SCUBA-D: a freshly trained diffusion model generates high-quality protein structures

IF 36.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Nature Methods Pub Date : 2024-10-28 DOI:10.1038/s41592-024-02465-6
{"title":"SCUBA-D: a freshly trained diffusion model generates high-quality protein structures","authors":"","doi":"10.1038/s41592-024-02465-6","DOIUrl":null,"url":null,"abstract":"The accuracy of SCUBA-D, a protein backbone structure diffusion model trained independently and orthogonally to existing protein structure prediction networks, is confirmed by the X-ray structures of 16 designed proteins and a protein complex, and by experimental validation of designed heme-binding proteins and Ras-binding proteins.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"21 11","pages":"1990-1991"},"PeriodicalIF":36.1000,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Methods","FirstCategoryId":"99","ListUrlMain":"https://www.nature.com/articles/s41592-024-02465-6","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

The accuracy of SCUBA-D, a protein backbone structure diffusion model trained independently and orthogonally to existing protein structure prediction networks, is confirmed by the X-ray structures of 16 designed proteins and a protein complex, and by experimental validation of designed heme-binding proteins and Ras-binding proteins.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
SCUBA-D:新训练的扩散模型生成高质量的蛋白质结构。
SCUBA-D是一个独立训练的蛋白质骨架结构扩散模型,与现有的蛋白质结构预测网络正交,16个设计蛋白质和一个蛋白质复合物的X射线结构以及设计血红素结合蛋白和Ras结合蛋白的实验验证证实了SCUBA-D的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Nature Methods
Nature Methods 生物-生化研究方法
CiteScore
58.70
自引率
1.70%
发文量
326
审稿时长
1 months
期刊介绍: Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.
期刊最新文献
A benchmarked, high-efficiency prime editing platform for multiplexed dropout screening. First-timers at a huge meeting. Precision mutational scanning: your multipass to the future of genetics. Repurposing large-format microarrays for scalable spatial transcriptomics. A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1