Jak2 inhibitor – a jackpot for pharmaceutical industries: a comprehensive computational method in the discovery of new potent Jak2 inhibitors

Abstract

A potent Jak2 inhibitor could solve numerous diseases including hypertension and cardiovascular diseases, myeloproliferative neoplasms, polycythemia vera, essential thrombocythemia, primary myelofibrosis, psoriasis and rheumatoid arthritis. So, identifying potent Jak2 inhibitors is of great interest to researchers and pharmaceutical companies. Virtual screening and molecular docking are important tools for structure based drug discovery but selecting an appropriate method to calculate the electrostatic potential is critical. In this study, four semi empirical (AM1, RM1, PM3, and MNDO) and two empirical (DFT, HF) charges were investigated for their performance on the prediction of docking pose using Glide XP. The result shows that AM1 has the best charge model for our study. Further, we performed a 3D-quantitative structure–activity relationship (3D-QSAR) study of 76 decaene derivatives. Since 3D-QSAR methods are known to be highly sensitive to ligand conformation and alignment method, we did a comparative 3D-QSAR study of AM1 charge docked pose alignment based QSAR (structure based) and pharmacophore based QSAR. We found a better QSAR model in the structure based method. Hence, the results clearly demonstrate that selecting an appropriate method to calculate the electrostatic potential for docking studies and a good alignment of the ligand for 3D-QSAR is critical. Finally, extensive pharmacophore and e-pharmacophore based virtual screening followed by subsequent docking studies identified 27 lead molecules which could be potent Jak2 inhibitors.