• Dual PPAR-α/γ ligands;
  • 2-D QSAR;
  • Multivariate data analysis;
  • PLS models;
  • Drug-like descriptors;
  • MOLCONN-Z descriptors;
  • Molecular simulation


In the present study 2D-QSAR analysis was combined with information on crystallographic data and molecular modeling, in order to investigate dual PPAR-α/γ activity for a data set of 71 compounds, compiled from literature. Using Multivariate Data Analysis, satisfactory PLS models were generated for each receptor subtype separately. The models were based on simple and easily interpretable drug-like and constitutional descriptors, while the inclusion of MOLCONN-Z descriptors in the initial pool of variables had no considerable impact in model predictivity. By simultaneous analysis of both types of activity, a consensus PLS model for dual PPAR-α/γ activity could be derived, displaying the molecular features, which may lead to a balanced activity. All models were validated by permutation tests, by dividing the data set into training and test sets, as well as by external validation using a blind test set. Detailed inspection of PPAR-α and PPAR-γ crystal structures and molecular simulation supported the differentiation of most important descriptors in the separate PLS models, e.g. the higher impact of lipophilicity and bulk descriptors in PPAR-α and PPAR-γ activity respectively, as well as the effect of specific structural descriptors. Molecular simulation provided also explanation for the behavior of certain outliers in the PLS models.