Virtual screening for Raf-1 kinase inhibitors based on pharmacophore model of substituted ureas

摘要

A three-dimensional (3D) quantitative pharmacophore model was developed from a training set of structurally diverse substituted ureas against Raf-1 kinase, which was well validated to be highly predictive by two methods, namely, test set prediction and cross-validated method. Then a virtual database searching was performed with the pharmacophore model as a 3D query, and the bioactivities of the retrieved hits were predicted by the pharmacophore. Subsequently, molecular docking was carried out on the selected hits whose estimated IC50 were less than 1 μM Finally, 29 hits, which exhibited good estimated activities, high docking scores, similar binding mode to experimentally proven compounds and favorable drug-like properties, were identified as potential leads against Raf-1 kinase. The study may facilitate the discovery and rational design of novel leads with potent inhibitory activity targeting Raf-1 kinase. Softwares used: Catalyst 4.10, Gold 3.0.1