3D-QSAR based pharmacophore modeling and virtual screening for identification of novel pteridine reductase inhibitors.

Pteridine reductase is a promising target for development of novel therapeutic agents against Trypanosomatid parasites. A 3D-QSAR pharmacophore hypothesis has been generated for a series of L. major pteridine reductase inhibitors using Catalyst/HypoGen algorithm for identification of the chemical features that are responsible for the inhibitory activity. Four pharmacophore features, namely: two H-bond donors (D), one Hydrophobic aromatic (H) and one Ring aromatic (R) have been identified as key features involved in inhibitor-PTR1 interaction. These features are able to predict the activity of external test set of pteridine reductase inhibitors with a correlation coefficient (r) of 0.80. Based on the analysis of the best hypotheses, some potent Pteridine reductase inhibitors were screened out and predicted with anti-PTR1 activity. It turned out that the newly identified inhibitory molecules are at least 300 fold more potent than the current crop of existing inhibitors. Overall the current SAR study is an effort for elucidating quantitative structure-activity relationship for the PTR1 inhibitors. The results from the combined 3D-QSAR modeling and molecular docking approach have led to the prediction of new potent inhibitory scaffolds.