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BioExcel Student Webinar: Coarse-Grained Modeling of Salbutamol and Salmeterol Binding to Beta2-Adrenergic Receptor

Authors: Gil, Cristina;

BioExcel Student Webinar: Coarse-Grained Modeling of Salbutamol and Salmeterol Binding to Beta2-Adrenergic Receptor

Abstract

The beta2-adrenergic receptor (B2AR) belongs to the family of G protein-coupled receptors, one of the major drug targets. G protein-coupled receptors are integral membrane proteins that convert external signals into intracellular responses. Two already known drugs employed in the treatment of several respiratory diseases are salmeterol and salbutamol. They show a high affinity to B2AR, however, their binding pathways have not yet been fully characterized. Along this project we will shed light on the binding process by means of coarse-grained molecular dynamics simulations using the Martini 3.0 force field. This methodology enables us to study the binding pathway of both drugs in an unbiased way. First, we parametrized the new ligands and the target protein according to the Martini 3.0 model. The defined parameters were in good agreement with all-atom simulations and experimental properties. In addition, the analysis of the ligands’ behaviour within different membrane compositions provided fundamental details such as the high membrane affinity of salmeterol indicated by its longer residence time in the membrane compared to salbutamol. The placement of the ligands in their known binding site showed residence times expected for their high affinity to B2AR. Afterwards, a system composed of B2AR embedded in a membrane including multiple ligands in the water phase was simulated. Based on the binding events observed along the different simulation replicas, we will analyze the ligand hot spots on the B2AR surface as well as their binding pathways and affinities.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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