Structural basis of ZAP-70 activation upon phosphorylation of tyrosines 315, 319 and 493
https://doi.org/10.29235/1561-8323-2023-67-1-38-40
Abstract
ZAP-70 (Zeta-chain-Associated Protein kinase 70) is a key kinase in the regulation of the adaptive immune response. Zap-70 acts by binding its SH2-domains to the T-cell-associated CD3ζ protein, thus transmitting a T-cell activation signal induced by the interaction of Major Histocompatibility Complex with T-cell Receptor. It has been established that for ZAP-70 kinase activation, the phosphorylation of Tyr315, Tyr319, and Tyr493 is required, however the mechanisms are unclear. In the present study, we use the tools of structural modeling to elucidate the ZAP-70 activation mechanisms.
Supporting agencies: The work has been sponsored by the Belarusian Republican Foundation for Fundamental Research (Grant Б20-120).
About the Authors
V. A. Urban
Institute of Biophysics and Cell Engineering of the National Academy
of Sciences of Belarus
Belarus
Belarus
Urban Viktar A. – Junior Researcher
27, Akademicheskaya Str., 220072,
Minsk
V. G. Veresov
Institute of Biophysics and Cell Engineering of the National Academy
of Sciences of Belarus
Russian Federation
Russian Federation
Veresov Valery G. – D. Sc. (Biology), Chief Researcher
27, Akademicheskaya Str., 220072,
Minsk
References
1. Mariuzza R. A., Agnihotri P., Orban J. The structural basis of T-cell receptor (TCR) activation: An enduring enigma. Journal of Biological Chemistry, 2020, vol. 295, no. 4, pp. 914–925. https://doi.org/10.1074/jbc.rev119.009411
2. Deindl S., Kadlecek T. A., Brdicka T., Cao X., Weiss A., Kuriyan J. Structural basis for the inhibition of tyrosine kinase activity of ZAP-70. Cell, 2007, vol. 129, no. 4, pp. 735–746. https://doi.org/10.1016/j.cell.2007.03.039
3. Yan Q., Barros T., Visperas P. R., Deindl S., Kadlecek T. A., Weiss A., Kuriyan J. Structural basis for activation of ZAP-70 by phosphorylation of the SH2-kinase linker. Molecular and Cellular Biology, 2013, vol. 33, no. 11, pp. 2188–2201. https://doi.org/10.1128/mcb.01637-12
4. Roy A., Kucukural A., Zhang Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nature Protocols, 2010, vol. 5, no. 4, pp. 725–738. https://doi.org/10.1038/nprot.2010.5
5. Heo L., Park H., Seok C. GalaxyRefine: Protein structure refinement driven by side-chain repacking. Nucleic Acids Research, 2013, vol. 41, no. W1, pp. W384–W388. https://doi.org/10.1093/nar/gkt458
6. Margreitter C., Petrov D., Zagrovic B. Vienna-PTM web server: a toolkit for MD simulations of protein post-translational modifications. Nucleic Acids Research, 2013, vol. 41, no. W1, pp. W422–W426. https://doi.org/10.1093/nar/gkt416
7. Pronk S., Páll S., Schulz R., Larsson P., Bjelkmar P., Apostolov R., Shirts M. R., Smith J. C., Kasson P. M., van der Spoel D., Hess B., Lindahl E. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics, 2013, vol. 29, no. 7, pp. 845–854. https://doi.org/10.1093/bioinformatics/btt055
8. Petrov D., Margreitter C., Grandits M., Oostenbrink C., Zagrovic B. A Systematic Framework for Molecular Dynamics Simulations of Protein Post-Translational Modifications. PLOS Computational Biology, 2013, vol. 9, no. 7, art. e1003154. https://doi.org/10.1371/journal.pcbi.1003154
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