PREDICTIVE QSAR ANALYSIS OF FLAVONOID ANALOGUES AS ANTIPSORIATIC AGENTSAbstract
Objective: Newly designed antipsoriatic agents which are substituted series of analogues of flavonoids (kaempferol and quercetin) that belong to the subclass flavonols were subjected to (2D-QSAR) analysis using VLIFEMDS-QSARPro software with an intention to derive and understand the possible correlation of biological activity as dependent variable and other descriptors like molecular weight, XLogP values as independent variables. It can be concluded that the current study provides better insight for designing and chemical synthesis of more potent antipsoriatic agents. Methods: Several statistical regression expressions were obtained using variable selection method as simulated annealing coupled with various model building methods like partial least squares (PLS) Regression, multiple linear regression (MLR) etc. Results: For the analogues of both quercetin and kaempferol, a total of 9 QSAR models were generated, each using test set of 15 and training set of 45 similar compounds. The best QSAR model generated by PLS model building method for quercetin was model Q4 with correlation coefficient r2 of 0.9021 and significant cross validated correlation coefficient q2 of 0.5791.Similarly, the best QSAR model generated by MLR method, for kaempferol was model K2 with r2 of 0.687, significant q2 of 0.5676. Both model Q4 and K2, gave significant results and revealed that presence of SdOE-index, SdsCH count favours the biological activity of quercetin analogues whereas presence of SdssCE-index contributes positively towards biological activity of analogues of kaempferol. This study suggests that such descriptors will be helpful in designing more potent antipsoriatic agents.
P. K. Sharma and B. V. Vakil*
Guru Nanak Institute for Research and Development, G. N. Khalsa College, Mumbai, Maharashtra, India.
08 April, 2017
14 June, 2017
17 September, 2017
01 December, 2017