Pharmacophore Based Virtual Screening for Identification of Novel CDK2 Inhibitors

Abstract

CDK2 is one of the most important members of Cyclin-dependent kinases. It is a critical modulator of various oncogenic signaling pathways, and its activity is vital for loss of proliferative control during oncogenesis. This work has focused on developing a pharmacophore model for CDK2 inhibitors by using a dataset of known inhibitors as a pre-filter throughout the virtual screening and docking process. Consequently, the best pharmacophore model was made of one hydrogen bond acceptor, and two aromatic ring features with a high correlation value of 0.906. The validation findings proved out that the selected model can be used as a filter to screen new molecules like Enamine kinase hinge region directed library against CDK2. As a result, 69 hits were subjected to molecular docking studies. Eventually, three compounds (5909, 701 and 8397) scored good interaction energy values and strong molecular interactions. Hence, they were identified as leads for novel CDK2 inhibitors as anticancer drugs.