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Computer-Aided Design and Biological Evaluation of Diazaspirocyclic D4R Antagonists.
Jones, Caleb A H; Brown, Benjamin P; Schultz, Daniel C; Engers, Julie; Kramlinger, Valerie M; Meiler, Jens; Lindsley, Craig W.
Afiliação
  • Jones CAH; Warren Center for Neuroscience Drug Discovery, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, United States.
  • Brown BP; Department of Pharmacology, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, United States.
  • Schultz DC; Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37232, United States.
  • Engers J; Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37232, United States.
  • Kramlinger VM; Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37232, United States.
  • Meiler J; Center for Applied AI in Protein Dynamics, Vanderbilt University, Nashville, Tennessee 37232, United States.
  • Lindsley CW; Warren Center for Neuroscience Drug Discovery, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, United States.
ACS Chem Neurosci ; 15(12): 2396-2407, 2024 Jun 19.
Article em En | MEDLINE | ID: mdl-38847395
ABSTRACT
Parkinson's disease (PD) is a neurodegenerative disorder characterized by the progressive loss of dopaminergic neurons in the substantia nigra, resulting in motor dysfunction. Current treatments are primarily centered around enhancing dopamine signaling or providing dopamine replacement therapy and face limitations such as reduced efficacy over time and adverse side effects. To address these challenges, we identified selective dopamine receptor subtype 4 (D4R) antagonists not previously reported as potential adjuvants for PD management. In this study, a library screening and artificial neural network quantitative structure-activity relationship (QSAR) modeling with experimentally driven library design resulted in a class of spirocyclic compounds to identify candidate D4R antagonists. However, developing selective D4R antagonists suitable for clinical translation remains a challenge.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Desenho Assistido por Computador / Relação Quantitativa Estrutura-Atividade Limite: Animals / Humans Idioma: En Revista: ACS Chem Neurosci Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Desenho Assistido por Computador / Relação Quantitativa Estrutura-Atividade Limite: Animals / Humans Idioma: En Revista: ACS Chem Neurosci Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos