Exploration of Important Sites of Antimalarial Endochins for Optimum Structural Modification Using Group-Based QSAR (G-QSAR) Modeling
The emergence of multidrug resistance of the currently available antimalarial drugs has led to the need of the discovery and development of new antimalarial compounds. In the present study, we have used a novel group based quantitative structure-activity relationship (G-QSAR) approach, which allows to establish a correlation of chemical group variation at different molecular sites of interest with the biological activity, using a series of 53 antimalarial endochin analogs. In our previous work, we developed QSAR models for this data set using different chemometric tools and tried to emphasize on importance of descriptor thinning and noise reduction prior to feature selection step. In the present paper, we have tried to select optimal subset of variables using a new strategy for the development of robust G-QSAR models. Starting with an initial pool of 6395 descriptors, we have finally used 51 descriptors for model development using genetic methods. The best model showed encouraging values for internal (Q(2)=0.806,  =0.728 and Lambda r(m)((LOO))(2) =0.071), external (R-pred(2)=0.793,   =0.729 and Lambda r(m)((test))(2) =0.064) and overall (  =0.725 and Delta r(m)((overall))(2)=0.067) validation parameters. The G-QSAR models developed here from the reduced pool of descriptors were found to be statistically more acceptable than the previously reported models. According to the best model, modification of the fragments based on their interactions with each other at R-1, R-2, R-5 and R-6 positions of the parent moiety are essential for optimum antimalarial activity.
antimalarials endochin qsar g-qsar gfa g/pls tm-90-c2b