Biomimetic Synthesis of Nanosilica by Deep Learning‐Designed Peptides and Its Anti‐UV Application
Biomimetic Synthesis In article 2300467, Weiqi Fu and co-workers use machine learning techniques to design peptides with silicifying functionality. Inspired by the exquisite nanosilica structures from nature, a deep learning model, based on antimicrobial peptide migration learning, is developed with the inputs of a comprehensive collection of silicifying peptides from diatoms to achieve the biomimetic synthesis of nanosilica. The newly designed silicified peptides could facilitate the development of new biosensors and drug delivery systems. [Image by Jiwei Chen and Mengsheng Xia.]
Authors
- Zhengchang Liu (ORCID: https://orcid.org/0000-0002-8039-0998)
- Yuexuan Shu
- Weiqi Fu (ORCID: https://orcid.org/0000-0002-7368-383X)
- Fan Zhang (ORCID: https://orcid.org/0000-0002-4480-2158)
- Jiwei Chen (ORCID: https://orcid.org/0000-0002-3702-5645)
- Beibei Xu
- Hao Zheng (ORCID: https://orcid.org/0009-0002-8108-5044)
Institutions
- Nanjing Tech University (CN)
- University of Iceland (IS)
- Zhejiang Ocean University (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- Advanced Intelligent Systems
- Published
- 2024-08-01
- DOI
- https://doi.org/10.1002/aisy.202470037
- Citations
- 1
- Primary Topic
- Diatoms and Algae Research
- Type
- article
- Field-Weighted Citation Impact
- 0.17