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Biophysical and pharmacokinetic characterization of a small-molecule inhibitor of RUNX1/ETO tetramerization with anti-leukemic effects
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Resumo(s)
Acute myeloid leukemia (AML) is a malignant disease of immature myeloid cells and the most prevalent acute leukemia among adults. The oncogenic homo-tetrameric fusion protein RUNX1/ETO results from the chromosomal translocation t(8;21) and is found in AML patients. The nervy homology region 2 (NHR2) domain of ETO mediates tetramerization; this oligomerization is essential for oncogenic activity. Previously, we identified the first-in-class small-molecule inhibitor of NHR2 tetramer formation, 7.44, which was shown to specifically interfere with NHR2, restore gene expression down-regulated by RUNX1/ETO, inhibit the proliferation of RUNX1/ETO-depending SKNO-1 cells, and reduce the RUNX1/ETO-related tumor growth in a mouse model. However, no biophysical and structural characterization of 7.44 binding to the NHR2 domain has been reported. Likewise, the compound has not been characterized as to physicochemical, pharmacokinetic, and toxicological properties. Here, we characterize the interaction between the NHR2 domain of RUNX1/ETO and 7.44 by biophysical assays and show that 7.44 interferes with NHR2 tetramer stability and leads to an increase in the dimer population of NHR2. The affinity of 7.44 with respect to binding to NHR2 is Klig = 3.75 ± 1.22 µM. By NMR spectroscopy combined with molecular dynamics simulations, we show that 7.44 binds with both heteroaromatic moieties to NHR2 and interacts with or leads to conformational changes in the N-termini of the NHR2 tetramer. Finally, we demonstrate that 7.44 has favorable physicochemical, pharmacokinetic, and toxicological properties. Together with biochemical, cellular, and in vivo assessments, the results reveal 7.44 as a lead for further optimization towards targeted therapy of t(8;21) AML.
Descrição
Funding Information: This work was supported by a grant by the state of North-Rhine Westphalia and the European Fonds for Regional Development EFRE.NRW 2014-2020 to HG. We are grateful for computational support and infrastructure provided by the “Zentrum für Informations- und Medientechnologie” (ZIM) at the Heinrich Heine University Düsseldorf and the computing time provided by the John von Neumann Institute for Computing (NIC) to HG on the supercomputer JUWELS at Jülich Supercomputing Centre (JSC) (user ID: HKF7, VSK33). Financial support by Deutsche Forschungsgemeinschaft (DFG) through funds (INST 208/704-1 FUGG to HG) to purchase the hybrid computer cluster used in this study, an Emmy-Noether- and Heisenberg fellowship to ME (ET 103/2 and ET 103/5), and GRK 2158/2 (project number 270650915) to HG is gratefully acknowledged. Publisher Copyright: © 2022, The Author(s).
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General SDG 3 - Good Health and Well-being