Revolutionizing biomolecular structure determination with artificial intelligence

被引：0

作者：

Han Li ^{[1
]}

Yipin Lei ^{[2
]}

Jianyang Zeng ^{[3
]}

机构：

[1] School of Mathematical Sciences and LPMC,Nankai University

[2] Institute for Interdisciplinary Information Sciences, Tsinghua University

[3] School of Engineering,Westlake

来源：

National Science Review | 2024年 / 11卷 / 11期

关键词：

D O I：

暂无

中图分类号：

Q617 [生物结构理论]; TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

<正>Determination of biomolecular structures is crucial for understanding biological functions and designing novel therapeutics. Numerous artificial intelligence based approaches have been developed for modeling specific types of biomolecules, aiming to improve the cost and time efficiency of wet-lab experiments. Recently, the advanced deep-learning-based methods such as Rose TTAFold All-Atom(RFAA) and AlphaFold3 have emerged for generalized biomolecular structure modeling.

引用

页码：26 / 29

页数：4

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