An In Silico Approach to Uncover Selective JAK1 Inhibitors for Breast Cancer from Life Chemicals Database.

Abstract

JAK1, a key regulator of multiple oncogenic pathways, is a sought-out target, and its expression in immune cells and tumour-infiltrating lymphocytes (TILs) is associated with a favorable prognosis in breast cancer. JAK1 activates IL-6 via ERBB2 receptor tyrosine kinase signalling and promotes metastatic cancer and STAT3 activation in breast cancer cells. Hence, targeting JAK1 in breast cancer is being explored as a potential therapeutic strategy. A comprehensive in silico approach was utilised in this study to identify selective JAK1 inhibitors from the Life chemicals database. First, we utilised an anticancer focussed library and performed molecular docking to screen against JAK1 protein. The top 10 compounds from docking were taken for cross-docking, to assess the selectivity towards JAK1 target. Lipinski's RO5 was checked for eliminating the compounds that violate rules. Toxicity, biological activity and reactivity for the identified best compounds were predicted by Protox-II server, PASS server and cDFT analysis respectively. MD simulations were carried out to examine the stability and dynamic behaviour of the top leads, including the long-term stability of the ligand-receptor complex and any conformational changes. Lastly, the MM/PBSA method was used to determine the binding free energy of the protein-ligand complex. Our in silico approach has yielded a promising set of compounds F2638-0133, F3408-0020 and F5833-7435 with the potential to selectively target JAK1, a critical player in breast cancer progression. The docking, simulation and MM/PBSA results were compared with standard drug abrocitinib. Identified compounds exhibit favorable binding interactions, electronic properties and robust stability profiles compared to standard drug, making them promising leads for further experimental validation.