Abstract
In this research, our objective is to build the pharmacophore models for selected target proteins that can identify inhibitors with high biological activities and to execute computer-aided drug design. Human dihydroorotate dehydrogenase (hDHODH) is an enzyme which is strongly correlated with certain cancers and autoimmune and inflammatory diseases. Thromboxane A2 receptor (TP) promotes platelet aggregation when activated by thromboxane A2, but over activation of TP may lead to thrombosis and other cardiovascular diseases. Due to the importance of these two proteins related to many human diseases, we use them as targets to build the hypotheses based on a set of known inhibitors, and then use cost function analysis, Fischer’s randomization and goodness of hit test to validate the quality and the confidence of statistical significance of our models. The results show that our models have excellent prediction ability. According to the crystal structures have been solved or not, we can construct different workflows for hDHODH and TP. Consequently, the pharmacophore model, Lipinski’s Rule-of-Five and CDOCKER docking program were integrated into a workflow for the discovery of potential inhibitor candidates from database. Through these workflows, 155 candidates for hDHODH and 5,621 candidates for TP are retrieved for further study.