Discovery of High-Affinity Cannabinoid Receptors Ligands through a 3D-QSAR Ushered by Scaffold-Hopping Analysis.

ABSTRACT: Two 3D quantitative structure⁻activity relationships (3D-QSAR) models for predicting Cannabinoid receptor 1 and 2 (CB₁ and CB₂) ligands have been produced by way of creating a practical tool for the drug-design and optimization of CB₁ and CB₂ ligands. A set of 312 molecules have been used to build the model for the CB₁ receptor, and a set of 187 molecules for the CB₂ receptor. All of the molecules were recovered from the literature among those possessing measured Ki values, and Forge was used as software. The present model shows high and robust predictive potential, confirmed by the quality of the statistical analysis, and an adequate descriptive capability. A visual understanding of the hydrophobic, electrostatic, and shaping features highlighting the principal interactions for the CB₁ an

SUBMITTER: Floresta G 

PROVIDER: S-EPMC6225167 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature