Artificial Intelligence designed compound successfully inhibits TRPM7 enzyme domain 3623

Abstract Description The TRPM7 chanzyme represents a unique structure, combining an ion channel covalently fused to a cytosolic α-type serine/threonine kinase. Genetic ablation of TRPM7 leads to embryonic lethality and impaired T cell proliferation in mice. TRPM7 kinase deficient mice are viable but fail to differentiate to proinflammatory TH17 cells, while their differentiation to regulatory Treg cells is not impaired. Moreover, TRPM7 kinase domain plays a crucial role in facilitating gut colonization by alloreactive T cells during acute Graft-versus-Host-Disease (GvHD). This renders the kinase a promising pharmacological target in treating different manifestations of GvHD. Currently, there are neither potent nor specific TRPM7 kinase inhibitors available. Therefore, we used an artificial intelligence (AI) network to identify 96 completely new small molecules predicted to target specifically the TRPM7 kinase. After synthesis, we performed an initial radiometric in vitro screen, which unveiled three potential inhibitors and five potential enhancers of TRPM7 kinase activity. None of them was toxic in Jurkat cells. Notably, compound 11_F effectively blocked phosphorylation of SMAD2, a native TRPM7 kinase substrate, in native system. Besides, compound 11_F also showed a dose-dependent inhibitory effect with an IC50 of 30,5 µM. Summarized, we were able to confirm a theoretical AI screen in vitro and in cellular assay. Next, we evaluate the effect of compound 11_F on T cell differentiation. Funding Sources Supported by German Research Foundation (DFG) - Project ID 239283807 Topic Categories Transplantation Immunology (TRAN)