Abstract
Involvement of Insulin-like growth factor-1 receptor (IGF-1R) in carcinogenesis has led to the development of new cancer therapies. But due to the very high degree of homology among IGF-1R and insulin receptor, these drugs are known to inhibit insulin receptor to a significant degree, leading to hyperglycemia and the concomitant diabetic complications. Thus, our aim was to explore safe IGF-1R targeting agent with lesser side effects by means of structure-based pharmacophore modelling and docking approach. High affinity compounds for IGF-1R were searched among a database of chemical structures comprising 9,127 approved drugs, chemical isolates from traditional medicinal herbs, and regulated chemicals, termed SWEETLEAD. Seven different pharmacophore models and a merged pharmacophore model were generated using seven different inactive crystal structures of IGF-1R. Pharmacophore-based screening yielded overall 5,842 hits. Afterwards, all these hit compounds were docked to the inactive form of IGF-1R using docking and scoring protocols. The best pose was further evaluated based on the existence of key residues for antagonist binding in its vicinity which retrieved 28 hits. After final evaluations based on S-score, 9 hits were revealed. Although the experimental validation of these compounds are lacking, computational methods predicts them as strong binders. Further experimental validation of these compounds will confirm this in silico study results and their potential role in treatment of cancer with high IGF-1R expression.
