Chemical function-based pharmacophore generation of selective κ-opioid receptor agonists by catalyst and phase

Two chemical function-based pharmacophore models of selective κ-opioid receptor agonists were generated by using two different programs: Catalyst/HypoGen and Phase. The best output hypothesis (Hypo1) of HypoGen consisted of five features: one hydrogen-bond acceptor (HA), three hydrophobic points (HY), and one positive ionizable function (PI). The highest scoring model (Hypo2) produced by Phase comprised four features: one acceptor (A), one positive ionizable function (P), and two aromatic ring features (R). These two models (Hypo1 and Hypo2) were then validated by test set prediction and enrichment factors. They were shown to be able to identify highly potent κ-agonists within a certain range, and satisfactory enrichments were achieved. The features of these two pharmacophore models were similar and consistent with experiment data. The models produced here were also generally in accord with other reported models. Therefore, our pharmacophore models were considered as valuable tools for 3D virtual screening, and could be useful for designing novel κ-agonists.

[1]  P. von Voigtlander,et al.  Benzeneacetamide amines: structurally novel non-m mu opioids. , 1982, Journal of medicinal chemistry.

[2]  Osman F. Güner,et al.  Pharmacophore perception, development, and use in drug design , 2000 .

[3]  B. Wünsch,et al.  Methylated analogues of methyl (R)-4-(3,4-dichlorophenylacetyl)- 3-(pyrrolidin-1-ylmethyl)piperazine-1-carboxylate (GR-89,696) as highly potent kappa-receptor agonists: stereoselective synthesis, opioid-receptor affinity, receptor selectivity, and functional studies. , 2001, Journal of medicinal chemistry.

[4]  J. Shaw,et al.  2-(3,4-Dichlorophenyl)-N-methyl-N-[2-(1-pyrrolidinyl)-1-substituted- ethyl]-acetamides: the use of conformational analysis in the development of a novel series of potent opioid kappa agonists. , 1991, Journal of medicinal chemistry.

[5]  U. Holzgrabe,et al.  Mechanism of action of the diazabicyclononanone-type kappa-agonists. , 2003, Journal of medicinal chemistry.

[6]  R. Dolle,et al.  Arylacetamide κ opioid receptor agonists with reduced cytochrome P450 2D6 inhibitory activity , 2005 .

[7]  T. Graczyk,et al.  Novel malonamide derivatives as potent κ opioid receptor agonists , 2007 .

[8]  P B Bradley,et al.  International Union of Pharmacology. XII. Classification of opioid receptors. , 1996, Pharmacological reviews.

[9]  Marta Filizola,et al.  Differentiation of δ, μ, and κ opioid receptor agonists based on pharmacophore development and computed physicochemical properties , 2001, J. Comput. Aided Mol. Des..

[10]  U. Gether Uncovering molecular mechanisms involved in activation of G protein-coupled receptors. , 2000, Endocrine reviews.

[11]  Michael Koblish,et al.  Azepinone as a conformational constraint in the design of κ-opioid receptor agonists , 2004 .

[12]  Brigitte L. Kieffer,et al.  Recent advances in molecular recognition and signal transduction of active peptides: Receptors for opioid peptides , 1995, Cellular and Molecular Neurobiology.

[13]  G. Uhl,et al.  -mu opiate receptor. Charged transmembrane domain amino acids are critical for agonist recognition and intrinsic activity. , 1994, The Journal of biological chemistry.

[14]  W. Bowen,et al.  Alterations in the stereochemistry of the kappa-selective opioid agonist U50,488 result in high-affinity sigma ligands. , 1989, Journal of medicinal chemistry.

[15]  R. Dolle,et al.  Peripherally restricted opioid agonists as novel analgesic agents. , 2004, Current pharmaceutical design.

[16]  T. Graczyk,et al.  Potent and highly selective kappa opioid receptor agonists incorporating chroman- and 2,3-dihydrobenzofuran-based constraints. , 2005, Bioorganic & medicinal chemistry letters.

[17]  Kong Haeyoung,et al.  Amino acids in the cloned mouse kappa receptor that are necessary for high affinity agonist binding but not antagonist binding , 1994, Regulatory Peptides.

[18]  Gareth Jones,et al.  A genetic algorithm for flexible molecular overlay and pharmacophore elucidation , 1995, J. Comput. Aided Mol. Des..

[19]  Eva M. Krovat,et al.  Non-peptide angiotensin II receptor antagonists: chemical feature based pharmacophore identification. , 2003, Journal of medicinal chemistry.

[20]  M. Botta,et al.  Antifungal agents. 10. New derivatives of 1-[(aryl)[4-aryl-1H-pyrrol-3-yl]methyl]-1H-imidazole, synthesis, anti-candida activity, and quantitative structure-analysis relationship studies. , 2002, Journal of medicinal chemistry.

[21]  Michael Koblish,et al.  Synthesis and evaluation of novel peripherally restricted κ-opioid receptor agonists , 2005 .

[22]  Y. Kurogi,et al.  Pharmacophore modeling and three-dimensional database searching for drug design using catalyst. , 2001, Current medicinal chemistry.

[23]  D. Rees,et al.  Highly selective kappa-opioid analgesics. 3. Synthesis and structure-activity relationships of novel N-[2-(1-pyrrolidinyl)-4- or -5-substituted-cyclohexyl]arylacetamide derivatives. , 1990, Journal of medicinal chemistry.

[24]  A Ulloa-Aguirre,et al.  Structure-activity relationships of G protein-coupled receptors. , 1999, Archives of medical research.

[25]  W. Bowen,et al.  Synthesis, characterization, and biological evaluation of a novel class of N-(arylethyl)-N-alkyl-2-(1-pyrrolidinyl)ethylamines: structural requirements and binding affinity at the sigma receptor. , 1992, Journal of medicinal chemistry.

[26]  T. Langer,et al.  Chemical function based pharmacophore generation of endothelin-A selective receptor antagonists. , 2004, Journal of medicinal chemistry.

[27]  L. Cortes-Burgos,et al.  Arylacetamides as peripherally restricted kappa opioid receptor agonists. , 2000, Bioorganic & Medicinal Chemistry Letters.

[28]  David M. Ferguson,et al.  A combined ligand-based and target-based drug design approach for G-protein coupled receptors: application to salvinorin A, a selective kappa opioid receptor agonist , 2006, J. Comput. Aided Mol. Des..

[29]  E Novellino,et al.  Modeling of kappa-opioid receptor/agonists interactions using pharmacophore-based and docking simulations. , 2000, Journal of medicinal chemistry.

[30]  David E. Shaw,et al.  PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results , 2006, J. Comput. Aided Mol. Des..

[31]  Yvonne Connolly Martin Distance Comparisons: A New Strategy for Examining Three-Dimensional Structure—Activity Relationships , 1995 .

[32]  Harald Schwalbe,et al.  Editorial: Dissecting G‐Protein‐Coupled Receptors: Structure, Function, and Ligand Interaction , 2002, Chembiochem : a European journal of chemical biology.

[33]  Michael Koblish,et al.  Novel phenylamino acetamide derivatives as potent and selective κ opioid receptor agonists , 2006 .

[34]  Harald Schwalbe Prof.,et al.  Editorial: Dissecting G-Protein-Coupled Receptors: Structure, Function, and Ligand Interaction , 2002 .

[35]  Peter Willett,et al.  GALAHAD: 1. Pharmacophore identification by hypermolecular alignment of ligands in 3D , 2006, J. Comput. Aided Mol. Des..