G-Protein-Coupled Receptor Affinity Prediction Based on the Use of a Profiling Dataset: QSAR Design, Synthesis, and Experimental Validation
| Autor: | Frédérique Barbosa, Frédéric Revah, Dragos Horvath, Laurent Coussy, Rafael Gozalbes, Marie-France Paugam, Eric Nicolai, Catherine Rolland |
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| Rok vydání: | 2005 |
| Předmět: |
Models
Molecular Quantitative structure–activity relationship Receptors Peptide Molecular model Chemistry Stereochemistry Quantitative Structure-Activity Relationship Experimental validation Computational biology Ligands Receptors G-Protein-Coupled Radioligand Assay Design synthesis Drug Design Drug Discovery Combinatorial Chemistry Techniques Molecular Medicine Receptors Chemokine hormones hormone substitutes and hormone antagonists G protein-coupled receptor |
| Zdroj: | Journal of Medicinal Chemistry. 48:6563-6574 |
| ISSN: | 1520-4804 0022-2623 |
| DOI: | 10.1021/jm0500673 |
| Popis: | A QSAR model accounting for "average" G-protein-coupled receptor (GPCR) binding was built from a large set of experimental standardized binding data (1939 compounds systematically tested over 40 different GPCRs) and applied to the design of a library of "GPCR-predicted" compounds. Three hundred and sixty of these compounds were randomly selected and tested in 21 GPCR binding assays. Positives were defined by their ability to inhibit by more than 70% the binding of reference compounds at 10 microM. A 5.5-fold enrichment in positives was observed when comparing the "GPCR-predicted" compounds with 600 randomly selected compounds predicted as "non-GPCR" from a general collection. The model was efficient in predicting strongest binders, since enrichment was greater for higher cutoffs. Significant enrichment was also observed for peptidic GPCRs and receptors not included to develop the QSAR model, suggesting the usefulness of the model to design ligands binding with newly identified GPCRs, including orphan ones. |
| Databáze: | OpenAIRE |
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