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Substructural features

In order to enhance our ligand-based query hypothesis, the structural fragments of the initial query were generalized but linked with the same distance constraints. A search of this final query (see Fig. 4-10) in the same list yielded 690 hits and a statistically significant correlation of the presence of this enantiophore and the enan-tioselectivity of the compounds was found (94 % of those are well resolved on Chi-ralcel OD). Note that out of the 4203 compounds of the Chiralcel OD domain search, a 2D search found 1900 structures that contain the substructural features of the generalized query. [Pg.111]

Purdy [91] used the technique to predict the carcinogenicity of organic chemicals in rodents, although his model was based on physicochemical and molecular orbital-based descriptors as well as on substructural features and it used only a relatively small number of compounds. His decision tree, which was manual rather than computer based, was trained on 306 compounds and tested on 301 different compounds it achieved 96% correct classification for the training set and 90% correct classification for the test set. [Pg.484]

Figure 16 shows that compounds with structural alerts, substructural features that are generally not wanted in drug candidates but may be acceptable in lead compounds, are pushed back into the fifth and sixth lists. [Pg.124]

Fig. 15.8. Substructure mapping, highlighting, and drill-down. Based on on-the-fly substructure query and mapping capability within SciTegic Pipeline Pilot, PGVL Hub allows user to perform substructure queries into a set of target molecules. In the example shown, a set of substructure queries globally collected and validated as undesirable substructure features to be avoided are mapped into target molecules (41b). Fig. 15.8. Substructure mapping, highlighting, and drill-down. Based on on-the-fly substructure query and mapping capability within SciTegic Pipeline Pilot, PGVL Hub allows user to perform substructure queries into a set of target molecules. In the example shown, a set of substructure queries globally collected and validated as undesirable substructure features to be avoided are mapped into target molecules (41b).
Method of Meylan and Howard Meylan and Howard [9] expanded the bond contribution method of Hine and Mookerjee. Based on 345 compounds they derived bond contributions for 59 different bond types. Their method has been validated with an independent set of 74 structurally diverse compounds, obtaining a correlation coefficient of 0.96. Their method also needs correction factors for several structural-substructural features. This method has been implemented into a Henry s law constant program performing AWPC (25°C) estimations from SMILES input [15]. [Pg.142]

BgW The BgVV database has been used to develop specific S AR models for predicting skin irritation and corrosion. These models have been incorporated into a decision support system (DSS). The DSS is mainly a rule based approach, the rules being developed are not only based on substructural features but additionally incorporate specific physicochemical properties such as Log P, molecular weight, and aqueous solubility. The rules have been developed and validated on a total of 1508 compounds of which 199 are classified as hazardous. The DSS is designed to predict EU risk phrases. [Pg.503]

Figure 13.2 Three structural alerts. Chemicals with any of these 2D substructural features should receive proper attention in priority setting because they are commonly observed in most ligands to ER. Figure 13.2 Three structural alerts. Chemicals with any of these 2D substructural features should receive proper attention in priority setting because they are commonly observed in most ligands to ER.
Molecular similarity and diversity methods typically represent molecules by a vector of real-valued properties (molecular weight, logP etc.) or binary values (0 for absence, 1 for presence of a substructure feature for example) in a bit-string or... [Pg.84]

The score s,- of the activity for a new compound is calculated by adding the weights for each substructural feature present in the considered compoxmd, i.e. ... [Pg.215]

A structure-activity analysis of 609 compounds87 revealed different substructural features ( biophores ) related to MDR reversal activity. The biophore most significantly related to activity had the generic form C-C-X-C-C, where X = N,... [Pg.501]

Others have used MULTICASE to determine important substructural features like... [Pg.273]

The structural unit of this subtype of polycyclic alkaloid is a 3-alkyl substituted pyridine, where remote terminal oxime, amine, methoxy amine, nitro, imine oxide or methoxy-oxime fuctionalities are characteristic in the monomeric forms. Polymeric pyridinium salts attached to a long linear carbonated chain through positions 1 and 3 are a substructural feature in a second subgroup of alkaloids. Related reduced dihydropyridinium salts have also been known since the discovery of haliclamine A and B. (See Tables 5 and 6 for C-NMR data). [Pg.584]

In a related study containing hydroxylated and sulfonic acid analogs, we again find excellent additivity of substructural features (25). Data are for inhibition of h-GABA binding to human cerebellar membranes. [Pg.284]

Studies of screening systems for 2-D substructure searching have shown that the substructural features which are chosen for use as screens should be of intermediate frequency of occurrence in the database which is to be searched moreover, all of these frequencies should be approximately equal if facile query encoding and good levels of screen-out are to be obtained. Accordingly, there has been considerable interest in methodologies for the generation of equifrequent screen sets, " and this work forms the basis for the selection procedure used here. [Pg.133]

A known chemical structure permitted the assignment of substructural features. [Pg.410]

In an attempt to place such extrapolations on a more logical basis, Craig and Enslein (57) tested the assumption that the interspecies differences between the mouse and rat may be modeled by using a combination of substructural features and physical properties. From the 1974 version of the Toxic Substances List, 160 diversified compounds were identified for which both rat and mouse oral LD50 values were reported, and for which partition coefficients could either be located or reasonable estimates calculated. [Pg.411]


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See also in sourсe #XX -- [ Pg.8 ]




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