Research Article
Neelakantan Suresh and N. S
Abstract
Protein Tyrosine Phosphatase 1B (PTP-1B) is one of the important targets in the treatment of diabetes and obesity. They play a very important role in cellular signaling within and 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 coefficient of 0.961, a root mean square deviation (RMSD) of 0.885, and a cost difference of 62.436, suggesting that a highly predictive pharmacophore model was successfully obtained. A chemical feature based pharmacophore model has been generated from known PTP-1B inhibitors (25 training set compounds) by HypoGen module implemented in CATALYST software. The top ranked hypothesis (Hypo1) contained four chemical feature types such as hydrogen-bond acceptor (HA), hydrophobic aromatic (HY), and two ring aromatic (RA) features. Hypo1 was further validated by 125 test set molecules giving a correlation coefficient of 0.905 between experimental and estimated activity. This was also validated using CatScramble method. Thus, the Hypo1 was exploited for searching new lead compounds over chemical compounds in Medichem database and then the selected compounds were screened based on restriction estimated activity. Finally, we obtained 30 new lead candidates and the one best highly active compound structure was selected as a lead compound. The results demonstrate that hypothesis derived in this study could be considered to be a useful and reliable tool in identifying structurally diverse compounds with desired biological activity.