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Understanding Ligand Binding to G-Protein Coupled Receptors Using Multiscale Simulations

Human G-protein coupled receptors (GPCRs) convey a wide variety of extracellular signals inside the cell and they are one of the main targets for pharmaceutical intervention. Rational drug design requires structural information on these receptors; however, the number of experimental structures is sc...

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Autores principales: Alfonso-Prieto, Mercedes, Navarini, Luciano, Carloni, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510167/
https://www.ncbi.nlm.nih.gov/pubmed/31131282
http://dx.doi.org/10.3389/fmolb.2019.00029
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author Alfonso-Prieto, Mercedes
Navarini, Luciano
Carloni, Paolo
author_facet Alfonso-Prieto, Mercedes
Navarini, Luciano
Carloni, Paolo
author_sort Alfonso-Prieto, Mercedes
collection PubMed
description Human G-protein coupled receptors (GPCRs) convey a wide variety of extracellular signals inside the cell and they are one of the main targets for pharmaceutical intervention. Rational drug design requires structural information on these receptors; however, the number of experimental structures is scarce. This gap can be filled by computational models, based on homology modeling and docking techniques. Nonetheless, the low sequence identity across GPCRs and the chemical diversity of their ligands may limit the quality of these models and hence refinement using molecular dynamics simulations is recommended. This is the case for olfactory and bitter taste receptors, which constitute the first and third largest GPCR groups and show sequence identities with the available GPCR templates below 20%. We have developed a molecular dynamics approach, based on the combination of molecular mechanics and coarse grained (MM/CG), tailored to study ligand binding in GPCRs. This approach has been applied so far to bitter taste receptor complexes, showing significant predictive power. The protein/ligand interactions observed in the simulations were consistent with extensive mutagenesis and functional data. Moreover, the simulations predicted several binding residues not previously tested, which were subsequently verified by carrying out additional experiments. Comparison of the simulations of two bitter taste receptors with different ligand selectivity also provided some insights into the binding determinants of bitter taste receptors. Although the MM/CG approach has been applied so far to a limited number of GPCR/ligand complexes, the excellent agreement of the computational models with the mutagenesis and functional data supports the applicability of this method to other GPCRs for which experimental structures are missing. This is particularly important for the challenging case of GPCRs with low sequence identity with available templates, for which molecular docking shows limited predictive power.
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spelling pubmed-65101672019-05-24 Understanding Ligand Binding to G-Protein Coupled Receptors Using Multiscale Simulations Alfonso-Prieto, Mercedes Navarini, Luciano Carloni, Paolo Front Mol Biosci Molecular Biosciences Human G-protein coupled receptors (GPCRs) convey a wide variety of extracellular signals inside the cell and they are one of the main targets for pharmaceutical intervention. Rational drug design requires structural information on these receptors; however, the number of experimental structures is scarce. This gap can be filled by computational models, based on homology modeling and docking techniques. Nonetheless, the low sequence identity across GPCRs and the chemical diversity of their ligands may limit the quality of these models and hence refinement using molecular dynamics simulations is recommended. This is the case for olfactory and bitter taste receptors, which constitute the first and third largest GPCR groups and show sequence identities with the available GPCR templates below 20%. We have developed a molecular dynamics approach, based on the combination of molecular mechanics and coarse grained (MM/CG), tailored to study ligand binding in GPCRs. This approach has been applied so far to bitter taste receptor complexes, showing significant predictive power. The protein/ligand interactions observed in the simulations were consistent with extensive mutagenesis and functional data. Moreover, the simulations predicted several binding residues not previously tested, which were subsequently verified by carrying out additional experiments. Comparison of the simulations of two bitter taste receptors with different ligand selectivity also provided some insights into the binding determinants of bitter taste receptors. Although the MM/CG approach has been applied so far to a limited number of GPCR/ligand complexes, the excellent agreement of the computational models with the mutagenesis and functional data supports the applicability of this method to other GPCRs for which experimental structures are missing. This is particularly important for the challenging case of GPCRs with low sequence identity with available templates, for which molecular docking shows limited predictive power. Frontiers Media S.A. 2019-05-03 /pmc/articles/PMC6510167/ /pubmed/31131282 http://dx.doi.org/10.3389/fmolb.2019.00029 Text en Copyright © 2019 Alfonso-Prieto, Navarini and Carloni. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Alfonso-Prieto, Mercedes
Navarini, Luciano
Carloni, Paolo
Understanding Ligand Binding to G-Protein Coupled Receptors Using Multiscale Simulations
title Understanding Ligand Binding to G-Protein Coupled Receptors Using Multiscale Simulations
title_full Understanding Ligand Binding to G-Protein Coupled Receptors Using Multiscale Simulations
title_fullStr Understanding Ligand Binding to G-Protein Coupled Receptors Using Multiscale Simulations
title_full_unstemmed Understanding Ligand Binding to G-Protein Coupled Receptors Using Multiscale Simulations
title_short Understanding Ligand Binding to G-Protein Coupled Receptors Using Multiscale Simulations
title_sort understanding ligand binding to g-protein coupled receptors using multiscale simulations
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510167/
https://www.ncbi.nlm.nih.gov/pubmed/31131282
http://dx.doi.org/10.3389/fmolb.2019.00029
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