Computational insights into ligand-induced G protein and ß-arrestin signaling of the dopamine D1 receptor.
J Comput Aided Mol Des
; 37(5-6): 227-244, 2023 06.
Article
en En
| MEDLINE
| ID: mdl-37060492
The dopamine D1 receptor (D1R), is a class A G protein coupled-receptor (GPCR) which has been a promising drug target for psychiatric and neurological disorders such as Parkinson's disease (PD). Previous studies have suggested that therapeutic effects can be realized by targeting the ß-arrestin signaling pathway of dopamine receptors, while overactivation of the G protein-dependent pathways leads to side effects, such as dyskinesias. Therefore, it is highly desirable to develop a D1R ligand that selectively regulates the ß-arrestin pathway. Currently, most D1R agonists are signaling-balanced and stimulate both G protein and ß-arrestin pathways, with a few reports of G protein biased ligands. However, identification and characterization of ß-arrestin biased D1R agonists has been a challenge thus far. In this study, we implemented Gaussian accelerated molecular dynamics (GaMD) simulations to provide valuable computational insights into the possible underlying molecular mechanism of the different signaling properties of two catechol and two non-catechol D1R agonists that are either G protein biased or signaling-balanced. Dynamic network analysis further identified critical residues in the allosteric signaling network of D1R for each ligand at different conformational or binding states. Some of these residues are crucial for G protein or arrestin signals of GPCRs based on previous studies. Finally, we provided a molecular design strategy which can be utilized by medicinal chemists to develop potential ß-arrestin biased D1R ligands. The proposed hypotheses are experimentally testable and can guide the development of safer and more effective medications for a variety of CNS disorders.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Transducción de Señal
/
Proteínas de Unión al GTP
Idioma:
En
Revista:
J Comput Aided Mol Des
Asunto de la revista:
BIOLOGIA MOLECULAR
/
ENGENHARIA BIOMEDICA
Año:
2023
Tipo del documento:
Article
País de afiliación:
Estados Unidos
Pais de publicación:
Países Bajos