Characterization of the dynamic events of GPCRs by automated computational simulations.
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Computational approaches for modeling GPCR dimerizationGPCR-ModSim: A comprehensive web based solution for modeling G-protein coupled receptorsComputational prediction of alanine scanning and ligand binding energetics in G-protein coupled receptorsStructural and functional analysis of a platelet-activating lysophosphatidylcholine of Trypanosoma cruziOn the modularity of the intrinsic flexibility of the µ opioid receptor: a computational studyStructural and energetic effects of A2A adenosine receptor mutations on agonist and antagonist bindingThe GPR139 reference agonists 1a and 7c, and tryptophan and phenylalanine share a common binding site.The role of a sodium ion binding site in the allosteric modulation of the A(2A) adenosine G protein-coupled receptor.Expanding the horizons of G protein-coupled receptor structure-based ligand discovery and optimization using homology models.Pyrazin-2(1H)-ones as a novel class of selective A3 adenosine receptor antagonists.Multiscale design of coarse-grained elastic network-based potentials for the μ opioid receptor.Characterization of Ligand Binding to GPCRs Through Computational Methods.
P2860
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P2860
Characterization of the dynamic events of GPCRs by automated computational simulations.
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article científic
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article scientifique
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articol științific
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articolo scientifico
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artigo científico
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artigo científico
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artigo científico
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artikel ilmiah
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artículo científico
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Characterization of the dynamic events of GPCRs by automated computational simulations.
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Characterization of the dynamic events of GPCRs by automated computational simulations.
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prefLabel
Characterization of the dynamic events of GPCRs by automated computational simulations.
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P2860
P356
P1476
Characterization of the dynamic events of GPCRs by automated computational simulations.
@en
P2093
David Rodríguez
Xabier Bello
P2860
P304
P356
10.1042/BST20120287
P577
2013-02-01T00:00:00Z