| Background: Anti-inflammatory inhibitors of cyclooxygenase 2 (COX2) have been
shown to increase the risk of adverse cardiovascular events in clinical trials. The
studies showed that such adverse events could be due to COX2-induced suppression
of prostaglandin I2 (PGI2) synthesis. These adverse effects related to the degree of
COX2 selectivity of NSAIDs. Study of the selectivity index of COX1/COX2 is
important for development of the new NSAID drugs. Prediction methods of such
index have been interested by scientists. Methods: The selectivity index of a number
of 68 molecules from 8 different chemical groups was predicted using MLR and
SVM-RBF models. Calculated structural and physicochemical parameters, using the
energy optimized molecular structures were applied to develop the desired models.
The developed models were validated using LMO, external test set and Yrandomization methods. Results: Regression coefficient of developed MLR model
was 0.825 and 0.752 for training and test sets, while for SVM-RBF model it was 0.628
and 0.863 for training and test sets. The RMSE of the developed models were 0.08,
0.06, 0.29 and 0.16 respectively for train (MLR, SVM-RBF) and test (MLR, SVMRBF) datasets. Conclusion: The validation results showed the higher prediction
capability for SVM-RBF in comparison with MLR models. The selected descriptors
showed the contribution of electronic parameters in conjunction with size and shape
parameters in selectivity of studied compounds. |