• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

40个盲法蛋白质结构预测的综合分析。

A comprehensive analysis of 40 blind protein structure predictions.

作者信息

Samudrala Ram, Levitt Michael

机构信息

Department of Microbiology, University of Washington, School of Medicine, Seattle, WA 98195, USA.

出版信息

BMC Struct Biol. 2002 Aug 1;2:3. doi: 10.1186/1472-6807-2-3.

DOI:10.1186/1472-6807-2-3
PMID:12150712
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC122083/
Abstract

BACKGROUND

We thoroughly analyse the results of 40 blind predictions for which an experimental answer was made available at the fourth meeting on the critical assessment of protein structure methods (CASP4). Using our comparative modelling and fold recognition methodologies, we made 29 predictions for targets that had sequence identities ranging from 50% to 10% to the nearest related protein with known structure. Using our ab initio methodologies, we made eleven predictions for targets that had no detectable sequence relationships.

RESULTS

For 23 of these proteins, we produced models ranging from 1.0 to 6.0 A root mean square deviation (RMSD) for the Calpha atoms between the model and the corresponding experimental structure for all or large parts of the protein, with model accuracies scaling fairly linearly with respect to sequence identity (i.e., the higher the sequence identity, the better the prediction). We produced nine models with accuracies ranging from 4.0 to 6.0 A Calpha RMSD for 60-100 residue proteins (or large fragments of a protein), with a prediction accuracy of 4.0 A Calpha RMSD for residues 1-80 for T110/rbfa.

CONCLUSIONS

The areas of protein structure prediction that work well, and areas that need improvement, are discernable by examining how our methods have performed over the past four CASP experiments. These results have implications for modelling the structure of all tractable proteins encoded by the genome of an organism.

摘要

背景

我们全面分析了在蛋白质结构预测方法关键评估第四次会议(CASP4)上可获得实验答案的40次盲预测结果。使用我们的比较建模和折叠识别方法,我们对与已知结构的最接近相关蛋白质的序列同一性在50%至10%之间的目标进行了29次预测。使用我们的从头算方法,我们对没有可检测到序列关系的目标进行了11次预测。

结果

对于其中23种蛋白质,我们生成的模型在蛋白质的全部或大部分区域中,模型与相应实验结构之间的Cα原子的均方根偏差(RMSD)范围为1.0至6.0埃,模型准确性与序列同一性大致呈线性比例关系(即,序列同一性越高,预测越好)。对于60 - 100个残基的蛋白质(或蛋白质的大片段),我们生成了9个准确性范围为4.0至6.0埃Cα RMSD的模型,对于T110/rbfa的1 - 80位残基,预测准确性为4.0埃Cα RMSD。

结论

通过检查我们的方法在过去四次CASP实验中的表现,可以辨别出蛋白质结构预测中表现良好的领域和需要改进的领域。这些结果对于模拟生物体基因组编码的所有可处理蛋白质的结构具有启示意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/b0371c1d8613/1472-6807-2-3-6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/1f4d1fa7c34f/1472-6807-2-3-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/717b158304ff/1472-6807-2-3-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/087219a44686/1472-6807-2-3-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/98f9ab865ab3/1472-6807-2-3-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/eb54f63a772e/1472-6807-2-3-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/b0371c1d8613/1472-6807-2-3-6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/1f4d1fa7c34f/1472-6807-2-3-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/717b158304ff/1472-6807-2-3-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/087219a44686/1472-6807-2-3-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/98f9ab865ab3/1472-6807-2-3-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/eb54f63a772e/1472-6807-2-3-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54ea/122083/b0371c1d8613/1472-6807-2-3-6.jpg

相似文献

1
A comprehensive analysis of 40 blind protein structure predictions.40个盲法蛋白质结构预测的综合分析。
BMC Struct Biol. 2002 Aug 1;2:3. doi: 10.1186/1472-6807-2-3.
2
Fully automated ab initio protein structure prediction using I-SITES, HMMSTR and ROSETTA.使用I-SITES、HMMSTR和ROSETTA进行全自动从头算蛋白质结构预测。
Bioinformatics. 2002;18 Suppl 1:S54-61. doi: 10.1093/bioinformatics/18.suppl_1.s54.
3
TOUCHSTONE II: a new approach to ab initio protein structure prediction.试金石二号:从头开始预测蛋白质结构的新方法。
Biophys J. 2003 Aug;85(2):1145-64. doi: 10.1016/S0006-3495(03)74551-2.
4
Tertiary structure predictions on a comprehensive benchmark of medium to large size proteins.对中大型蛋白质综合基准进行三级结构预测。
Biophys J. 2004 Oct;87(4):2647-55. doi: 10.1529/biophysj.104.045385.
5
Can molecular dynamics simulations help in discriminating correct from erroneous protein 3D models?分子动力学模拟能否有助于区分正确与错误的蛋白质三维模型?
BMC Bioinformatics. 2008 Jan 7;9:6. doi: 10.1186/1471-2105-9-6.
6
Protein structure prediction of CASP5 comparative modeling and fold recognition targets using consensus alignment approach and 3D assessment.使用一致性比对方法和三维评估对CASP5比较建模与折叠识别目标进行蛋白质结构预测。
Proteins. 2003;53 Suppl 6:410-7. doi: 10.1002/prot.10548.
7
Protein structure validation by generalized linear model root-mean-square deviation prediction.基于广义线性模型均方根偏差预测的蛋白质结构验证。
Protein Sci. 2012 Feb;21(2):229-38. doi: 10.1002/pro.2007. Epub 2012 Jan 4.
8
A further leap of improvement in tertiary structure prediction in CASP13 prompts new routes for future assessments.在 CASP13 中,三级结构预测的进一步改进促使未来评估有了新的途径。
Proteins. 2019 Dec;87(12):1100-1112. doi: 10.1002/prot.25787. Epub 2019 Aug 7.
9
Ab initio modeling of small proteins by iterative TASSER simulations.通过迭代TASSER模拟对小蛋白质进行从头建模。
BMC Biol. 2007 May 8;5:17. doi: 10.1186/1741-7007-5-17.
10
Modeling structurally variable regions in homologous proteins with rosetta.使用Rosetta对同源蛋白中的结构可变区域进行建模。
Proteins. 2004 May 15;55(3):656-77. doi: 10.1002/prot.10629.

引用本文的文献

1
Exploring Polypharmacology in Drug Discovery and Repurposing Using the CANDO Platform.利用CANDO平台探索药物发现与药物再利用中的多药理学
Curr Pharm Des. 2016;22(21):3109-23. doi: 10.2174/1381612822666160325121943.
2
Unbiased, scalable sampling of protein loop conformations from probabilistic priors.从概率先验中对蛋白质环构象进行无偏、可扩展的采样。
BMC Struct Biol. 2013;13 Suppl 1(Suppl 1):S9. doi: 10.1186/1472-6807-13-S1-S9. Epub 2013 Nov 8.
3
Homo-dimerization and ligand binding by the leucine-rich repeat domain at RHG1/RFS2 underlying resistance to two soybean pathogens.

本文引用的文献

1
Identification of amino acids in the Dr adhesin required for binding to decay-accelerating factor.鉴定Dr黏附素中与衰变加速因子结合所需的氨基酸。
Mol Microbiol. 2002 Jul;45(2):439-52. doi: 10.1046/j.1365-2958.2002.03022.x.
2
Prediction targets of CASP4.CASP4的预测目标。
Proteins. 2001;Suppl 5:8-12. doi: 10.1002/prot.10055.
3
Protein structure prediction and structural genomics.蛋白质结构预测与结构基因组学。
RHG1/RFS2 富含亮氨酸重复域的同源二聚化和配体结合导致对两种大豆病原体的抗性。
BMC Plant Biol. 2013 Mar 15;13:43. doi: 10.1186/1471-2229-13-43.
4
Fast structure similarity searches among protein models: efficient clustering of protein fragments.蛋白质模型间的快速结构相似性搜索:蛋白质片段的高效聚类
Algorithms Mol Biol. 2012 May 29;7(1):16. doi: 10.1186/1748-7188-7-16.
5
Helix-sheet packing in proteins.蛋白质中的螺旋-片层组装。
Proteins. 2010 May 15;78(7):1736-47. doi: 10.1002/prot.22688.
6
A pairwise residue contact area-based mean force potential for discrimination of native protein structure.基于残基对接触面积的平均力势函数用于判别天然蛋白质结构。
BMC Bioinformatics. 2010 Jan 9;11:16. doi: 10.1186/1471-2105-11-16.
7
Prediction of calcium-binding sites by combining loop-modeling with machine learning.通过结合环建模与机器学习预测钙结合位点。
BMC Struct Biol. 2009 Dec 11;9:72. doi: 10.1186/1472-6807-9-72.
8
Selecting high quality protein structures from diverse conformational ensembles.从多样的构象集合中选择高质量蛋白质结构。
Biophys J. 2009 Sep 16;97(6):1728-36. doi: 10.1016/j.bpj.2009.06.046.
9
Protinfo PPC: a web server for atomic level prediction of protein complexes.Protinfo PPC:用于蛋白质复合物原子水平预测的网络服务器。
Nucleic Acids Res. 2009 Jul;37(Web Server issue):W519-25. doi: 10.1093/nar/gkp306. Epub 2009 May 6.
10
Functional group based Ligand binding affinity scoring function at atomic environmental level.基于官能团的原子环境水平配体结合亲和力评分函数。
Bioinformation. 2009;3(6):268-74. doi: 10.6026/97320630003268. Epub 2009 Jan 12.
Science. 2001 Oct 5;294(5540):93-6. doi: 10.1126/science.1065659.
4
Structure prediction meta server.结构预测元服务器。
Bioinformatics. 2001 Aug;17(8):750-1. doi: 10.1093/bioinformatics/17.8.750.
5
Integrated genomic and proteomic analyses of a systematically perturbed metabolic network.对一个系统扰动的代谢网络进行综合基因组和蛋白质组分析。
Science. 2001 May 4;292(5518):929-34. doi: 10.1126/science.292.5518.929.
6
Ab initio protein structure prediction: progress and prospects.从头算蛋白质结构预测:进展与展望。
Annu Rev Biophys Biomol Struct. 2001;30:173-89. doi: 10.1146/annurev.biophys.30.1.173.
7
A network of protein-protein interactions in yeast.酵母中蛋白质-蛋白质相互作用的网络。
Nat Biotechnol. 2000 Dec;18(12):1257-61. doi: 10.1038/82360.
8
Comparative protein structure modeling of genes and genomes.基因与基因组的比较蛋白质结构建模
Annu Rev Biophys Biomol Struct. 2000;29:291-325. doi: 10.1146/annurev.biophys.29.1.291.
9
Decoys 'R' Us: a database of incorrect conformations to improve protein structure prediction.“诱饵”数据库:用于改进蛋白质结构预测的错误构象数据库。
Protein Sci. 2000 Jul;9(7):1399-401. doi: 10.1110/ps.9.7.1399.
10
Constructing side chains on near-native main chains for ab initio protein structure prediction.从头算蛋白质结构预测中在近天然主链上构建侧链。
Protein Eng. 2000 Jul;13(7):453-7. doi: 10.1093/protein/13.7.453.