2004
DOI: 10.1021/jm040762v
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A Virtual Screening Approach to Finding Novel and Potent Antagonists at the Melanin-Concentrating Hormone 1 Receptor

Abstract: Melanin-concentrating hormone (MCH) has been known to be an appetite-stimulating peptide for a number of years. However, it is only recently that MCH has been discovered to be the natural ligand for a previously "orphan" G-protein-coupled receptor, now designated MCH-1R. This receptor has been shown to mediate the effects of MCH on appetite and body weight, and consequently, drug discovery programs have begun to exploit this information in the search for MCH-1R antagonists for the treatment of obesity. In this… Show more

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Cited by 82 publications
(56 citation statements)
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“…ref 50 where models are selected according to docking score and quality of binding pose), we felt it was better to validate the final set of models through the performance of the modeled binding sites in a smallscale virtual screen. In this way, we test models in the demanding experiment of discriminating between known MCH-R1 antagonists described previously 27 and GPCR class A binders. This is a more stringent test than using a random library where compounds that do not share the physicochemical profile of known binders may facilitate binder/nonbinder separation.…”
Section: Ligand-steered Homology Modeling Method: Overview and Applicmentioning
confidence: 99%
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“…ref 50 where models are selected according to docking score and quality of binding pose), we felt it was better to validate the final set of models through the performance of the modeled binding sites in a smallscale virtual screen. In this way, we test models in the demanding experiment of discriminating between known MCH-R1 antagonists described previously 27 and GPCR class A binders. This is a more stringent test than using a random library where compounds that do not share the physicochemical profile of known binders may facilitate binder/nonbinder separation.…”
Section: Ligand-steered Homology Modeling Method: Overview and Applicmentioning
confidence: 99%
“…Refinement showed that 3 349 510 nonredundant compounds were present. The nonredundant database was then filtered according to a set of parameters based on those used by Clark et al 27 in their ligandbased screening for MCH-R1 antagonists. Maximum allowed molecular weight was increased to 600 from 550, and compounds that did not have an amine nitrogen (single bonded nitrogen not bonded to any sp 2 heavy atom) were removed from the database, resulting in 187 084 compounds.…”
Section: Methodsmentioning
confidence: 99%
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“…Initially, studies of molecular modeling of first MCH-R1 antagonists T-226296 and compounds of Argenta group, defined the following characteristics as being essential to MCH-R1 binding: positive nitrogen, hydrogen acceptor group and the presence of one or two hydrophobic subunits. 36 Recently, quantitative structure-activity relationship (QSAR) information derived from aproximately 300 benzamides compounds to contruct pharmacophore models suggests similar results of previous studies: a hydrophobic and an aromatic moieties, a hydrogen bond acceptor or donor and a positive charged site. 37 On the other hand, a second small molecule MCH-R1 antagonist was identified, (Figure 3) with a K i of 7.7 nM, which showed good aqueous solubility, good BBB ratio and a positive pharmacokinetic profile with high oral bioavailability (80%) in rats.…”
Section: Carboxamide Derivativesmentioning
confidence: 54%
“…However, as it was already demonstrated by Figure 3b [22], slight chemical changes of a novel scaffold might readily result in much improved potency. In a different study, a "fuzzy" pharmacophore technique retrieved a molecule inhibit- [22], c [23]; d [24], e [5]; f, [25]; g, [26]; h, [28]; i, [30]; j, [32]; k, [34]; l, [35]; m, [36]; n, [37]; o, [38]; p, [40]; q, [41]; r, [42]; s, [43]; t, [44]; u, [45].…”
Section: Examples Of Successful Scaffold-hopsmentioning
confidence: 99%