Deriving and Using Three-dimensional Pharmacophores

There are two problems to consider when calculating 3D pharmacophores First, unless the molecules are all completely rigid, one must take account of their conformational properties. The second problem is to determine which combinations of pharmacophoric groups are common to the molecules and can be positioned in a similar orientation in space. More than one pharmacophore may be possible indeed, some algorithms can generate hundreds of possible pharmacophores, which must then be evaluated to determine which best fits the data. It is important to realise that all of these approaches to finding 3D pharmacophores assume that all of the molecules bind in a common manner to the macromolecule. 

Fig 12 9 A distance map indicates the distances available to specified groups. As more molecules are considered, fe permitted regions get smaller 

2 Ensemble Distance Geometry, Ensemble Molecular Dynamics and Genetic Algorithms 

A variant of distance geometry called ensemble distance geometry [Sheridan et al. 1986] can be used to simultaneously derive a set of conformations with a previously defined set of pharmacophoric groups overlaid. Ensemble distance geometry uses the same steps as 

Fig 12 10 Two ACE pharmacophores identified by the constrained systematic search [Dammkoehler et al 1989], 

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