In-Silico Approach for Identification of The Most Potent JAK Inhibitors as a Possible Treatment for Myelofibrosis

Background: Myelofibrosis is a type of malignancy that is mainly caused by JAK2 gene mutation. This study employed an in silico approach to analyse the binding affinity of five JAK2 inhibitors that were already FDA-approved in order to determine the most effective JAK2 inhibitor to suppress the overstimulating JAK-STATs caused by the mutation Methods: The 3D structure of JAK2 protein was built using the Swiss-Prot Expas and loaded into PyMol to remove the solvent and add the hydrogen atom. On the other hand, five JAK inhibitors including Ruxolitinib, Fedratinib, Momelotinib, Pacritinib, and Ilginatinib (NS-018) were retrieved in 3D conformer from the PubChem NCBI database. The ligands were minimized and combined with the JAK2 protein using PyRx, as well as to be visualized using BIOVE and Castp. Results: The molecular docking analysis showed that Fedratinib has the most negative binding affinity followed by Pacritinib, Ruxolitinib, Ilginitinib, and Momelotinib. By comparing BIOVIA and Castp visualisation results, all JAK2 inhibitors bind to the JAK2 protein Pocket 1 Chain A, whereas Ruxolitinib and Momelotinib have an additional binding to JAK2 protein Pocket 1 Chain B. Conclusion: Fedratinib is the most potent JAK2 inhibitor based on the binding affinity it possesses. Further pharmacology research is required to analyse further the efficacy and safety of the Fedratinib.