ArticleFrontiers in molecular biosciences2017
Agonist Binding to Chemosensory Receptors: A Systematic Bioinformatics Analysis.
Article in Frontiers in molecular biosciences, 2017. 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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Who cites it
16 citing papers in PubMed.
- Bitter taste TAS2R14 and TAS2R46 receptors bound to G proteins: comparison of cryo-EM, AlphaFold, and molecular dynamics structures.European biophysics journal : EBJ · 2026Article
- Machine Learning-Based Modeling of Olfactory Receptors in Their Inactive State: Human OR51E2 as a Case Study.Journal of chemical information and modeling · 2023Article
- pyGOMoDo: GPCRs modeling and docking with python.Bioinformatics (Oxford, England) · 2023Article
- Inhibiting a promiscuous GPCR: iterative discovery of bitter taste receptor ligands.Cellular and molecular life sciences : CMLS · 2023Article
- BitterMatch: recommendation systems for matching molecules with bitter taste receptors.Journal of cheminformatics · 2022Article
- Functional molecular switches of mammalian G protein-coupled bitter-taste receptors.Cellular and molecular life sciences : CMLS · 2021Article
- Bitter Taste and Olfactory Receptors: Beyond Chemical Sensing in the Tongue and the Nose.The Journal of membrane biology · 2021Article
- Understanding and Controlling Food Protein Structure and Function in Foods: Perspectives from Experiments and Computer Simulations.Annual review of food science and technology · 2020Review
- Hybrid MM/CG Webserver: Automatic Set Up of Molecular Mechanics/Coarse-Grained Simulations for Human G Protein-Coupled Receptor/Ligand Complexes.Frontiers in molecular biosciences · 2020Article
- Dual binding mode of "bitter sugars" to their human bitter taste receptor target.Scientific reports · 2019Article
- Beyond the Flavour: The Potential Druggability of Chemosensory G Protein-Coupled Receptors.International journal of molecular sciences · 2019Review
- Open-Boundary Molecular Mechanics/Coarse-Grained Framework for Simulations of Low-Resolution G-Protein-Coupled Receptor-Ligand Complexes.Journal of chemical theory and computation · 2019Article
- Understanding Ligand Binding to G-Protein Coupled Receptors Using Multiscale Simulations.Frontiers in molecular biosciences · 2019Review
- Toward the Identification of Extra-Oral TAS2R Agonists as Drug Agents for Muscle Relaxation Therapies via Bioinformatics-Aided Screening of Bitter Compounds in Traditional Chinese Medicine.Frontiers in physiology · 2019Article
- Allosteric sodium binding cavity in GPR3: a novel player in modulation of Aβ production.Scientific reports · 2018Article
- Independent Evolution of Strychnine Recognition by Bitter Taste Receptor Subtypes.Frontiers in molecular biosciences · 2018Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human G-protein coupled receptors (hGPCRs) constitute a large and highly pharmaceutically relevant membrane receptor superfamily. About half of the hGPCRs' family members are chemosensory receptors, involved in bitter taste and olfaction, along with a variety of other physiological processes. Hence these receptors constitute promising targets for pharmaceutical intervention. Molecular modeling has been so far the most important tool to get insights on agonist binding and receptor activation. Here we investigate both aspects by bioinformatics-based predictions across all bitter taste and odorant receptors for which site-directed mutagenesis data are available. First, we observe that state-of-the-art homology modeling combined with previously used docking procedures turned out to reproduce only a limited fraction of ligand/receptor interactions inferred by experiments. This is most probably caused by the low sequence identity with available structural templates, which limits the accuracy of the protein model and in particular of the side-chains' orientations. Methods which transcend the limited sampling of the conformational space of docking may improve the predictions. As an example corroborating this, we review here multi-scale simulations from our lab and show that, for the three complexes studied so far, they significantly enhance the predictive power of the computational approach. Second, our bioinformatics analysis provides support to previous claims that several residues, including those at positions 1.50, 2.50, and 7.52, are involved in receptor activation.
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