Siavash Tatardar
1, Abolghasem Jouyban
2, Somaieh Soltani
2*, Mostafa Zakariazadeh
31 Student Research Committee , Tabriz University of medical sciences, Tabriz, Iran
2 Drug A pplied R esearch C enter and Pharmacy F aculty, Tabriz University of medical sciences, Tabriz, Iran
3 Biothechnology Research Center , Tabriz University of medical sciences, Tabriz, Iran
Abstract
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 Y-randomization 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, SVM-RBF) 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.