Computer-Aided Drug Design For Screening Novel c-Met Kinase Inhibitors

Abstract

Cancer is a broad group of second-leading diseases after cardiac disorder. It is the highest cause of death globally, accounting for approximately 10M deaths by 2020” and 19.3 million cases are registered globally. c-Met is a proto-oncogenic transmembrane receptor for its natural ligand Hepatocyte Growth Factor (HGF). c-Met and HGF are highly overexpressed in different cancers such as metastatic colorectal cancer, endometrium, solid tumours including Small and NSCLC, bladder and ovary cancer, prostate, and breast cancer. c-Met after binding with its natural ligand HGF, it activates a wide range of different intracellular signalling pathways, including those involved in cell proliferation, motility, cell survival and adhesion. c Met has the most characteristics and plays a crucial role in treating cancers as potential therapeutic agents. The discovery of c-Met inhibitors is small molecules that inhibit phosphorylation by interaction with the intracellular tyrosine kinase domain. FDA approved small molecules of c-Met kinase inhibitors Crizotinib, Cabozantinib, Imatinib, Foretinib etc., for the treatment of cancer. While several small molecules are in a clinical trial, such as Capmatinib, Altiratinib, Sitravatinib etc., for use as a single agent or combination with chemotherapy. Diverse structures are taken for the structure-based pharmacophore generation, and the best model contains one hydrophobic, one aromatic, one donor atom and one acceptor site. This model was validated through the GH method. After Pharmacophore Validation, around 8,00,000 compounds will be subjected to Virtual Screening. Molecules were retrieved from the different databases, and these Molecules were subjected to docking. After that, molecules that were showing a good docking score were subjected to ADMET Property Prediction.