.png){kind=icon}
.png){kind=icon}
Return
DiffModeler: large macromolecular structure modeling for cryo-EM maps using a diffusion model
.png){kind=icon}
PRE
AI
DOI：10.1038/s41592-024-02479-0.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
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;.
Journal
IF:
32.1
Papers:
7.2K
Citations:
12.7W
