• 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

模型多肽链中的二级结构形成。

Secondary structure formation in model polypeptide chains.

作者信息

Aszódi A, Taylor W R

机构信息

Laboratory of Mathematical Biology, National Institute for Medical Research, Mill Hill, London, UK.

出版信息

Protein Eng. 1994 May;7(5):633-44. doi: 10.1093/protein/7.5.633.

DOI:10.1093/protein/7.5.633
PMID:8073033
Abstract

Model polypeptide chains were folded into 3-D compact conformations using distance geometry techniques. Interresidue distances were predicted from the hydrophobicity of the monomers and were refined by repeated projections into lower-dimensional spaces. Main-chain hydrogen bond networks were constructed and propagated through the structure by adjusting local conformations to comply with ideal distance constraints around hydrogen bonds. The resulting folds were compact globules with distinct hydrophobic cores and contained secondary structure elements like real protein molecules. Apart from similarity in appearance, several properties of the model chains were also very close to those of native folded polypeptides. The method in its present form can serve as a starting point for the development of a novel structure prediction algorithm.

摘要

使用距离几何技术将模型多肽链折叠成三维紧密构象。根据单体的疏水性预测残基间距离,并通过反复投影到低维空间进行优化。构建主链氢键网络,并通过调整局部构象使其符合氢键周围的理想距离约束,从而在整个结构中传播。生成的折叠结构是具有明显疏水核心的紧密球体,并包含如真实蛋白质分子般的二级结构元件。除了外观相似外,模型链的几个性质也与天然折叠多肽非常接近。目前形式的该方法可作为开发新型结构预测算法的起点。

相似文献

1
Secondary structure formation in model polypeptide chains.模型多肽链中的二级结构形成。
Protein Eng. 1994 May;7(5):633-44. doi: 10.1093/protein/7.5.633.
2
Protein fold refinement: building models from idealized folds using motif constraints and multiple sequence data.蛋白质折叠优化:利用基序约束和多序列数据从理想化折叠构建模型。
Protein Eng. 1993 Aug;6(6):593-604. doi: 10.1093/protein/6.6.593.
3
Molecular dynamics simulations of a beta-hairpin fragment of protein G: balance between side-chain and backbone forces.蛋白质G的β-发夹片段的分子动力学模拟:侧链与主链力之间的平衡
J Mol Biol. 2000 Mar 3;296(4):1091-104. doi: 10.1006/jmbi.2000.3518.
4
Determination of the conformation of folding initiation sites in proteins by computer simulation.通过计算机模拟确定蛋白质折叠起始位点的构象
Proteins. 1995 Oct;23(2):129-41. doi: 10.1002/prot.340230203.
5
Entropy reduction effect imposed by hydrogen bond formation on protein folding cooperativity: evidence from a hydrophobic minimalist model.氢键形成对蛋白质折叠协同性施加的熵降低效应:来自疏水极简模型的证据。
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Nov;72(5 Pt 1):051903. doi: 10.1103/PhysRevE.72.051903. Epub 2005 Nov 1.
6
Global fold determination from a small number of distance restraints.从少量距离约束条件确定全局折叠结构
J Mol Biol. 1995 Aug 11;251(2):308-26. doi: 10.1006/jmbi.1995.0436.
7
Secondary-structure-favored hydrophobic-polar lattice model of protein folding.
Phys Rev E Stat Nonlin Soft Matter Phys. 2001 Oct;64(4 Pt 1):041905. doi: 10.1103/PhysRevE.64.041905. Epub 2001 Sep 20.
8
Calculation of protein backbone geometry from alpha-carbon coordinates based on peptide-group dipole alignment.基于肽基团偶极排列从α-碳坐标计算蛋白质主链几何结构。
Protein Sci. 1993 Oct;2(10):1697-714. doi: 10.1002/pro.5560021015.
9
Protein three-dimensional structure generation with an empirical hydrophobic penalty function.利用经验性疏水惩罚函数生成蛋白质三维结构。
J Mol Graph. 1993 Dec;11(4):222-32, 234. doi: 10.1016/0263-7855(93)80002-9.
10
The origins of protein secondary structure. Effects of packing density and hydrogen bonding studied by a fast conformational search.蛋白质二级结构的起源。通过快速构象搜索研究堆积密度和氢键的影响。
J Mol Biol. 1994 Aug 12;241(2):214-25. doi: 10.1006/jmbi.1994.1490.

引用本文的文献

1
Deep learning for the PSIPRED Protein Analysis Workbench.深度学习在 PSIPRED 蛋白质分析工作台上的应用。
Nucleic Acids Res. 2024 Jul 5;52(W1):W287-W293. doi: 10.1093/nar/gkae328.
2
Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterized proteins.超快的端到端蛋白质结构预测能够实现对未被充分研究的蛋白质的高通量探索。
Proc Natl Acad Sci U S A. 2022 Jan 25;119(4). doi: 10.1073/pnas.2113348119.
3
Automated method to differentiate between native and mirror protein models obtained from contact maps.
从接触图中获得的天然和镜像蛋白模型的自动区分方法。
PLoS One. 2018 May 22;13(5):e0196993. doi: 10.1371/journal.pone.0196993. eCollection 2018.
4
Comparative Protein Structure Modeling Using MODELLER.使用MODELLER进行比较蛋白质结构建模。
Curr Protoc Bioinformatics. 2016 Jun 20;54:5.6.1-5.6.37. doi: 10.1002/cpbi.3.
5
Direct correlation analysis improves fold recognition.直接相关性分析提高了折叠识别能力。
Comput Biol Chem. 2011 Oct 12;35(5):323-32. doi: 10.1016/j.compbiolchem.2011.08.002. Epub 2011 Aug 22.
6
Comparative protein structure modeling using Modeller.使用Modeller进行比较蛋白质结构建模。
Curr Protoc Bioinformatics. 2006 Oct;Chapter 5:Unit-5.6. doi: 10.1002/0471250953.bi0506s15.
7
Signalling mechanisms underlying subversion of the immune response by the filarial nematode secreted product ES-62.丝虫线虫分泌产物ES-62颠覆免疫反应的潜在信号传导机制。
Immunology. 2005 Jul;115(3):296-304. doi: 10.1111/j.1365-2567.2005.02167.x.
8
Protein structure comparison using iterated double dynamic programming.使用迭代双动态规划进行蛋白质结构比较。
Protein Sci. 1999 Mar;8(3):654-65. doi: 10.1110/ps.8.3.654.
9
Random Structural Models for Double Dynamic Programming Score Evaluation.用于双动态规划分数评估的随机结构模型
J Mol Evol. 1997;44(7):174-80. doi: 10.1007/pl00000069.