4-(6-FENIL-7H-[1,2,4]TRIAZOLO[3,4-B][1,3,4]TIADIAZIN-3-IL)ANILIN ATSIL HOSILALARI 5BK8 VA 9EHA OQSILLARINING TAHMINIY INGIBITORI
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Ushbu tadqiqotda SHP2 oqsil-tirozin fosfatazaga nisbatan yangi biologik faol birikmalarning bog'lanish xususiyatlari molekulyar
docking usuli yordamida o‘rganildi. Tadqiqot uchun Protein Data Bank bazasidan olingan 5BK8 kristall strukturasi tanlandi va
BIOVIA Discovery Studio dasturida docking hisob-kitoblariga tayyorlandi. Ligandlarning uch o'lchovli tuzilmalari Avogadro
dasturida yaratilib, geometrik optimallashtirish amalga oshirildi. Molekulyar docking hisob-kitoblari AutoDock Vina dasturida
bajarildi va ligandlarning bog'lanish energiyasi hamda oqsilning faol markazidagi aminokislotalar bilan o‘zaro ta’siri baholandi.
Olingan natijalar tadqiq qilingan birikmalarning SHP2 oqsiliga nisbatan istiqbolli inhibitor bo‘lish imkoniyatini ko‘rsatdi hamda
kelgusida eksperimental tadqiqotlar o‘tkazish uchun ilmiy asos yaratdi.
1. Grossmann K.S., Rosário M., Birchmeier C., Birchmeier W. The tyrosine phosphatase Shp2 in development and cancer //
Advances in Cancer Research. – 2010. – Vol. 106. – P. 53–89. – DOI: 10.1016/S0065-230X(10)06002-1.
2. Chen Y.N.P., LaMarche M.J., Chan H.M. et al. Allosteric inhibition of SHP2 phosphatase inhibits cancers driven by receptor
tyrosine kinases // Nature. – 2016. – Vol. 535, No. 7610. – P. 148–152. – DOI: 10.1038/nature18621.
3. Nichols R.J., Haderk F., Stahlhut C. et al. RMC-4550, a selective SHP2 inhibitor, suppresses RAS signaling // Cancer
Research. – 2018. – Vol. 78. – P. 3381–3393.
4. Hof P., Pluskey S., Dhe-Paganon S., Eck M.J., Shoelson S.E. Crystal structure of the tyrosine phosphatase SHP-2 // Cell. –
1998. – Vol. 92, No. 4. – P. 441–450. – DOI: 10.1016/S0092-8674(00)80938-1.
5. Fodor M., Price E., Wang P. et al. Dual allosteric inhibition of SHP2 phosphatase // ACS Chemical Biology. – 2018. – Vol.
13, No. 3. – P. 647–656. – DOI: 10.1021/acschembio.7b00980.
6. Xie J., Si X., Gu S. et al. Discovery of novel SHP2 inhibitors by virtual screening // Bioorganic Chemistry. – 2021. – Vol.
110. – Art. 104777. – DOI: 10.1016/j.bioorg.2021.104777.
7. Trott O., Olson A.J. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient
optimization, and multithreading // Journal of Computational Chemistry. – 2010. – Vol. 31, No. 2. – P. 455–461. – DOI:
10.1002/jcc.21334.
8. Forli S., Huey R., Pique M.E., Sanner M.F., Goodsell D.S., Olson A.J. Computational protein–ligand docking and virtual
drug screening with AutoDock // Nature Protocols. – 2016. – Vol. 11, No. 5. – P. 905–919. – DOI: 10.1038/nprot.2016.051.
9. Pagadala N.S., Syed K., Tuszynski J. Software for molecular docking: A review // Biophysical Reviews. – 2017. – Vol. 9,
No. 2. – P. 91–102. – DOI: 10.1007/s12551-016-0247-1.
10. Hanwell M.D., Curtis D.E., Lonie D.C., Vandermeersch T., Zurek E., Hutchison G.R. Avogadro: An advanced semantic
chemical editor, visualization, and analysis platform // Journal of Cheminformatics. – 2012. – Vol. 4. – Art. 17. – DOI:
10.1186/1758-2946-4-17.
11. BIOVIA. Discovery Studio Visualizer User Guide. – San Diego: Dassault Systèmes BIOVIA, 2021.
12. Lionta E., Spyrou G., Vassilatis D.K., Cournia Z. Structure-based virtual screening for drug discovery: Principles,
applications and recent advances // Current Topics in Medicinal Chemistry. – 2014. – Vol. 14, No. 16. – P. 1923–1938. –
DOI: 10.2174/1568026614666140929124445.
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