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DiffModeler: large macromolecular structure modeling for cryo-EM maps using a diffusion model

delete2024-10-21
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PRE
AI
X
Xiao Wang
H
Han Zhu
G
Genki Terashi
M
Manav Taluja
D
Daisuke Kihara *
DOI:10.1038/s41592-024-02479-0delete
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摘要

摘要

En 中文
Cryogenic electron microscopy (cryo-EM) has now been widely used for determining multichain protein complexes. However, modeling a large complex structure, such as those with more than ten chains, is challenging, particularly when the map resolution decreases. Here we present DiffModeler, a fully automated method for modeling large protein complex structures. DiffModeler employs a diffusion model for backbone tracing and integrates AlphaFold2-predicted single-chain structures for structure fitting. DiffModeler showed an average template modeling score of 0.88 and 0.91 for two datasets of cryo-EM maps of 0-5 & Aring; resolution and 0.92 for intermediate resolution maps (5-10 & Aring;), substantially outperforming existing methodologies. Further benchmarking at low resolutions (10-20 & Aring;) confirms its versatility, demonstrating plausible performance. DiffModeler is a fully automated structure fitting method for modeling large protein complex structures in cryo-EM maps with resolutions up to 15 & Aring;.

期刊

Nature Methods 封面图
Nature Methods
IF:
32.1
论文数:
7.2K
被引数:
12.7W

机构

Purdue University System 封面图
Purdue University System
学者数:
4.0W
论文数: 3.6W
被引数: 66
P
Purdue University
学者数:
2.7W
论文数: 2.1W
被引数: 147
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