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Insights into the Role of Asp79(2.50) in beta(2) Adrenergic Receptor Activation from Molecular Dynamics Simulations
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab). Stanford University, USA.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab). Stanford University, USA .
2014 (English)In: Biochemistry, ISSN 0006-2960, E-ISSN 1520-4995, Vol. 53, no 46, 7283-7296 p.Article in journal (Refereed) Published
Abstract [en]

Achieving a molecular-level understanding of G-protein-coupled receptor (GPCR) activation has been a long-standing goal in biology and could be important for the development of novel drugs. Recent breakthroughs in structural biology have led to the determination of high-resolution crystal structures for the beta(2) adrenergic receptor (beta(2)AR) in inactive and active states, which provided an unprecedented opportunity to understand receptor signaling at the atomic level. We used molecular dynamics (MD) simulations to explore the potential roles of ionizable residues in beta(2)AR activation. One such residue is the strongly conserved Asp79(2.50), which is buried in a transmembrane cavity and becomes dehydrated upon beta(2)AR activation. MD free energy calculations based on beta(2)AR crystal structures suggested an increase in the population of the protonated state of Asp79(2.50) upon activation, which may contribute to the experimentally observed pH-dependent activation of this receptor. Analysis of MD simulations (in total >100 mu s) with two different protonation states further supported the conclusion that the protonated Asp79(2.50) shifts the conformation of the beta(2)AR toward more active-like states. On the basis of our calculations and analysis of other GPCR crystal structures, we suggest that the protonation state of Asp(2.50) may act as a functionally important microswitch in the activation of the beta(2)AR and other class A receptors.

Place, publisher, year, edition, pages
2014. Vol. 53, no 46, 7283-7296 p.
National Category
Biological Sciences Theoretical Chemistry
Research subject
Biochemistry towards Bioinformatics
Identifiers
URN: urn:nbn:se:su:diva-111913DOI: 10.1021/bi5008723ISI: 000345551800013OAI: oai:DiVA.org:su-111913DiVA: diva2:778906
Note

AuthorCount:3;

Available from: 2015-01-12 Created: 2015-01-08 Last updated: 2017-12-05Bibliographically approved
In thesis
1. The impact of GPCR structures on understanding receptor function and ligand binding
Open this publication in new window or tab >>The impact of GPCR structures on understanding receptor function and ligand binding
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

G protein-coupled receptors (GPCRs) form the largest superfamily of eukaryotic membrane proteins and are responsible for the action of nearly 30% of all marketed drugs. For a long period, efforts to study these receptors were limited by the paucity of atomic-resolution structural information. Numerous receptors spread across the GPCR superfamily have recently been crystallized, revealing crucial clues about receptor function and ligand recognition. The work in this thesis has primarily focused on using computational techniques to capitalize on this increasing amount of structural information. In papers I, II, and III protocols were developed to identify novel ligands for pharmaceutically important targets from in silico screens of large chemical libraries. In these papers, the fragment-based lead discovery (FBLD) approach was evaluated for GPCR targets using molecular docking screens. The high hit-rates obtained in these studies indicate promise for the use of computational approaches for fragment screening. In paper IV, molecular dynamics was used to identify a possible role for a conserved ionizable residue (Asp792.50) as a protonation switch during the activation process of the β2 adrenergic receptor. Analyses from this paper indicated that this residue could also perform a similar function in other class A GPCRs. Papers V and VI detail the modeling strategy followed during the GPCR Dock 2013 assessment to blindly predict the structure of two serotonin receptor subtypes (5-HT1B and 5-HT2B) bound to ergotamine. The developed ligand-steered homology modeling protocol was largely successful resulting in the best-ranked predictions for the 5-HT1B subtype. It is hoped that the work described in this thesis has highlighted the potential for structure-based computational approaches to identify novel ligands for important pharmaceutical targets and improve understanding of GPCR function.

Place, publisher, year, edition, pages
Stockholm: Department of Biochemistry and Biophysics, Stockholm University, 2016. 56 p.
National Category
Biological Sciences Theoretical Chemistry
Research subject
Biochemistry towards Bioinformatics
Identifiers
urn:nbn:se:su:diva-129879 (URN)978-91-7649-431-8 (ISBN)
Public defence
2016-06-09, William-Olssonsalen, Geovetenskapens hus, Svante Arrhenius väg 8, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript.

Available from: 2016-05-17 Created: 2016-05-02 Last updated: 2017-02-24Bibliographically approved

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