Identification of novel off targets of baricitinib and tofacitinib by machine learning with a focus on thrombosis and viral infection
Sci Rep. 2022 doi: 10.1038/s41598-022-11879-1
Established machine learning approaches, based on ligand similarity, identified previously unknown off-target interactions of baricitinib and tofacitinib, and adds to the evidence that these JAK inhibitors are promiscuous binders, and highlight the potential for repurposing.
Computational approaches, combined with in vitro studies, can be used to predict and validate the potential for an approved drug to interact with additional (often unwanted) targets, and identify potential safety-related concerns.
To this end, Faquetti, et al. investigate if the currently unexplained thrombotic and viral infection risk with JAK inhibitors may be a result of an off-target effect.