Pharmacophore maps

DP Mamott, IG Dougall, P Meghani, Y-J Liu, DR Flower. Lead generation using pharmacophore mapping and three-dimensional database searching Application to muscarinic M3 receptor antagonists. J Med Chem 42 3210-3216, 1999. 

YC Martin, MG Bures, EA Danaher, I DeLazzer, I Lico, PA Pavlik. A fast new approach to pharmacophore mapping and its application to dopaminergic and benzodiazepine agonists. I Comput Aided Mol Des 7 83-102, 1993. 

Pharmacophore mapping (pharmacophore-based virtual screening) given the relative orientation of a few functional groups in space (a pharmacophore), ligand molecules that are able to fulfill the pharmacophore are searched for. 

For most of the classes, recent review articles can easily be found Molecular docking [6-10], Structural alignments [11, 12], Molecular similarity [13-15], Pharmacophore mapping [16-18]. 

Bures, M.G. Recent techniques and applications in pharmacophore mapping. In Practical Application of Computer-Aided Drug Design,... 

One example of this approach is illustrated in Fig. 1, which represents the interaction at the sulphonyl urea receptor associated with the Katp potassium channel and which is involved in the control of insulin release in the pancreas. This pharmacophore map was obtained by an analysis... 

Figure 6. Predicted pharmacophore map of the serotonin 5HT2a receptor overiaid with a 5HT2a antagonist.

The standard screening approach when several active molecules have been identified is pharmacophore mapping followed by 3D database searching. This approach assumes that the active molecules have a common mode of action and that features that are common to all of the molecules describe the pharmacophoric pattern responsible for the observed bioactivity. This is a powerful technique but one that may not be applicable to the structurally heterogeneous hits that characterize typical HTS experiments or sets of competitor compounds drawn from the public literature. In such cases, it is appropriate to consider approaches based on 2D similarity searching and we present here a comparison of approaches for combining the structural information that can be gleaned from a small set of reference structures. 

Sanchez-Pedregal, V. M., et al., The INPHARMA method protein-mediated interligand NOEs for pharmacophore mapping. Angew Chem Int Ed, 2005, 44, 4172-4175. 

Once a lead is found, we have to focus in our search of property space as rapidly as possible to understand structure-activity relationships and perhaps build pharmacophore maps. To do this, we need to design more compounds to explore ranges of properties centered around our lead. This explosion of compounds is a knowledge-gathering process which, when the compounds are tested, should increase the understanding of bioactivity. By application of the neighborhood principle to eliminate similar molecules, any molecules selected for synthesis will likely have several hundred or a thousand similar structures that are stored in a virtual library. These often represent an ideal starting point for lead follow-up. 

Figure 13.6 Pharmacophore mapping of high-affinity a1A binder mapped on to class II adrenergic a1A pharmacophore model.

But you get more. A map is a tool that relates objects to each other. These relations may be distances as they appear on a roadmap, it may be frequencies or densities on a web exploration map or it may be metabolism-emotion relationships in a brain map. Hence the pharmacophoric map can be used as a filter by matching the property vectors and a library of synthetic and/or virtual ligands, sorting out putative binders. 

Pharmacophore mapping, Computer-aided drug design... 

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