A meticulous analysis of these fit values revealed that there was a good correlation between experimentally known activity values and fit values generated by 144217-65-2 pharmacophore mapping. Thus, the result of this validation technique clearly indicates that the selected ligand and structure-based pharmacophore models have the capability to single out most active inhibitors form less active chymase inhibitors. To further validate representative pharmacophore models and demonstrate their efficiency, SB_Model1, SB_Model2, SB_ Model4, and LB_Model were used as 3D queries to screen the chemical databases like Maybridge and Chembridge which consist of 59 652 and 50 000 compounds, respectively. Prior to multiple pharmacophore-based virtual screening experiments, both databases were transformed to druglike databases by Prepare Ligands and ADMET JNJ-26481585 chemical information Descriptors protocols of DS. After preparation of druglike databases, all four pharmacophore models were subjected to screening of these druglike databases. For SB_Model4 which holds six features, Maximum omitted feature was set to 1 and for all other three models it was set to 0. The retrieved database hits were then ranked by their fit scores and the sorted list of hit compounds was analyzed to generate the final hits for each pharmacophore model. The hits acquired by the structure-based pharmacophore models with fit values above 2.0 were considered as potential hits and were reserved for further inspection. For LB_Model, fit value was set to3.5. The numbers of final hit compounds predicted by each of the four pharmacophore models from both databases are summarized in Table 4. It is observed that even for the same target, the hits retrieved by diverse pharmacophore models are quite distinguished from each other hence signifying that different pharmacophore models may show assorted output in virtual screening experiments. However, there were few common hits which were retrieved by more than one pharmacophore models. In order to decipher the proportion of common hits between various models, the overlap segment of the hit compounds obtained by each pair of two diverse pharmacophore models was evaluated. Analysis revealed that ratio of common hits among all four pharmacophore was between 18 and 32% thus s
