Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 15, 04 December 2023
Open
Access | Article
HER2 targeted structure prediction and analysis based on artificial intelligence
* Author to whom correspondence should be addressed.
Abstract
HER2 is a crucial marker in cancer diagnosis and targeted treatment. Accurate structure prediction and analysis of HER2 are vital for understanding its function and designing effective therapies. Our study proposes an end-to-end and artificial intelligence approach that uses deep learning frameworks to predict and analyze HER2’s structure. Using top-notch machine learning algorithms, we trained a model on a comprehensive dataset of HER2 sequences and structures. The model showed impressive accuracy in forecasting HER2’s tertiary structure, helping identify potential functional areas and critical interaction points. Moreover, our analysis provided new insights into HER2’s structural changes and stability, revealing potential regulation mechanisms for targeted therapies. We used advanced bioinformatics tools to validate our predictions and ensure their reliability. This research marks a significant step in understanding HER2’s molecular structure and lays a solid groundwork for personalized cancer treatments. By harnessing artificial intelligence, our study offers a promising path for precise medicine and targeted treatments for HER2-overexpressing cancers.
Keywords
Alphafold2, Protein Structure Prediction, Deep Learning, HER2
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Modern Medicine and Global Health
- ISBN (Print)
- 978-1-83558-193-3
- ISBN (Online)
- 978-1-83558-194-0
- Published Date
- 04 December 2023
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/15/20240444
- Copyright
- 04 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited