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Deciphering conformational selectivity in the A2A adenosine G protein-coupled receptor by free energy simulations
- Source :
- PLoS Computational Biology, 17(11), PLoS Computational Biology, PLoS Computational Biology, Vol 17, Iss 11, p e1009152 (2021)
- Publication Year :
- 2021
- Publisher :
- Public Library of Science (PLoS), 2021.
-
Abstract
- Transmembranal G Protein-Coupled Receptors (GPCRs) transduce extracellular chemical signals to the cell, via conformational change from a resting (inactive) to an active (canonically bound to a G-protein) conformation. Receptor activation is normally modulated by extracellular ligand binding, but mutations in the receptor can also shift this equilibrium by stabilizing different conformational states. In this work, we built structure-energetic relationships of receptor activation based on original thermodynamic cycles that represent the conformational equilibrium of the prototypical A2A adenosine receptor (AR). These cycles were solved with efficient free energy perturbation (FEP) protocols, allowing to distinguish the pharmacological profile of different series of A2AAR agonists with different efficacies. The modulatory effects of point mutations on the basal activity of the receptor or on ligand efficacies could also be detected. This methodology can guide GPCR ligand design with tailored pharmacological properties, or allow the identification of mutations that modulate receptor activation with potential clinical implications.<br />Author summary The design of new ligands as chemical modulators of G protein-coupled receptors (GPCRs) has benefited considerably during the last years of advances in both the structural and computational biology disciplines. Within the last area, the use of free energy calculation methods has arisen as a computational tool to predict ligand affinities to explain structure-affinity relationships and guide lead optimization campaigns. However, our comprehension of the structural determinants of ligands with different pharmacological profile is scarce, and knowledge of the chemical modifications associated with an agonistic or antagonistic profile would be extremely valuable. We herein report an original implementation of the thermodynamic cycles associated with free energy perturbation (FEP) simulations, to mimic the conformational equilibrium between active and inactive GPCRs, and establish a framework to describe pharmacological profiles as a function of the ligands selectivity for a given receptor conformation. The advantage of this method resides into its simplicity of use, and the only consideration of active and inactive conformations of the receptor, with no simulation of the transitions between them. This model can accurately predict the pharmacological profile of series of full and partial agonists as opposed to antagonists of the A2A adenosine receptor, and moreover, how certain mutations associated with modulation of basal activity can influence this pharmacological profiles, which enables our understanding of such clinically relevant mutations.
- Subjects :
- Models, Molecular
Partial Agonists
Conformational change
Adenosine
Protein Conformation
Ribose
Glycobiology
Ligands
Biochemistry
Medicine and Health Sciences
Biology (General)
Receptor
Free Energy
Bioinformatics (Computational Biology)
Crystallography
Ecology
Organic Compounds
Chemistry
Physics
Monosaccharides
Drugs
Nucleosides
Condensed Matter Physics
Ligand (biochemistry)
Glycosylamines
Adenosine A2 Receptor Antagonists
Computational Theory and Mathematics
Modeling and Simulation
Physical Sciences
Crystal Structure
Thermodynamics
Research Article
Signal Transduction
medicine.drug
Transmembrane Receptors
Adenosine A2 Receptor Agonists
Receptor, Adenosine A2A
QH301-705.5
Carbohydrates
Molecular Dynamics Simulation
Free energy perturbation
Cellular and Molecular Neuroscience
Genetics
medicine
Point Mutation
Solid State Physics
Humans
Molecular Biology
Ecology, Evolution, Behavior and Systematics
G protein-coupled receptor
Pharmacology
Point mutation
Organic Chemistry
Chemical Compounds
Biology and Life Sciences
Proteins
Computational Biology
Cell Biology
Adenosine receptor
Amino Acid Substitution
Mutation
Bioinformatik (beräkningsbiologi)
Biophysics
G Protein Coupled Receptors
Subjects
Details
- ISSN :
- 15537358
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- PLOS Computational Biology
- Accession number :
- edsair.doi.dedup.....2140e01a0a4fe6b35c8fab97cb2fa113