ArticleJournal of chemical information and modeling2011
Structure-based prediction of subtype selectivity of histamine H3 receptor selective antagonists in clinical trials.
Article in Journal of chemical information and modeling, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed, 38 citations in OpenAlex.
- Steviol rebaudiosides bind to four different sites of the human sweet taste receptor (T1R2/T1R3) complex explaining confusing experiments.Communications chemistry · 2024Article
- Dual Piperidine-Based Histamine HJournal of medicinal chemistry · 2023Article
- CCR6 as a Potential Target for Therapeutic Antibodies for the Treatment of Inflammatory Diseases.Antibodies (Basel, Switzerland) · 2023Review
- Molecular Modeling of Histamine Receptors-Recent Advances in Drug Discovery.Molecules (Basel, Switzerland) · 2021Review
- Mechanism of Action of Atypical Antipsychotic Drugs in Mood Disorders.International journal of molecular sciences · 2020Review
- Design, synthesis, and anticonvulsant effects evaluation of nonimidazole histamine HJournal of enzyme inhibition and medicinal chemistry · 2020Article
- Molecular dynamics of the histamine H3 membrane receptor reveals different mechanisms of GPCR signal transduction.Scientific reports · 2020Article
- Pitolisant and Other Histamine-3 Receptor Antagonists-An Update on Therapeutic Potentials and Clinical Prospects.Medicines (Basel, Switzerland) · 2020Review
- How to design potent and selective DYRK1B inhibitors? Molecular modeling study.Journal of molecular modeling · 2019Article
- Synthesis and Characterization of a Bidirectional Photoswitchable Antagonist Toolbox for Real-Time GPCR Photopharmacology.Journal of the American Chemical Society · 2018Article
- QSAR Modeling of Histamine H3R Antagonists/inverse Agonists as Future Drugs for Neurodegenerative Diseases.Current neuropharmacology · 2018Review
- Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification.PloS one · 2017Article
- Predicted 3D structures of olfactory receptors with details of odorant binding to OR1G1.Journal of computer-aided molecular design · 2014Article
- SuperBiHelix method for predicting the pleiotropic ensemble of G-protein-coupled receptor conformations.Proceedings of the National Academy of Sciences of the United States of America · 2014Article
- A single-point mutation (Ala280Val) in the third intracellular loop alters the signalling properties of the human histamine H₃ receptor stably expressed in CHO-K1 cells.British journal of pharmacology · 2013Article
- Cunninghamella as a microbiological model for metabolism of histamine H(3) receptor antagonist 1-[3-(4-tert-butylphenoxy)propyl]piperidine.Applied biochemistry and biotechnology · 2012Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
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.
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Registered trials
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