Focus on Human Monoamine Transporter Selectivity. New Human DAT and NET Models, Experimental Validation, and SERT Affinity Exploration.
ACS Chem Neurosci
; 11(20): 3214-3232, 2020 10 21.
Article
em En
| MEDLINE
| ID: mdl-32991141
The most commonly used antidepressant drugs are the serotonin transporter inhibitors. Their effects depend strongly on the selectivity for a single monoamine transporter compared to other amine transporters or receptors, and the selectivity is roughly influenced by the spatial protein structure. Here, we provide a computational study on three human monoamine transporters, i.e., DAT, NET, and SERT. Starting from the construction of hDAT and hNET models, whose three-dimensional structure is unknown, and the prediction of the binding pose for 19 known inhibitors, 3D-QSAR models of three human transporters were built. The training set variability, which was high in structure and activity profile, was validated using a set of in-house compounds. Results concern more than one aspect. First of all, hDAT and hNET three-dimensional structures were built, validated, and compared to the hSERT one; second, the computational study highlighted the differences in binding site arrangement statistically correlated to inhibitor selectivity; third, the profiling of new inhibitors pointed out a conservation of the inhibitory activity trend between rabbit and human SERT with a difference of about 1 order of magnitude; fourth, binding and functional studies confirmed 4-(benzyloxy)-4-phenylpiperidine 20a-d and 21a-d as potent SERT inhibitors. In particular, one of the compounds (compound 20b) revealed a higher affinity for SERT than paroxetine in human platelets.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Inibidores Seletivos de Recaptação de Serotonina
/
Proteínas da Membrana Plasmática de Transporte de Norepinefrina
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Proteínas da Membrana Plasmática de Transporte de Serotonina
Tipo de estudo:
Prognostic_studies
Limite:
Animals
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Humans
Idioma:
En
Revista:
ACS Chem Neurosci
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Itália