Query pharmacophore

The Web-based graphical user interface permits a choice from numerous criteria and the performance of rapid searches. This service, based on the chemistry information toolkit CACTVS, provides complex Boolean searches. Flexible substructure searches have also been implemented. Users can conduct 3D pharmacophore queries in up to 25 conformations pre-calculated for each compound. Numerous output formats as well as 2D and 3D visuaHzation options are supplied. It is possible to export search results in various forms and with choices for data contents in the exported files, for structure sets ranging in size from a single compound to the entire database. Additional information and down-loadable files (in various formats) can be obtained from this service. 

Figure 10.3-25. a) Structure of diethylstilbestrol (DES) b) 3 D pharmacophore query of DES two hits were found c) estrone and d) estradiol. 

Each of the pharmacophore queries consisted of one donor, one acceptor and one of the two hydrophobic points indicated in Figure 1.16. The directionality of hydrogen bonds was inferred from the X-ray structure and reasonably loose tolerances of 1.5 A were used for donor-acceptor distances and 2-2.5 A to the hydrophobe were chosen to allow for the flexibility seen across kinase structures and to maximise the diversity amongst the identified fragments. Four pharmacophore queries were completed and the results were combined. The chosen fragments were further filtered by molecular weight (between 150 and 250), 51og P (between 2.5 and —2.5) and the presence of... 

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... 

As part of the processing within this system, molecules can be cleaned (chirality, ionization). Conformers can also be generated on-the-fly when performing the database search. In addition to conformations, indexing of a database can be done by adding pharmacophore sites. Partial match of the hits on a pharmacophore query is allowed. The pharmacophore search hits are ranked using a fitness function. 

The definition of pharmacophores is done manually by applying so-called schemes using a Pharmacophore Query Editor. A template molecule is generally used for this purpose. In the MOE environment, a scheme is a collection of functions that define how each ligand is annotated. This is accessed via an SVL function. The default scheme is called PCH (Polarity-Charged-Hydrophobicity). New schemes can be created to represent certain molecules better, e.g. Planar-Polar-Charged- Hydrophobiaty [91]. 

If the structural information of a receptor is not available, molecule alignments can be performed using an all-atom flexible alignment procedure that combines a force field and a 3D similarity function based on Gaussian descriptions of shape and pharmacophore features to produce an ensemble of possible alignments of a collection of small molecules [92]. Pharmacophore queries can be derived from the resulting set of aligned conformations of known actives. 

Figure 13.4 Seven pharmacophore queries. The mesh balls represent H-bond acceptor sites, hydrophobic centers and aromatic centers. The solid white surfaces represent shape constrain. 

This phase classifies chemicals passing from the previous phase into active and inactive categories. Three structural alerts (Section IV.B), seven pharmacophore queries (Section IV.C), and the Decision Tree classification model (Section IV.D) were used in parallel to discriminate active from inactive chemicals. To ensure the lowest false negative rate in this phase, a chemical predicted to be active by any of these 11 models is subsequently evaluated in Phase III, whereas only those predicted to inactive by all these models are eliminated for further evaluation. Since structural alert, pharamacophore and Decision Tree methods incorporate and weight differently the various structural features that endow a chemical with the ability to bind the ER the combined outputs derived... 

Active/lnactive Assignment 3 Structural Alerts 7 Pharmacophore Queries 1 Decision Tree... 

An extension of the method that enables the steric shape of a protein site to be used as an additional constraint in the comparison of multiple potential pharmacophores of a protein site with a ligand has been developed, and is being commercialised as the DiR module of Chem-X. The method is equivalent to simultaneous 3D-database searching using multiple 3D pharmacophoric queries and steric constraints the advantage is that only one conformational sampling is necessary. 

Figure 2. Discovering candidate ligands from a pharmacophore model. First the model is determined by examining SAR from a compound series. A database can then be searched for compounds matching the pharmacophore query...

Computational search (by docking and/or pharmacophore queries) in chemical databases for compounds that fit into the binding site and satisfy key interactions. 

Compound 1 Known adenosine ligand used to generate pharmacophore queries... 

T.R. Webb, N. Melman, D. Lvovskiy, X-D. Ji and K.A. Jacobson, The ntiliza-tion of a nnified pharmacophore query in the discovery of new antagonists of the adenosine receptor family, Bioorg. Med. Chem. Lett., 2000, 10, 31-34. 

In an initial implementation from the authors (35), a set of 5916 three-point pharmacophore queries was generated and used to setirch a database. Compounds were charac-... 

Pharmacophore Keys. Originally designed to speed pharmacophore query searching, pharmacophore keys are bitset fingerprints that indicate the presence or absence of given... 

Successful virtual screening relies on an appropriate and correct description of the molecules being screened two particular sources of error are protonation state and tautomeric form. Oellien et have developed an exhaustive tautomer enumeration approach based on a set of 21 predefined transforms. The group do not attempt to say which tautomer is favoured, only that every form is represented. Databases built using all tautomers show better performance especially when screened with pharmacophore queries, as the bias introduced by most compound registration tools as to the correct tautomer is removed. 

Fig. 10 Definition of the pharmacophore query for the Kvl.5 channel. Representatives of the two compound series (A and B) were aligned(b) to derive the pharmacophore (a). (Copyright is permitted by Elsevier).

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