深度学习设计肽的纳米二氧化硅仿生合成及其抗紫外线应用

IF 6.8 Q1 AUTOMATION & CONTROL SYSTEMS

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-08-18 DOI:10.1002/aisy.202470037

Yuexuan Shu, Jiwei Chen, Beibei Xu, Zhengchang Liu, Hao Zheng, Fan Zhang, Weiqi Fu

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引用次数: 0

摘要

仿生合成在第 2300467 号文章中，傅蔚琦及其合作者利用机器学习技术设计了具有硅化功能的多肽。受自然界精美的纳米二氧化硅结构的启发，基于抗菌肽迁移学习建立了一个深度学习模型，并输入了从硅藻中收集的大量硅化肽，实现了纳米二氧化硅的生物仿生合成。新设计的硅化肽可促进新型生物传感器和药物输送系统的开发。[图片由陈吉伟和夏梦生提供] 。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Biomimetic Synthesis of Nanosilica by Deep Learning-Designed Peptides and Its Anti-UV Application

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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.]

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来源期刊

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)

CiteScore

1.30

自引率

0.00%

发文量

审稿时长

4 weeks