Journal of Integrative Natural Science (통합자연과학논문집)

The Basic Science Institute Chosun University (조선대학교 기초과학연구원)
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Identification of STAT5a Inhibitors for Breast Cancer Treatment Through In silico Approach

  • Bavya Chandrasekhar (Department of Genetic Engineering, Computational Biology Lab, School of Bioengineering, SRM Institute of Science and Technology) ;
  • Dona Samuel Karen (Department of Genetic Engineering, Computational Biology Lab, School of Bioengineering, SRM Institute of Science and Technology) ;
  • Veena Jaganivasan (Department of Genetic Engineering, Computational Biology Lab, School of Bioengineering, SRM Institute of Science and Technology)
  • Received : 2023.12.13
  • Accepted : 2024.02.29
  • Published : 2024.03.30
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Abstract

Female breast cancer is the fifth highest cause of mortality. Breast cancer is the most prevalent type of cancer in women globally, while it can also affect men. STAT5A plays a role in its development and progression. Given that activation of STAT5a is frequently linked to the growth and progression of tumors, STAT5a has been identified as a possible target for the therapy of several cancers. STAT5A, in particular, has proven to be overexpressed in various breast cancer cell lines and tumors, and it has been associated to the promotion of tumour cell proliferation and survival. STAT5A inhibition has been shown in vitro and in vivo to reduce the development of breast cancer cells. As a result, we have screened compounds from the FDA database that might serve as potential inhibitors of STAT5a through virtual screening, docking, DFT and MD simulation approaches. The drug Nilotinib has shown promising results inhibiting STAT5a. Further, in-vitro analysis will be carried forward to understand the anti-cancer activity.

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References

  1. Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F., "Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.", CA: A Cancer Journal for Clinicians, Vol. 71, No. 3, pp. 209-249, 2021. https://doi.org/10.3322/caac.21660
  2. Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F., "Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.", CA: A Cancer Journal for Clinicians, Vol. 71, No. 3, pp. 209-249, 2021. https://doi.org/10.3322/caac.21660
  3. Li, Z., Chen, C., Chen, L., Hu, D., Yang, X., Zhuo, W., Chen, Y., Yang, J., Zhou, Y., Mao, M. and Zhang, X., "STAT5a confers doxorubicin resistance to breast cancer by regulating ABCB1.", Frontiers in oncology, p. 2761, 2021.
  4. Pushpakom, S., Iorio, F., Eyers, P.A., Escott, K.J., Hopper, S., Wells, A., Doig, A., Guilliams, T., Latimer, J., McNamee, C. and Norris, A., 2019. Drug repurposing: progress, challenges and recommendations. Nature reviews Drug discovery, Vol. 18, No. 1, pp.41-58, 2019. https://doi.org/10.1038/nrd.2018.168
  5. Liu, X., Gallego, M.I., Smith, G.H., Robinson, G.W. and Hennighausen, L., "Functional rescue of Stat5a-null mammary tissue through the activation of compensating signals including Stat5b.", Cell Growth and Differentiation-Publication American Association for Cancer Research, Vol. 9, No. 9, pp. 795-804, 1998
  6. Tan, S.H. and Nevalainen, M.T., "Signal transducer and activator of transcription 5A/B in prostate and breast cancers.", Endocrine-Related Cancer, Vol. 15, No. 2, p. 367, 2008.
  7. Trott O., Olson A. J., "AutoDockVina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading.", J. Comput. Chem., Vol. 31, No. 2, pp. 455-461, 2010. 10.1002/jcc.21334 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  8. Baba, N. and Akaho, E., "VSDK: Virtual screening of small molecules using AutoDock Vina on Windows platform.", Bioinformation, Vol. 6, No. 10, p. 387, 2011.
  9. Frisch M., Trucks G., Schlegel H., Scuseria G., Robb M., Cheeseman J., et al. (2016). Gaussian 16. (Version Revision B. 01)[Linux]. Wallingford CT: Gaussian. [Google Scholar]
  10. Nagarajan, S.K., Babu, S., Sohn, H. and Madhavan, T., "Molecular-level understanding of the somatostatin receptor 1 (SSTR1)-ligand binding: a structural biology study based on computational methods.", ACS omega, Vol. 5, No. 33, pp. 21145-21161, 2020. https://doi.org/10.1021/acsomega.0c02847
  11. Beveridge, D.L., Barreiro, G., Byun, K.S., Case, D.A., Cheatham, T.E., Dixit, S.B., Giudice, E., Lankas, F., Lavery, R., Maddocks, J.H. and Osman, R., "Molecular dynamics simulations of the 136 unique tetranucleotide sequences of DNA oligonucleotides., I. Research design and results on d (CpG) steps.", Biophysical journal, Vol. 87, No. 6, pp.3799-3813, 2004. https://doi.org/10.1529/biophysj.104.045252