Abstract

Historically, the pharmacophore concept was formulated in 1909 by the German physician and Nobel prize laureate Paul Ehrlich. According to the International Union of Pure and Applied Chemistry (IUPAC), a pharmacophore is defined as “an ensemble of steric and electronic features that is necessary to ensure the optimal supramolecular interactions with a specific biological target and to trigger (or block) its biological response”. Starting from the cocrystal structure of a non-covalent protein–ligand complex (e.g. Figure 1), pharmacophore perception involves the extraction of the key molecular features of the bioactive ligand at the protein–ligand contact interface into a single model. These pharmacophoric features mainly include: H-bond acceptor (HACC or A), H-bond donor (HDON or D), lipophilic group (LIPO or H), negative center (NEGC or N), positive center (POSC or P), and aromatic ring (AROM or R) moieties. Moreover, receptor-based excluded spheres (EXCL) can be added in order to mimic spatial constraints of the binding pocket (Figure 2). Once a pharmacophore model has been generated, a query can be performed either in a forward manner, using several ligands to search for novel putative hits of a given target, or in a reverse manner, by screening a single ligand against multiple pharmacophore models in search of putative protein targets.

About This Material

This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.

Questions this will address

• What is a pharmacophore model?
• How can I perform protein target prediction with a multi-step workflow or the one-step Zauberkugel workflow?

Learning Objectives

• Create an SMILES file of a bioactive ligand.
• Screen the query ligand against a pharmacophore library.
• Analyze the results of the protein target prediction.