Various computational tools and molecular modeling platforms are known to support medicinal chemists in understanding bioactivities, predicting binding events and rationally designing drug molecules. Among them, the pharmacophore approach is an accurate and minimal 3D-abstraction of chemical structures and intermolecular interactions.

Pharmacophore models are usually derived from a group of molecules in absence of structural information on their biological targets (ligand-based approach) or from a ligand-target complex (structure-based approach). However, only a limited amount of solutions exists to model comprehensive pharmacophores using the information of a particular target structure without knowledge of any binding ligand. In the presented work, T2F-Pharm, a fully automated tool for Truly Target-Focused Pharmacophore modeling will be introduced. Using a grid-based approach, this method samples the protein cavity, filters the grid points by energy level and clusters them into low energy hot spots. Subsequently, key features in the pocket required for optimal interaction in a 3D-pharmacophore model are derived.

T2F-Pharm represents a valuable instrument for drug discovery to investigate protein surfaces in absence of known binding partners, e.g. in cases of rather unexplored binding sites including allosteric pockets.