Virtual Screening of CB2 Receptor Agonists from Bayesian Network and High-Throughput Docking: Structural Insights into Agonist-Modulated GPCR Features
Version of Record online: 28 MAR 2013
© 2012 John Wiley & Sons A/S
Chemical Biology & Drug Design
Volume 81, Issue 4, pages 442–454, April 2013
How to Cite
Renault, N., Laurent, X., Farce, A., El Bakali, J., Mansouri, R., Gervois, P., Millet, R., Desreumaux, P., Furman, C. and Chavatte, P. (2013), Virtual Screening of CB2 Receptor Agonists from Bayesian Network and High-Throughput Docking: Structural Insights into Agonist-Modulated GPCR Features. Chemical Biology & Drug Design, 81: 442–454. doi: 10.1111/cbdd.12095
- Issue online: 28 MAR 2013
- Version of Record online: 28 MAR 2013
- Accepted manuscript online: 6 DEC 2012 02:34PM EST
- Received 29 August 2012, revised 13 November 2012 and accepted for publication 21 November 2012
Figure S2. 2D representation of referenceCB2 ligands.
Figure S5. Identity and purity of the 13 hits from virtual screening.
Figure S6. Top 10 Bayesian features of hits 1, 2 and 3.
Table S1. Chemical and biological clustering ofreference CB2 ligands.
Table S2. Discrimination efficiency of the Bayesian models.
Table S3. Virtual hits (compounds1–13).
|cbdd12095_sm_TableS1-S3-FigS1-S2.pdf||1882K||Supporting info item|
Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.