A 3D QSAR study of monoamino oxidase-B inhibitors using the chemical function based pharmacophore generation approach

Abstract

A molecular modelling study was performed using the CATALYST software package on a dataset of 100 thiosemicarbazide and thiazole derivatives acting as MAO-B irreversible inhibitors in order to, (i) better elucidate the possible role of the ligand features which are significant for binding and (ii) generate chemical features based pharmacophore models which were subsequently used as 3D queries for database searching. Based on known MAO-B inhibitors, pharmacophore hypotheses were created in order to find similarities between the thiazoles and thiosemicarbazides and identify the key sub-structures most likely to be significant for high MAO-B inhibitory activity.