Structure-Based Approach for the Prediction of Mu-opioid Binding Affinity of Unclassified Designer Fentanyl-Like Molecules.
Int J Mol Sci
; 20(9)2019 May 10.
Article
en En
| MEDLINE
| ID: mdl-31083294
ABSTRACT
Three quantitative structure-activity relationship (QSAR) models for predicting the affinity of mu-opioid receptor (OR) ligands have been developed. The resulted models, exploiting the accessibility of the QSAR modeling, generate a useful tool for the investigation and identification of unclassified fentanyl-like structures. The models have been built using a set of 115 molecules using Forge as a software, and the quality was confirmed by statistical analysis, resulting in being effective for their predictive and descriptive capabilities. The three different approaches were then combined to produce a consensus model and were exploited to explore the chemical landscape of 3000 fentanyl-like structures, generated by a theoretical scaffold-hopping approach. The findings of this study should facilitate the identification and classification of new OR ligands with fentanyl-like structures.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Drogas de Diseño
/
Fentanilo
/
Receptores Opioides mu
/
Relación Estructura-Actividad Cuantitativa
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Año:
2019
Tipo del documento:
Article