QSAR Studies of Some Novel Triazines Inhibiting Dihydrofolate Reductase

In this paper the Multi-linear regression analysis has been applied for QSAR study. The relationship has been worked out between the Log 1/C values of a series of compounds and certain quantum chemical and energy descriptors. The QSAR studies of Triazines inhibiting dihydrofolate reductase based on quantum chemical and energy descriptors shows that among all the 28 QSAR models PA51 to PA 78, the number of good QSAR models is 08 whose regression coefficient is greater than 0.7. In all the best 08 QSAR models, heat of formation is common. It means the best descriptor to predict the activities are the heat of formation. Also, the predicted activity obtained by taking heat of formation as single descriptor possesses the good value of regression coefficient which is 0.738250.