进入设计蛋白材料的时代

IF 38.5 1区材料科学 Q1 CHEMISTRY, PHYSICAL

Nature Materials Pub Date : 2025-09-30 DOI:10.1038/s41563-025-02372-x

Shuguang Zhang

引用次数: 0

摘要

基于深度学习的生成工具用于设计具有良好定义的定向蛋白质结合相互作用的蛋白质构建块，允许从一小组可重用亚基生成各种可扩展的蛋白质组件。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Entering the age of designer protein materials

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Entering the age of designer protein materials

Deep learning-based generative tools are used to design protein building blocks with well-defined directional protein bonding interactions, allowing for the generation of a variety of scalable protein assemblies from a small set of reusable subunits.

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来源期刊

Nature Materials 工程技术-材料科学：综合

CiteScore

62.20

自引率

0.70%

发文量

221

审稿时长

3.2 months

期刊介绍： Nature Materials is a monthly multi-disciplinary journal aimed at bringing together cutting-edge research across the entire spectrum of materials science and engineering. It covers all applied and fundamental aspects of the synthesis/processing, structure/composition, properties, and performance of materials. The journal recognizes that materials research has an increasing impact on classical disciplines such as physics, chemistry, and biology. Additionally, Nature Materials provides a forum for the development of a common identity among materials scientists and encourages interdisciplinary collaboration. It takes an integrated and balanced approach to all areas of materials research, fostering the exchange of ideas between scientists involved in different disciplines. Nature Materials is an invaluable resource for scientists in academia and industry who are active in discovering and developing materials and materials-related concepts. It offers engaging and informative papers of exceptional significance and quality, with the aim of influencing the development of society in the future.