Earticle

초록

영어

Breast cancer continues to pose a substantial worldwide health challenge, thereby requiring the development of innovative strategies to discover new therapeutic interventions. Signal Transducer and Activator of Transcription 3 (STAT-3) has been identified as a significant factor in the development of several types of cancer, including breast cancer. This is primarily attributed to its diverse functions in promoting tumour formation and conferring resistance to therapeutic interventions. This study presents an in silico drug repositioning approach that focuses on identifying specific inhibitors of STAT-3 for the purpose of treating breast cancer. We initially examined the structural and functional attributes of STAT-3, thereby elucidating its crucial involvement in cellular signalling cascades. A comprehensive virtual screening was performed on a diverse collection of drugs that have been approved by the FDA from zinc15 database. Various computational techniques, including molecular docking, cross docking, and cDFT analysis, were utilised in order to prioritise potential candidates. This prioritisation was based on their predicted binding energies and outer molecular orbital reactivity. The findings of our study have unveiled a Dihydroergotamine and Paritaprevir that have been approved by the FDA and exhibit considerable promise as selective inhibitors of STAT-3. In conclusion, the utilisation of our in silico drug repositioning approach presents a prompt and economically efficient method for the identification of potential compounds that warrant subsequent experimental validation as selective STAT-3 inhibitors in the context of breast cancer. The present study highlights the considerable potential of employing computational strategies to expedite the drug discovery process. Moreover, it provides valuable insights into novel avenues for targeted therapeutic interventions in the context of breast cancer treatment.

목차

Abstract
1. Introduction
2. Materials and method
2.1 Preparing Ligands and the Target
2.2 Selection of Binding Site and Molecular docking:
2.3 Cross docking:
2.4 cDFT:
3. Results and Discussion
3.1 Molecular docking:
3.2 Cross docking:
3.3 cDFT analysis:
4. Conclusion
References
Table
Fig

키워드

저자

• Sruthy Sathish [ Computational Biology Laboratory, Department of Genetic Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur-603203, Tamil Nadu, India ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  통합자연과학논문집(구 조선자연과학논문집) [Journal of Integrative Natural Science]

• 간기

  계간

• pISSN

  2005-1042

• 수록기간

  2008~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 405 DDC 505