α-Substituted <i>N</i>-(Sulfonamido)alkyl-β-aminotetralins:  Potent and Selective Neuropeptide Y Y5 Receptor Antagonists

Youngman, Mark A.; McNally, James J.; Lovenberg, Timothy W.; Reitz, Allen B.; Willard, Nicole M.; Nepomuceno, Diane; Wilson, Sandy J.; Crooke, Jeffrey J.; Rosenthal, Daniel I.; Vaidya, and Anil H.; Dax, Scott L.

doi:10.1021/jm990468g

Cited by 42 publications

(29 citation statements)

References 24 publications

(37 reference statements)

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“…HTS has provided rapid lead identification for numerous drug targets (1)(2)(3)(4)(5)(6)(7)(8); however, HTS also has major drawbacks, including a significant level of false positives and false negatives and low hit rates for many targets (9). Successful leads from HTS can also suffer from poor bioavailability and unwanted toxicity profiles of compounds.…”

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confidence: 99%

Discovery of antiandrogen activity of nonsteroidal scaffolds of marketed drugs

Bisson

Cheltsov

Bruey-Sédano

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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Finding good drug leads de novo from large chemical libraries, real or virtual, is not an easy task. High-throughput screening is often plagued by low hit rates and many leads that are toxic or exhibit poor bioavailability. Exploiting the secondary activity of marketed drugs, on the other hand, may help in generating drug leads that can be optimized for the observed side-effect target, while maintaining acceptable bioavailability and toxicity profiles. Here, we describe an efficient computational methodology to discover leads to a protein target from safe marketed drugs. We applied an in silico ''drug repurposing'' procedure for identification of nonsteroidal antagonists against the human androgen receptor (AR), using multiple predicted models of an antagonist-bound receptor. The library of marketed oral drugs was then docked into the best-performing models, and the 11 selected compounds with the highest docking score were tested in vitro for AR binding and antagonism of dihydrotestosterone-induced AR transactivation. The phenothiazine derivatives acetophenazine, fluphenazine, and periciazine, used clinically as antipsychotic drugs, were identified as weak AR antagonists. This in vitro biological activity correlated well with endocrine side effects observed in individuals taking these medications. Further computational optimization of phenothiazines, combined with in vitro screening, led to the identification of a nonsteroidal antiandrogen with improved AR antagonism and marked reduction in affinity for dopaminergic and serotonergic receptors that are the primary target of phenothiazine antipsychotics.androgen receptor ͉ drug design ͉ prostate cancer C urrent approaches for discovery of novel chemical leads against a molecular target rely heavily on high-throughput screening (HTS) and to a lesser extent on virtual ligand screening (VLS) techniques. HTS has provided rapid lead identification for numerous drug targets (1-8); however, HTS also has major drawbacks, including a significant level of false positives and false negatives and low hit rates for many targets (9). Successful leads from HTS can also suffer from poor bioavailability and unwanted toxicity profiles of compounds. These problems result partially from the nature of the chemical libraries used for HTS. Furthermore, because the pharmacological properties of most compound libraries are largely unknown, there is an additional high risk that optimization of hits identified with HTS will not be sufficient for their evolution into real drugs.In contrast, retrospective analysis of marketed drugs reveals that their physicochemical and structural properties are clustered around preferred values and scaffolds (10). In addition, some chemical motifs are associated with high biological activity and often confer activity against more than one target/receptor (11-16). These motifs have been referred to as ''privileged structures'' (11). These observations lead to an assumption that the chemical space of potential drugs is limited. Consequently, currently marketed...

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confidence: 99%

Discovery of antiandrogen activity of nonsteroidal scaffolds of marketed drugs

Bisson

Cheltsov

Bruey-Sédano

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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“…Johnson, the nanomolar aminopyrazole lead was improved to yield (10) with Y5 affinity of 10 nM, while the 1 μM benzoindolylamine lead was improved to yield (11) with a 1 nM Y5 affinity [96,97]. A third series, the aminotetralins was also worked on by the R. W. Johnson group, resulting in a 1 nM antagonist [98,99]. A 21 nM Y5 antagonist (12) with good metabolic stability and aqueous solubility, was found to inhibit food intake in fasted rats for up to six hours post dosing, supporting the hypothesis that a Y5 antagonist could affect energy homeostasis [99].…”

Section: Y5 Antagonistsmentioning

confidence: 99%

“…A third series, the aminotetralins was also worked on by the R. W. Johnson group, resulting in a 1 nM antagonist [98,99]. A 21 nM Y5 antagonist (12) with good metabolic stability and aqueous solubility, was found to inhibit food intake in fasted rats for up to six hours post dosing, supporting the hypothesis that a Y5 antagonist could affect energy homeostasis [99]. S 25585 (13), a 5 nM antagonist, potently inhibited food intake, but also caused body-weight loss in Y5 knock-out mice [74].…”

Section: Y5 Antagonistsmentioning

confidence: 99%

“…As detailed above, several researchers have reported compounds that blocked Y5 agonist mediated food intake, but failed to block spontaneous food intake [102,103,107,117]. On the other hand, several researchers have reported Y5 antagonists that blocked fasting-induced or spontaneous food intake [99,104,105,111,118]. Although there have been only a small umber of chronic studies of the efficacy of Y5 antagonists, they are also inconsistent.…”

Section: Y5 Antagonistsmentioning

confidence: 99%

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NPY Y1 and Y5 Receptor Selective Antagonists as Anti-Obesity Drugs

MacNeil¹

2007

CTMC

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A combination of pharmacological and genetic studies in mice confirmed that the Y1 and Y5 receptors mediate the potent orexigenic actions of exogenous NPY. Although the physiological role of NPY in causing obesity is less clear, potent and selective antagonists of both Y1 and Y5 have been developed. Some of the NPY antagonists have suitable pharmacokinetic (PK) properties that allowed them to be evaluated in various rodent models of obesity. Several different Y1 and Y5 antagonists cause weight loss in rodent models, though confirmation that these effects are mechanism based has been limited. One Y5 antagonist, MK-0557 was evaluated in a 1-yr clinical trial and found to cause modest weight loss. Optimal NPY antagonist therapeutics for obesity may require blockade of both the Y1 and Y5 receptors.

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“…To date, various structurally diverse NPY Y5 receptor antagonists have been reported by a number of research groups, including ours. [10][11][12][13][14][15][16][17][18][19][20][21][22][23] Previously, our group reported several types of Y5 antagonists. [18][19][20][21][22][23] Our first lead compound, 1, was designed following similarity searching of an MRL compound collection, and had very high potency against Y5 receptor (IC 50 : 0.85 nM).…”

Section: Introductionmentioning

confidence: 99%