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Default Design and characterization of libraries of molecular fragments for use in NMR screen

Design and characterization of libraries of molecular fragments for use in NMR screening against protein targets.

Related Articles Design and characterization of libraries of molecular fragments for use in NMR screening against protein targets.

J Chem Inf Comput Sci. 2004 Nov-Dec;44(6):2157-66

Authors: Baurin N, Aboul-Ela F, Barril X, Davis B, Drysdale M, Dymock B, Finch H, Fromont C, Richardson C, Simmonite H, Hubbard RE

We have designed four generations of a low molecular weight fragment library for use in NMR-based screening against protein targets. The library initially contained 723 fragments which were selected manually from the Available Chemicals Directory. A series of in silico filters and property calculations were developed to automate the selection process, allowing a larger database of 1.79 M available compounds to be searched for a further 357 compounds that were added to the library. A kinase binding pharmacophore was then derived to select 174 kinase-focused fragments. Finally, an additional 61 fragments were selected to increase the number of different pharmacophores represented within the library. All of the fragments added to the library passed quality checks to ensure they were suitable for the screening protocol, with appropriate solubility, purity, chemical stability, and unambiguous NMR spectrum. The successive generations of libraries have been characterized through analysis of structural properties (molecular weight, lipophilicity, polar surface area, number of rotatable bonds, and hydrogen-bonding potential) and by analyzing their pharmacophoric complexity. These calculations have been used to compare the fragment libraries with a drug-like reference set of compounds and a set of molecules that bind to protein active sites. In addition, an analysis of the overall results of screening the library against the ATP binding site of two protein targets (HSP90 and CDK2) reveals different patterns of fragment binding, demonstrating that the approach can find selective compounds that discriminate between related binding sites.

PMID: 15554686 [PubMed - indexed for MEDLINE]



Source: PubMed
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