3D-Quantitative Structure Activity Relationship: A Strategic Approach for In Silico Prediction of Anti-Candididal Action of 1,2,4- Triazole Derivatives

Abstract

The three dimensional quantitative structure activity relationships(3D-QSAR) of a series of previously synthesized 1-(1H-1,2,4-triazole-1-yl)-2-(2,4-difluorophenyl)-3-substituted-2-propanol analogs(TDFPP) as antifungal against candida albicans, were studied using kNN(K nearest neighbour) protocol. This was in order to explore the selectivity requirements for fungicidal activity against C. albicans among these congeners. Theoretical active conformers for these TDFPP were generated. The best kNN model(N=44, q2= 0.8650, r2= 0.86504) showed contribution of the steric and electrostatic fields. The models were also external validated using 6 compounds(test set) not included in the model generation process. The statistical parameters from model indicate that the data are well fitted and have predictive ability. Moreover, the resulting contours and isosurface maps provide useful guidance for designing highly active ligands. The model is not only able to predict the activity of new compounds but also explains the important region in the molecules in the quantitative manner. © 2011 IGJPS. All rights reserved.