSA: Training Manual (University of Florida, Gainesville, FL, 1995) Google Scholar

  • [17] A.R. Katritzky, V.S. Lobanov, M. Karelson, CODESSA: Reference Manual (University of Florida, Gainesville, FL, 1994) Google Scholar

  • [18] S.C. Basak, B.D. Gute, A.T. Balaban, Croat. Chem. Acta, 77, 331 (2004) Google Scholar

  • [19] J.V. Turner, D.J. Cutler, I. Spence, D.J. Maddalena, J. Comput. Chem. Jpn. 24, 891 (2003) CrossrefGoogle Scholar

  • [20] F. Gharagheizi, Computational Materials Science 40, 159 (2007) http://dx.doi.org/10.1016/j.commatsci.2006.11.010CrossrefGoogle Scholar

  • [21] M. Oblak, M. Randic, T. Solmajer, J. Chem. Inf. Comput. Sci. 40, 994 (2000) CrossrefGoogle Scholar

  • [22] W.P. Ma, F. Luan, H.X. Zhang, X.Y. Zhang, M.C. Liu, Z.D. Hu, B.T. Fan, Analyst 131, 1254 (2006) http://dx.doi.org/10.1039/b605060cCrossrefGoogle Scholar

  • [23] X.J. Yao, A. Panaye, P. Doucet, R.S. Zhang, H.F. Chen, M.C. Liu, Z.D. Hu, B.T. Fan, J. Chem. Inf. Comput. Sci. 44, 1257 (2004) CrossrefGoogle Scholar

  • [24] Y.H. Xiang, M.C. Liu, X.Y. Zhang, R.S. Zhang, Z.D. Hu, B.T. Fan, D.J.P. Panaye, J. Chem. Inf. Comput. Sci. 42, 592 (2002) CrossrefGoogle Scholar

  • [25] M.J.L. Orr, Introduction to Radial Basis Function Networks (Centre for Cognitive Science, Edinburgh University, Scotland, 1996) http://www.anc.ed.ac.uk/~mjo/rbf.html (12/06/2001) Google Scholar

  • [26] M.J.L. Orr, MATLAB routines for subset selection and ridge regression in linear neural networks (Centre for Cognitive Science, Edinburgh University, Scotland, 1996) http://www.anc.ed.ac.uk/~mjo/rbf.html (12/06/2001) Google Scholar

  • [27] A.T. Balaban, S.C. Basak, A. Beteringhe, D. Mills, C.T. Supuran, Mol. Divers. 8, 401 (2004) http://dx.doi.org/10.1023/B:MODI.0000047516.97952.f4CrossrefGoogle Scholar

About the article

Published Online: 2009-06-21

Published in Print: 2009-09-01


Citation Information: Open Chemistry, Volume 7, Issue 3, Pages 439–445, ISSN (Online) 2391-5420, DOI: https://doi.org/10.2478/s11532-009-0033-z.

Export Citation

© 2009 Versita Warsaw. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

Citing Articles

Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.

Comments (0)

Please log in or register to comment.
Log in