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Internet Electronic Journal of Molecular Design - IEJMD, ISSN 1538-6414, CODEN IEJMAT
| ABSTRACT - Internet Electron. J. Mol. Des. August 2008, Volume 7, Number 8, 161-185 |
2D-QSAR Autocorrelation Study on Selective COX-2 Inhibitors
Safia Taïri-Kellou, Souhila Bouaziz-Terrachet, Boubekeur Maouche, and Gilles Moreau
Internet Electron. J. Mol. Des. 2008, 7, 161-185
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Abstract:
A database of 185 COX-2 inhibitors including traditional NSAIDs was used to
derive regression and classification models starting from the 2D autocorrelation
descriptors. For that, we have described an original application of autocorrelation
vectors for encoding the chemical information derived from 2D-structures. Thus,
a separate autocorrelation vector was computed for each of the following atomic
properties: Pauling electronegativity, van der Waals volume, indicator for
saturated/unsaturated, logP contribution, polar surface area, indicator for
hydrogen-bond donor, indicator for hydrogen-bond acceptor and partial charge,
and the resulting set was reduced into a smaller number of variables using PCA.
The robustness and predictive ability of the obtained models were evaluated by
selecting chemical classes similar to the training set with activities ranging from
low to high and the results of the models were compared. The data generated from
the present study should be useful for predictive purposes, as an in silico filter, to
screen large structural database for new potent COX-2 inhibitor.
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