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Random screening antagonists

The discovery that the 4-heteroarylpiperazine-l-carboxyanilide template can generate potent TRPVl antagonists was independently reported by three groups [76-79]. Most of the published work on this class of compounds was carried out by Purdue Pharma, and is focused on the optimization of (13a), a lead compound that had emerged from random screening of a chemical... [Pg.154]

Like angiotensin 11, non-peptide B2 receptor antagonists and agonists of bradykinin were obtained by random screening approaches. Chemical modifications on random screening leads like 101 led to non-peptide antagonists... [Pg.38]

Non-peptide antagonists of endothelin were discovered by random screening approaches. A comparison of compounds 119 and 120 demonstrates that it is possible to obtain selective and non-selective compounds in the same series by chemical modifications. Carboxyindoline derivative 119 was about 100-fold more selective ETa receptor antagonist and compound 120 was a non-selective antagonist. Another series of... [Pg.42]

Most of the other compounds which have been discovered to have endothelin antagonist properties were identified as a result of the random screening of natural products in endothelin binding assays. [Pg.386]

Numerous highly potent and selective substance P antagonists are known, some of which were obtained from optimization of compounds identified during random screening.In addition, Hirschmann et al.i47 found excellent antagonist activity at the SP receptor (IC50 = 60 nM) with a (3-D-glucose-based peptidomimetic. [Pg.56]

Fig. 13.4 En richment graph for virtual screening of a1A antagonists embedded into a random MDDR library comprising 1048 compounds [11]. The curve shows the relative ranking of the 50 a1A antagonists. Database compounds are ranked along the x-axis based on the fit value calculated for the mapping on the respective pharmacophore. Fig. 13.4 En richment graph for virtual screening of a1A antagonists embedded into a random MDDR library comprising 1048 compounds [11]. The curve shows the relative ranking of the 50 a1A antagonists. Database compounds are ranked along the x-axis based on the fit value calculated for the mapping on the respective pharmacophore.

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Screening, random

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