Ligand and structure-based models for the prediction of ligand-receptor affinities and virtual screenings: Development and application to the beta(2)-adrenergic receptor.

ABSTRACT: In this study, we evaluated the applicability of ligand-based and structure-based models to quantitative affinity predictions and virtual screenings for ligands of the beta(2)-adrenergic receptor, a G protein-coupled receptor (GPCR). We also devised and evaluated a number of consensus models obtained through partial least square regressions, to combine the strengths of the individual components. In all cases, the bioactive conformation of each ligand was derived from molecular docking at the crystal structure of the receptor. We identified the most effective models applicable to the different scenarios, in the presence or in the absence of a training set. For ranking the affinity of closely related analogs when a training set is available, a ligand-based consensus model (LI-CM) seems to be

SUBMITTER: Vilar S 

PROVIDER: S-EPMC2818076 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature