Development and validation of a pharmacophore-based QSAR model for the prediction of CNS activity
| Autor: | Rafael Gozalbes, Eric Nicolai, Dragos Horvath, Nicolas Froloff, Frédérique Barbosa |
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| Rok vydání: | 2008 |
| Předmět: |
Pharmacology
Central Nervous System Quantitative structure–activity relationship Validation study Chemistry Organic Chemistry Drug Evaluation Preclinical Discriminant Analysis Quantitative Structure-Activity Relationship Computational biology 3d descriptors Linear discriminant analysis Biochemistry Combinatorial chemistry In vitro binding Blood-Brain Barrier Drug Discovery Molecular Medicine Learning set Cns activity General Pharmacology Toxicology and Pharmaceutics Pharmacophore |
| Zdroj: | ChemMedChem. 4(2) |
| ISSN: | 1860-7187 |
| Popis: | A QSAR model aimed at predicting central nervous system (CNS) activity was developed based on the structure-activity relationships of compounds from an in-house database of "drug-like" molecules. These compounds were initially identified as "CNS-active" or "CNS-inactive", and pharmacophore 3D descriptors were calculated from multiple conformations for each structure. A linear discriminant analysis (LDA) was performed on this structure-activity matrix, and this QSAR model was able to correctly classify approximately 80 % in both a learning set and a validation set. For validation purposes, the LDA model was applied to compounds for which the blood-brain barrier (BBB) penetration was known, and all of them were correctly predicted. The model was also applied to 960 other in-house compounds for which in vitro binding tests were performed on 20 receptors known to be present at the CNS level, and a high correlation was observed between compounds predicted as CNS-active and experimental hits. Finally, the model was also applied to a set of 700 structures with known CNS activity or inactivity randomly chosen from public sources, and more than 70 % of the compounds were correctly classified, including novel CNS chemotypes. These results demonstrate the applicability of the model to novel chemical structures and its usefulness for designing original CNS-focused compound libraries. |
| Databáze: | OpenAIRE |
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