Chemical genetics and genomics and drug discovery. Highlights from the Society for Medicines Research symposium held Thursday March 10, 2005, in London, United Kingdom.
ABSTRACT The SMR Symposium Chemical Genetics and Genomics: What Are They and Are They Helping Drug Discovery was held on March 10, 2005 at the National Heart and Lung Institute, Imperial College London. The conference program brought together an international line up of speakers representing academia, biotechnology and large pharmaceutical companies to discuss a variety of drug discovery strategies, falling under the umbrella terminology Chemical Genomics and Genetics. Highlights of the meeting are discussed.
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ABSTRACT: The cannabinoid receptor subtype 2 (CB2) is a promising therapeutic target for treatment of chronic neuropathic pain, neuronal disorders, autoimmune diseases, osteoporosis, gliomas and other tumors of immune origin. The recent withdrawal of Rimonabant, which targets at another closely related cannabinoid receptor (CB1), accentuates the importance of selectivity for the development of CB2 ligands in order to minimize their side effects on CB1 receptor. In our previous report, LiCABEDS (Ligand Classifier of Adaptively Boosting Ensemble Decision Stumps) was developed as a generic ligand classification algorithm for the prediction of categorical molecular properties. Here, we further extended the application of LiCABEDS to modeling cannabinoid ligand selectivity with molecular fingerprints as descriptors. The performance of LiCABEDS was systematically compared with another popular classification algorithm, support vector machine (SVM), according to prediction precision and recall rate. In addition, the examination of LiCABEDS models revealed the difference in structure diversity of CB1 and CB2 selective ligands. The structure insight from data mining could be useful for the design of novel cannabinoid lead compounds. More importantly, the potential of LiCABEDS was demonstrated through successful identification of newly synthesized CB2 selective compounds.Journal of Chemical Information and Modeling 01/2013; · 4.30 Impact Factor