title: Quantifying conformational changes in GPCRs: glimpse of a common functional mechanism.
abstract: BACKGROUND
  G-protein-coupled receptors (GPCRs) are important drug targets and a better understanding of their molecular mechanisms would be desirable. The crystallization rate of GPCRs has accelerated in recent years as techniques have become more sophisticated, particularly with respect to Class A GPCRs interacting with G-proteins. These developments have made it possible for a quantitative analysis of GPCR geometrical features and binding-site conformations, including a statistical comparison between Class A GPCRs in active (agonist-bound) and inactive (antagonist-bound) states.
  
  
  RESULTS
  Here we implement algorithms for the analysis of interhelical angles, distances, interactions and binding-site volumes in the transmembrane domains of 25 Class A GPCRs (7 active and 18 inactive). Two interhelical angles change in a statistically significant way between average inactive and active states: TM3-TM6 (by -9°) and TM6-TM7 (by +12°). A third interhelical angle: TM5-TM6 shows a trend, changing by -9°. In the transition from inactive to active states, average van der Waals interactions between TM3 and TM7 significantly increase as the average distance between them decreases by >2 Å. Average H-bonding between TM3 and TM6 decreases but is seemingly compensated by an increase in H-bonding between TM5 and TM6. In five Class A GPCRs, crystallized in both active and inactive states, increased H-bonding of agonists to TM6 and TM7, relative to antagonists, is observed. These protein-agonist interactions likely favour a change in the TM6-TM7 angle, which creates a narrowing in the binding pocket of activated receptors and an average ~200 Å(3) reduction in volume.
  
  
  CONCLUSIONS
  In terms of similar conformational changes and agonist binding pattern, Class A GPCRs appear to share a common mechanism of activation, which can be exploited in future drug development.
authors.affiliation: Laboratory of Molecular Neuropharmacology and Bioinformatics, Institut de Neurociències and Unitat de Bioestadística, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain. james.dalton@uab.es.
authors.forename: James A R
authors.initials: JA
authors.lastname: Dalton
authors.affiliation: Laboratory of Molecular Neuropharmacology and Bioinformatics, Institut de Neurociències and Unitat de Bioestadística, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain. isaias.lans@uab.es.
authors.forename: Isaias
authors.initials: I
authors.lastname: Lans
authors.affiliation: Laboratory of Molecular Neuropharmacology and Bioinformatics, Institut de Neurociències and Unitat de Bioestadística, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain. jesus.giraldo@uab.es.
authors.forename: Jesús
authors.initials: J
authors.lastname: Giraldo
mesh_terms: D058666:Adrenergic beta-2 Receptor Agonists / Q000494:pharmacology; D058672:Adrenergic beta-2 Receptor Antagonists / Q000494:pharmacology; D001665:Binding Sites; D020134:Catalytic Domain; D003198:Computer Simulation; D006801:Humans; D006860:Hydrogen Bonding; D008024:Ligands; D008958:Models, Molecular; D011485:Protein Binding; D011487:Protein Conformation; D018343:Receptors, Adrenergic, beta-2 / Q000737:chemistry* / Q000378:metabolism; D043562:Receptors, G-Protein-Coupled / Q000737:chemistry* / Q000378:metabolism*
chemical_list: D058666:Adrenergic beta-2 Receptor Agonists; D058672:Adrenergic beta-2 Receptor Antagonists; D008024:Ligands; D018343:Receptors, Adrenergic, beta-2; D043562:Receptors, G-Protein-Coupled