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Molecular dynamics of dopamine at the D2 receptor.

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TLDR
The receptor model suggests that protonated ligands are attracted to the binding site by electrostatic forces and that proptonated agonists may induce conformational changes in the receptor, leading to G-protein activation, by increasing the electrostatic potentials near Asp-80.
Abstract
A three-dimensional model of the dopamine D2 receptor, assumed to be a target of antipsychotic drug action, was constructed from its amino acid sequence. The model was based on structural similarities within the super-family of guanine nucleotide-binding regulatory (G) protein-coupled neuroreceptors and has seven alpha-helical transmembrane segments that form a central core with a putative ligand-binding site. The space between two residues postulated to be involved in agonist binding, Asp-80 and Asn-390, perfectly accommodated an anti-dopamine molecule. Molecular electrostatic potentials were mainly negative on the synaptic side of the receptor model and around aspartate residues lining the central core and positive in the cytoplasmic domains. The docking of dopamine into a postulated binding site was examined by molecular dynamics simulation. The protonated amino group became oriented toward negatively charged aspartate residues in helix 2 and helix 3, whereas the dopamine molecule fluctuated rapidly between different anti and gauche conformations during the simulation. The receptor model suggests that protonated ligands are attracted to the binding site by electrostatic forces and that protonated agonists may induce conformational changes in the receptor, leading to G-protein activation, by increasing the electrostatic potentials near Asp-80.

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Citations
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Journal ArticleDOI

Sequence alignment of the G-protein coupled receptor superfamily.

TL;DR: This work has compiled and aligned the 74 unique amino acid sequences published to date and review the present understanding of the structural motifs contributing to ligand binding and G-protein coupling.
Journal ArticleDOI

Dopamine receptors: Molecular biology, biochemistry and behavioural aspects

TL;DR: Progress has been made in understanding the function of DA-containing discrete brain nuclei and the functional consequence of the DA's interaction with other neurotransmitters, and some of the latest advances in these various areas are explored.
Journal ArticleDOI

Modelling G-protein-coupled receptors for drug design.

TL;DR: Molecular modelling and site-directed mutagenesis have played an important role in increasing understanding of the structural basis of drug action at these receptors, and how these techniques can be used within a drug-design programme.
Journal ArticleDOI

Pharmacokinetics and Pharmacodynamics of Clozapine

TL;DR: Careful patient selection and monitoring are required when clozapine therapy is used in patients with schizophrenia because the drug does possess significant binding affinity for different dopamine receptors, with recent evidence supporting binding to the D4 receptor subtype.
References
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Journal ArticleDOI

A simple method for displaying the hydropathic character of a protein

TL;DR: A computer program that progressively evaluates the hydrophilicity and hydrophobicity of a protein along its amino acid sequence has been devised and its simplicity and its graphic nature make it a very useful tool for the evaluation of protein structures.
Journal ArticleDOI

A comprehensive set of sequence analysis programs for the VAX

TL;DR: A group of programs that will interact with each other has been developed for the Digital Equipment Corporation VAX computer using the VMS operating system.
Journal ArticleDOI

A general method applicable to the search for similarities in the amino acid sequence of two proteins

TL;DR: A computer adaptable method for finding similarities in the amino acid sequences of two proteins has been developed and it is possible to determine whether significant homology exists between the proteins to trace their possible evolutionary development.
Journal ArticleDOI

Prediction of protein antigenic determinants from amino acid sequences.

TL;DR: The method was developed using 12 proteins for which extensive immunochemical analysis has been carried out and subsequently was used to predict antigenic determinants for the following proteins, finding that the prediction success rate depended on averaging group length.
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