Substructures, identifying similar

The breaking of a strategic bond and the generation of synthesis precursors defines a synthesis reaction. In the simplest case, the reaction is already known from literature. In most cases, however, the rcaaion step obtained has to be generalised in order to find any similar and successfully performed reactions with a similar substituent pattern or with a similar rearrangement of bonds. One way of generalizing a reaction is to identify the reaction center and the reaction substructure of the reaction. This defines a reaction type. 

In a similar manner, such privileged motifs can be identified for each GPCR-specific activity group. The typical number of privileged substructures per group lies in the range of 5 to 20 for the studied GPCR-specific compound sets. 

In the area of structure elucidation, if one had evidence that an unknown contained a particular substructure, a search might reveal that there were NMR spectra to compare with such a similar structure, but no IR spectra, suggesting that an NMR spectrum would be more useful than an IR spectrum in attempts to identify the unknown. 

Since the formulation of precise and well defined substructure queries is not trivial, other approaches to identify unwanted substructures are used as well. If the decisions made by medicinal chemists whether to accept or reject individual screening hits based on purely structural criteria has been captured, this can be used to train a statistical model predicting medicinal chemists judgment on chemical structures. The consensus among medicinal chemists has been demonstrated to be limited [48]. Therefore, this exercise must be based on the decision of a larger group of chemists in order not to bias the model towards the preferences of any individual chemist. In a similar way such models can be trained on experimental toxicity data for an individual experimentally determined toxicological endpoint. 

While the size requirement for SMC antiproliferative activity had been investigated for heparin (cf. Sect. 2.2), a similar study on fractions of highly active heparan sulfate has not been carried out. After the discovery of active sulfated tetrasaccharides it seemed possible that relatively small heparan sulfate substructures with the antiproliferative activity of heparin could be identified. Model heparan sulfate oligosaccharides were devised in which the W-sulfate groups were replaced by 0-sulfates and the glucuronic acids were replaced by glucoses, form y carboxyl-reduced and sulfated glucuronic acids - in parallel to CRS-heparin (see above). With this approach Ae heparan sulfate backbone... 

The general problem can be expressed by considering a class of drug molecules, A, composed of a set of structurally similar members A, A2, A3, Ak. . . Am. Each drug molecule, Ak, of the set can be specified by a set of atomic coordinates for each atom a (xla, x2a, x3a and the molecule is composed of a set of molecular features F F, F2, F3, Fk. . . Fn. Within a set of active compounds, there are likely to be substructural similarities these similarities can be quantified so that similar molecular substructures in the set A can be found. A simple quantification system for molecular similarity is provided by the Tani-moto index of a pair of compounds. The index works by identifying common substructures within the molecules. Conversely, structural differences can also be identified. Correspondences in substructures and features can be determined by experiment and subsets of features can be related to activity. 

Carr et al., 1993). The neutral loss scan mode is used as a class identifier to also screen components that contain a common substructure. Barbuch et al. demonstrated this approach for the class identification of phytoestrogens (Barbuch et al., 1989), using thermospray ionization (TSI)-LC/MS/MS. Brownsill et al. used a similar electrospray ionization (ESI)-LC/MS/MS approach for the analysis of metabolites in rat liver slices (Brownsill et al., 1994). 

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