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Substructure analysis

Engkvist O, Wrede P, Rester U (2003) Prediction of CNS activity of compound libraries using substructure analysis. J Chem Inf Comput Sci 43 155-160... [Pg.417]

In Eq. (2), Tj is the total number of molecules in the database with bit j set and Nt is the total number of molecules in the database (rather than the total numbers in the training-set, as in conventional substructural analysis). [Pg.136]

Table 8 Mean Recalls at 5% for Similarity Searching (SS), Conventional Turbo Similarity Searching using Croup Fusion (TSS-CF) and Turbo Similarity Searching using Substructural Analysis (TSS-SSA) and Binary Kernel Discrimination (TSS-BKD)... Table 8 Mean Recalls at 5% for Similarity Searching (SS), Conventional Turbo Similarity Searching using Croup Fusion (TSS-CF) and Turbo Similarity Searching using Substructural Analysis (TSS-SSA) and Binary Kernel Discrimination (TSS-BKD)...
Cramer RD, Redl G, Berkoff CE. (1974) Substructural Analysis — A Novel Approach to Problem of Drug Design. /. Med. Chem. 17 533-535. [Pg.155]

Ormerod A, Willett P, BawdenD. (1989) Comparison of Fragment Weighting Schemes for Substructural Analysis. Quant. Struet.-Aet. Pel. 8 115-129. [Pg.155]

Gillet, V. J., Willett, R, and Bradshaw, J. (1998) Identification of biological activity profiles using substructural analysis and genetic algorithms. J. Chem. Inf. Comput. Sci. 38, 165-179. [Pg.61]

Table 2. Results of the common substructure analysis between acesul-fame and succharin... Table 2. Results of the common substructure analysis between acesul-fame and succharin...
TABLE 6.22 Substructure analysis data indicating the structures of the fragment ions with their experimentally determined mass, calculated accurate mass, and parts per million error... [Pg.181]

Sternson SM, Wong JC, Grozinger CM, Schreiber SL, Synthesis of 7200 small molecules based on a substructural analysis of the histone deacetylase inhibitors trichostatin and trapoxin, Org. Lett., 3 4239-4242, 2001. [Pg.86]

The main drawback of the conventional similarity search concerns an inability to use experimental information on biological activity to adjust similarity measures. This results in an inability to discriminate relevant and non-relevant fragment descriptors used for computing similarity measures. To tackle this problem, Cramer el al. developed substructural analysis, in which each fragment (represented as a bit in a fingerprint) is weighted by taking into account its occurrence in active and in inactive compounds. Subsequently, many similar approaches have been described in the literature. ... [Pg.24]

E.H. Kerns, K.J. Volk, S.E. Etill, M.S. Lee, Profiling new taxanes using LC-MS-MS substructural analysis techniques. Rapid Commun. Mass Spectrom., 9 (1995) 1539. [Pg.282]

The substructure list representation can be considered as a one-dimensional representation of a molecule and consists of a list of structured fragments of a molecule the list can only be a partial list of fragments, functional groups, or substituents of interest present in the molecule, thus not requiring a complete knowledge of the molecule structure. The descriptors derived by this representation can be called ID-descriptors and are typically used in - substructural analysis and -> substructure searching. [Pg.304]

An increasing interest of the scientific community in recent years has been shown in the fields of combinatorial chemistry, high-throughput screening, - substructural analysis, and -+ similarity searching, for which several similarity/diversity approaches have been proposed mainly based on - substructure descriptors such as -> molecular fingerprints, which are particularly suitable for informatic treatment. [Pg.422]

Craig, P.N. (1990). Substructural Analysis and Compound Selection. In Quantitative Drug Design. Vol. 4 (Ramsden, C.A., ed.), Pergamon Press, Oxford (UK), pp. 645-666. [Pg.552]

Hall, L.H. and Kier, L.B. (1978b). Molecular Connectivity and Substructure Analysis. [Pg.578]


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See also in sourсe #XX -- [ Pg.52 , Pg.181 , Pg.203 ]




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