An application of two MIFs-based tools (Volsurf+ and Pentacle) to binary QSAR: the case of a palinurin-related data set of non-ATP competitive glycogen synthase kinase 3β (GSK-3β) inhibitors.

VolSurf+ and GRIND descriptors extract the information present in MIFs calculated by GRID: the first are simpler to interpret and generally applied to ADME-Tox topics, whereas the latter are more sophisticated and thus more suited for pharmacodynamics events. Here we present a study which compares binary QSAR models obtained with VolSurf+ descriptors and GRIND for a data set of non-ATP competitive GSK-3β inhibitors chemically related to palinurin for which the biological activity is expressed in binary format. Results suggest not only that the simpler Volsurf+ descriptors are good enough to predict and chemically interpret the investigated phenomenon but also a bioactive conformation of palinurin which may guide future design of ATP non-competitive GSK-3 inhibitors.