Pharmacophores three-dimensional searching

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. 

Gund P. Three-dimensional pharmacophoric pattern searching. Prog Mol Subcell Biol 1977 5 117-43. 

Clark DE, Willett P, Kenny PW. Pharmacophoric pattern matching in files of three-dimensional chemical structures use of smoothed bounded-distance matrices for the representation and searching of conformationally-fiexible molecules. J Mol Graph 1992 10 194-204. 

Gund P. Three-dimensional pharmacophore pattern searching. In Hahn FE, editor, Progress in molecular and subcellular biology. Berlin Springer-Verlag, 1977. p.117-43. 

Varady J, Wu X, Fang X, Min J, Hu Z, Levant B, Wang S. Molecular modeling of the three-dimensional structure of dopamine 3 (D3) subtype receptor discovery of novel and potent D3 ligands through a hybrid pharmacophore-and structure-based database searching approach. / Med Chem 2003 46 4377-92. 

Kurogi, Y. and Guner, O.F. Pharmacophore modeling and three-dimensional database searching for dmg design using catalyst. Curr. 

Greenidge, P.A., Carlsson, B., Biadh, L.G., and Gillner, M. Pharmacophores incorporating numerous excluded volumes defined by x-ray crystallographic structure in three-dimensional database searching application to the thyroid hormone receptor./. Med. Chem. 1998, 41, 2503-2512. 

Van drie, J.H., Weininger, D., and Martin, Y.C. ALADDIN an integrated tool for computer-assisted molecular design and pharmacophore recognition from geometric, steric, and substructure searching of three-dimensional molecular structures./. Comput.-Aided Mol. Des. 1998, 3, 225-251. 

Quantitative Structure-Activity Relationship models are used increasingly in chemical data mining and combinatorial library design [5, 6]. For example, three-dimensional (3-D) stereoelectronic pharmacophore based on QSAR modeling was used recently to search the National Cancer Institute Repository of Small Molecules [7] to find new leads for inhibiting HIV type 1 reverse transcriptase at the nonnucleoside binding site [8]. A descriptor pharmacophore concept was introduced by us recently [9] on the basis of variable selection QSAR the descriptor pharmacophore is defined as a subset of... 

DISCO considers three-dimensional conformations of compounds not as coordinates but as sets of interpoint distances, an approach similar to a distance geometry conformational search. Points are calculated between the coordinates of heavy atoms labeled with interaction functions such as HBD, HBA or hydrophobes. One atom can carry more than one label. The atom types are considered as far as they determine which interaction type the respective atom would be engaged in. The points of the hypothetical locations of the interaction counterparts in the receptor macromolecule also participate in the distance matrix. These are calculated from the idealized projections of the lone pairs of participating heavy atoms or H-bond forming hydrogens. The hydrophobic points are handled in a way that the hydrophobic matches are limited to, e.g., only one atom in a hydrophobic chain and there is a differentiation between aliphatic and aromatic hydrophobes. A minimum constraint on pharmacophore point of a certain type can be set, e.g. if a certain feature is known to be required for activity [53, 54]. 

Another issue that should be addressed briefly is the relationship between size and resolution of a conformational model particularly in terms of coverage of the low-energy regions of the accessible conformational space. The coverage should at any rate be consistent with the precision of the application which uses the conformational model. During three-dimensional pharmacophore generation for database search purposes, the restriction is given by the tolerance of the pharmacophore query. It has been shown in principle that a limited number of... 

The database search process starts with a rapid screening process within which molecules possessing properties required from potential hits are sorted out from those that can be excluded a priori. The screen involves substructure match followed by screens matching three-dimensional pharmacophore features, molecular shapes or exclusion volumes and text constraints (ID properties) if present in the query (through Oracle). All this greatly reduces the number of potential hit compounds in the database. The next step of the search pro-... 

---