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ABSTRACT: Protein Tyrosine Phosphatase 1B (PTP-1B) is one of theimportant targets in the treatment of diabetes and obesity.They play a very important role in cellular signaling withinand between cells. The best pharmacophore hypothesis(Hypo 1), consisting of four features, namely, one hydrogen-bond acceptor (HBA), one hydrophobic point (HY),and two ring aromatics (RA), has a correlation coefficientof 0.961, a root mean square deviation (RMSD) of 0.885,and a cost difference of 62.436, suggesting that a highlypredictive pharmacophore model was successfully obtained.A chemical feature based pharmacophore modelhas been generated from known PTP-1B inhibitors (25training set compounds) by HypoGen module implementedin CATALYST software. The top ranked hypothesis(Hypo1) contained four chemical feature types such ashydrogen-bond acceptor (HA), hydrophobic aromatic(HY), and two ring aromatic (RA) features. Hypo1 wasfurther validated by 125 test set molecules giving a correlationcoefficient of 0.905 between experimental and estimatedactivity. This was also validated using CatScramblemethod. Thus, the Hypo1 was exploited for searching newlead compounds over chemical compounds in Medichemdatabase and then the selected compounds were screenedbased on restriction estimated activity. Finally, we obtained30 new lead candidates and the one best highly active compoundstructure was selected as a lead compound. The resultsdemonstrate that hypothesis derived in this studycould be considered to be a useful and reliable tool in identifyingstructurally diverse compounds with desired biologicalactivity.
Journal of Proteomics & Bioinformatics. 01/2010;