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Structure based prediction of subtype-selectivity for adenosine receptor antagonists.

ABSTRACT: One of the major hurdles in the development of safe and effective drugs targeting G-protein coupled receptors (GPCRs) is finding ligands that are highly selective for a specific receptor subtype. Structural understanding of subtype-specific binding pocket variations and ligand-receptor interactions may greatly facilitate design of selective ligands. To gain insights into the structural basis of ligand subtype selectivity within the family of adenosine receptors (AR: A(1), A(2A), A(2B), and A(3)) we generated 3D models of all four subtypes using the recently determined crystal structure of the A(A2)AR as a template, and employing the methodology of ligand-guided receptor optimization for refinement. This approach produced 3D conformational models of AR subtypes that effectively explain binding modes and subtype selectivity for a diverse set of known AR antagonists. Analysis of the subtype-specific ligand-receptor interactions allowed identification of the major determinants of ligand selectivity, which may facilitate discovery of more efficient drug candidates.

SUBMITTER: Katritch V

PROVIDER: S-EPMC2980563 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Structure based prediction of subtype-selectivity for adenosine receptor antagonists.

Katritch Vsevolod V Kufareva Irina I Abagyan Ruben R

Neuropharmacology 20100715 1

One of the major hurdles in the development of safe and effective drugs targeting G-protein coupled receptors (GPCRs) is finding ligands that are highly selective for a specific receptor subtype. Structural understanding of subtype-specific binding pocket variations and ligand-receptor interactions may greatly facilitate design of selective ligands. To gain insights into the structural basis of ligand subtype selectivity within the family of adenosine receptors (AR: A(1), A(2A), A(2B), and A(3)) ...[more]

PMID: 20637786

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Project description:Histamine receptors (HRs) are excellent drug targets for the treatment of diseases, such as schizophrenia, psychosis, depression, migraine, allergies, asthma, ulcers, and hypertension. Among them, the human H(3) histamine receptor (hH(3)HR) antagonists have been proposed for specific therapeutic applications, including treatment of Alzheimer's disease, attention deficit hyperactivity disorder (ADHD), epilepsy, and obesity. However, many of these drug candidates cause undesired side effects through the cross-reactivity with other histamine receptor subtypes. In order to develop improved selectivity and activity for such treatments, it would be useful to have the three-dimensional structures for all four HRs. We report here the predicted structures of four HR subtypes (H(1), H(2), H(3), and H(4)) using the GEnSeMBLE (GPCR ensemble of structures in membrane bilayer environment) Monte Carlo protocol, sampling ∼35 million combinations of helix packings to predict the 10 most stable packings for each of the four subtypes. Then we used these 10 best protein structures with the DarwinDock Monte Carlo protocol to sample ∼50 000 × 10(20) poses to predict the optimum ligand-protein structures for various agonists and antagonists. We find that E206(5.46) contributes most in binding H(3) selective agonists (5, 6, 7) in agreement with experimental mutation studies. We also find that conserved E5.46/S5.43 in both of hH(3)HR and hH(4)HR are involved in H(3)/ H(4) subtype selectivity. In addition, we find that M378(6.55) in hH(3)HR provides additional hydrophobic interactions different from hH(4)HR (the corresponding amino acid of T323(6.55) in hH(4)HR) to provide additional subtype bias. From these studies, we developed a pharmacophore model based on our predictions for known hH(3)HR selective antagonists in clinical study [ABT-239 1, GSK-189,254 2, PF-3654746 3, and BF2.649 (tiprolisant) 4] that suggests critical selectivity directing elements are: the basic proton interacting with D114(3.32), the spacer, the aromatic ring substituted with the hydrophilic or lipophilic groups interacting with lipophilic pockets in transmembranes (TMs) 3-5-6 and the aliphatic ring located in TMs 2-3-7. These 3D structures for all four HRs should help guide the rational design of novel drugs for the subtype selective antagonists and agonists with reduced side effects.

Dataset Information

Structure based prediction of subtype-selectivity for adenosine receptor antagonists.

Publications

Structure based prediction of subtype-selectivity for adenosine receptor antagonists.

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