Pharmacophore mapping

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. 

Mapping Pharmacophores in Ligands. Relaxed MCS approach. A rigid alignment, based on clique detection and genetic algorithm. (141)... 

The essential feature of the AAA is a comparison of active and inactive molecules. A commonly accepted hypothesis to explain the lack of activity of inactive molecules that possess the pharmacophoric conformation is that their molecular volume, when presenting the pharmacophore, exceeds the receptor excluded volume. This additional volume apparently is filled by the receptor and is unavailable for ligand binding this volume is termed the receptor essential volume [3]. Following this approach, the density maps for each of the inactive compounds (in their pharm conformations superimposed with that of active compounds) were constructed the difference between the combined inactive compound density maps and the receptor excluded volume represents the receptor essential volume. These receptor-mapping techniques supplied detailed topographical data that allowed a steric model of the D[ receptor site to be proposed. 

DM Mottola, S Laiter, VJ Watts, A Tropsha, SW Wyrick, DE Nichols, P Mailman. Conformational analysis of d dopamine receptor agonists Pharmacophore assessment and receptor mapping. J Med Chem 39 285-296, 1996. 

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. 

These pharmacophore techniques are different in format from the traditional pharmacophore definitions. They can not be easily visualized and mapped to the molecular structures rather, they are encoded as keys or topological/topographical descriptors. Nonetheless, they capture the same idea as the classic pharmacophore concept. Furthermore, this formalism is quite useful in building quantitative predictive models that can be used to classify and predict biological activities. 

Another group has evaluated self-organizing maps [63] and shape/ pharmacophore models [64]. They developed a new method termed SQUIRREL to compare molecules in terms of both shape and pharmacophore points. Thus from a commercial library of 199,272 compounds, 1926 were selected based on self-organizing maps trained on peroxisome proliferator-activated receptor a (PPARa) "activity islands." The compounds were further evaluated with SQUIRREL and 7 out of 21 molecules selected were found to be active in PPARa. Furthermore, a new virtual screening technique (PhAST) was developed based on representation of molecules as text strings that describe their pharmacophores [65]. 

Figure 6.3 Common-feature pharmacophores ofala adrenergic receptor antagonists [16]. Onto each pharmacophore the reference has been mapped, (a) Class I pharmacophore model aligned to prazosin, (b) class II pharmacophore model aligned to compound 10.

Mapping of Pharmacophore Models into Receptor Site... 

Figure 6.6 Mapping of high-affinity ai binder onto class II adrenergic aiA pharmacophore model. All pharmacophoric points are mapped. The alignment suggests that removal of the chlorine substituent within the 4-phenyl piperidine will reduce the unfavorable side affinity on a1A.

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