Pharmacophore topological

Schneider, G., Neidhart, W., Giller, T., and Schmidt, G. Scaffold-Hopping by topological pharmacophore search a contribution to virtual screening. Angeiv. Chemie. 1999, 111, 3068-3070. 

Schneider G, Neidhart W, Giller T, Schmid G. (1999) Scaffold-hopping by topological pharmacophore search A contribution to virtual screening. Angew. Chem. Int. Ed. Engl. 38 2894—2896. 

Key words ProSAR, combinatorial library design, topological pharmacophore, pharmacophore... 

The work of Schneider et al. [6] first focused on the scaffold-hopping ability of autocorrelation descriptors, in this case topological pharmacophores. The general description of the atoms with pharmacophore atom types in combination with the decomposition of molecules into atom pairs was shown to be especially successful in finding new molecules with significant different molecular scaffolds, maintaining the desired biological effect. 

An example may help to clarify this statement Figure 13.4 shows the 10 highest-ranking compounds that were retrieved from the COBRA database by a topological pharmacophore similarity search (CATS method, see below). The query structure was Haloperidol, a dopamine (D2) receptor antagonist. Not surprisingly classic variations of the query structure are found in ranks 1 and 2. These are not very... 

Figure 13.4 Results of a CATS similarity search. Similarity between the query structure (Haloperidol, a D2 antagonist upper left) and database compounds was defined in terms of a topological pharmacophore descriptor. The top 10 most-similar molecules found are shown.

Figure 13.12 A SOM-based pharmacophore road map. Different sets of ligands were projected onto a SOM that was generated by using the complete COBRA library. Black areas indicate the characteristic distributions of the compounds. Crosses indicate empty neurons in the map, i.e., areas of pharmacophore space that are not populated by the respective compound class. All molecules were encoded by a topological pharmacophore descriptor (CATS) [4], Note that each map forms a torus.

Pharmacophores are intrinsically three-dimensional - what, then, is topological pharmacophore supposed to mean This chapter highlights the key aspects of this topic along with some published studies. Its goal is to convey a general introduction to the main concepts and issues in 2D pharmacophore modeling, and was not conceived as an exhaustive literature review. This section briefly introduces key topics that are then detailed later on. 

The analogy between 3D and topological pharmacophore pattern descrip-... 

MTree models are per se not conceptually equivalent to topological pharmacophores , as the authors claim, but rather conceptually equivalent to the above-mentioned hypermolecules. They represent a fusion of nodes seen in training set compounds - some conserved in many molecules, other occurring less often. To generate a topological pharmacophore out of an MTree model, node weights should be introduced to account for the relative occurrence of each node within actives, by contrast to inactives - as pointed out by the authors in the perspectives section. 

Prior to a brief discussion of specific applications of topological pharmacophore fingerprints in similarity-based virtual screening, some general remarks can be made. 

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