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Understanding G Protein Selectivity of Dopamine Receptors Using Computational Methods
Author(s) -
Portillo Jennifer,
Abrol Ravinder,
Sakkiah Suguna
Publication year - 2019
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2019.33.1_supplement.477.9
Subject(s) - g protein coupled receptor , d1 like receptor , receptor , dopamine receptor , dopamine , dopamine receptor d2 , d2 like receptor , microbiology and biotechnology , chemistry , dopamine receptor d3 , biology , neuroscience , biochemistry
Dopamine is important in physiological processes associated with the rewards and pleasure system. Its function is facilitated by five G Protein – Coupled Receptors (GPCRs). The coupling that occurs between the dopamine receptor and G protein dictates the signaling cascade. The dopamine receptors D1 and D5 couple to the G s protein while the dopamine receptors D2, D3, and D4 couple to the G i protein. Dysregulation of the dopamine receptors can lead to neuropsychiatric disorders such as schizophrenia. These disorders are difficult to treat due to the side‐effects that transpire. Understanding the coupling that occurs between the dopamine receptors and the G proteins can further assist with the development of pharmaceutical drugs by helping to alleviate some of the side‐effects. Using computational biophysical methods, the coupling between the dopamine receptors and G protein is being studied to understand the structural mechanisms observed in G protein selectivity of these receptors. The dopamine receptor structures for D1 and D2 in complex with the two G proteins (G s and G i ) have been relaxed in the membrane environment. A structural analysis of those complexes in combination with structural bioinformatics methods has elucidated receptor residues playing a role in the G protein coupling, which has led to the design of receptor mutants with altered G protein selectivities. These mutants are now being characterized by computational biophysical methods before they will be tested in biochemical assays for altered G protein preferences. Support or Funding Information National Institutes of Health (NIH) Building Infrastructure Leading to Diversity (BUILD) #5TL4GM118977 This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .