• 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

蛋白质折叠动力学的马尔可夫状态模型中玻璃态行为的出现。

Emergence of glass-like behavior in Markov state models of protein folding dynamics.

机构信息

Department of Chemistry, Stanford University, Stanford, California 94305, USA.

出版信息

J Am Chem Soc. 2013 Apr 17;135(15):5501-4. doi: 10.1021/ja4002663. Epub 2013 Apr 3.

DOI:10.1021/ja4002663
PMID:23540906
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3677858/
Abstract

The extent to which glass-like kinetics govern dynamics in protein folding has been heavily debated. Here, we address the subject with an application of space-time perturbation theory to the dynamics of protein folding Markov state models. Borrowing techniques from the s-ensemble method, we argue that distinct active and inactive phases exist for protein folding dynamics, and that kinetics for specific systems can fall into either dynamical regime. We do not, however, observe a true glass transition in any system studied. We go on to discuss how these inactive and active phases might relate to general protein folding properties.

摘要

玻璃态动力学在多大程度上控制蛋白质折叠动力学一直存在争议。在这里,我们通过时空摄动理论在蛋白质折叠马氏态模型动力学中的应用来解决这个问题。借鉴 s-ensemble 方法的技术,我们认为蛋白质折叠动力学存在明显的活跃相和不活跃相,并且特定系统的动力学可以落入这两种动力学状态之一。然而,我们在任何研究的系统中都没有观察到真正的玻璃转变。我们接着讨论这些不活跃相和活跃相可能与一般蛋白质折叠性质的关系。

相似文献

1
Emergence of glass-like behavior in Markov state models of protein folding dynamics.蛋白质折叠动力学的马尔可夫状态模型中玻璃态行为的出现。
J Am Chem Soc. 2013 Apr 17;135(15):5501-4. doi: 10.1021/ja4002663. Epub 2013 Apr 3.
2
Percolation-like phase transitions in network models of protein dynamics.蛋白质动力学网络模型中的类似渗流的相变
J Chem Phys. 2015 Jun 7;142(21):215105. doi: 10.1063/1.4921989.
3
Markov state models provide insights into dynamic modulation of protein function.马尔可夫状态模型有助于深入了解蛋白质功能的动态调节。
Acc Chem Res. 2015 Feb 17;48(2):414-22. doi: 10.1021/ar5002999. Epub 2015 Jan 3.
4
Dynamical phase transitions reveal amyloid-like states on protein folding landscapes.动力学相变揭示了蛋白质折叠景观上的淀粉样状态。
Biophys J. 2014 Aug 19;107(4):974-82. doi: 10.1016/j.bpj.2014.06.046.
5
Probing molecular kinetics with Markov models: metastable states, transition pathways and spectroscopic observables.用马尔可夫模型探测分子动力学:亚稳态、跃迁途径和光谱可观测量。
Phys Chem Chem Phys. 2011 Oct 14;13(38):16912-27. doi: 10.1039/c1cp21258c. Epub 2011 Aug 22.
6
Derivation of a Markov state model of the dynamics of a protein-like chain immersed in an implicit solvent.浸没在隐式溶剂中的类蛋白质链动力学的马尔可夫状态模型的推导。
J Chem Phys. 2014 Sep 7;141(9):095101. doi: 10.1063/1.4894436.
7
Controlling protein molecular dynamics: how to accelerate folding while preserving the native state.控制蛋白质分子动力学:如何在保持天然状态的同时加速折叠。
J Chem Phys. 2008 Dec 14;129(22):225102. doi: 10.1063/1.3025888.
8
Constrained proper sampling of conformations of transition state ensemble of protein folding.约束过渡态折叠蛋白质构象集的适当采样。
J Chem Phys. 2011 Feb 21;134(7):075103. doi: 10.1063/1.3519056.
9
Identification of the protein folding transition state from molecular dynamics trajectories.从分子动力学轨迹中识别蛋白质折叠过渡态。
J Chem Phys. 2009 Mar 28;130(12):125104. doi: 10.1063/1.3099705.
10
Simple theory of protein folding kinetics.蛋白质折叠动力学的简单理论。
Phys Rev Lett. 2010 Nov 5;105(19):198101. doi: 10.1103/PhysRevLett.105.198101.

引用本文的文献

1
Identical sequences, different behaviors: Protein diversity captured at the single-molecule level.相同的序列,不同的行为:单分子水平上捕捉到的蛋白质多样性
Biophys J. 2024 Apr 2;123(7):814-823. doi: 10.1016/j.bpj.2024.02.020. Epub 2024 Feb 28.
2
Unsupervised Learning Methods for Molecular Simulation Data.无监督学习方法在分子模拟数据中的应用。
Chem Rev. 2021 Aug 25;121(16):9722-9758. doi: 10.1021/acs.chemrev.0c01195. Epub 2021 May 4.
3
EspcTM: Kinetic Transition Network Based on Trajectory Mapping in Effective Energy Rescaling Space.

本文引用的文献

1
Simple few-state models reveal hidden complexity in protein folding.简单的少体模型揭示了蛋白质折叠中的隐藏复杂性。
Proc Natl Acad Sci U S A. 2012 Oct 30;109(44):17807-13. doi: 10.1073/pnas.1201810109. Epub 2012 Jul 9.
2
The fast and the slow: folding and trapping of λ6-85.快速与缓慢:λ6-85 的折叠与捕获。
J Am Chem Soc. 2011 Dec 7;133(48):19338-41. doi: 10.1021/ja209073z. Epub 2011 Nov 14.
3
How fast-folding proteins fold.快速折叠蛋白如何折叠。
EspcTM:基于有效能量重标度空间中轨迹映射的动力学转变网络。
Front Mol Biosci. 2020 Oct 27;7:589718. doi: 10.3389/fmolb.2020.589718. eCollection 2020.
4
Equilibrium versus Nonequilibrium Peptide Dynamics: Insights into Transient 2D IR Spectroscopy.平衡态与非平衡态肽动力学:瞬态二维红外光谱的新见解。
J Phys Chem B. 2018 Sep 27;122(38):8783-8795. doi: 10.1021/acs.jpcb.8b05063. Epub 2018 Aug 10.
5
Rare Dissipative Transitions Punctuate the Initiation of Chemical Denaturation in Proteins.稀有耗散跃迁标记蛋白质化学变性的起始。
Biophys J. 2018 Feb 27;114(4):812-821. doi: 10.1016/j.bpj.2017.12.038.
6
Evaluation of the hybrid resolution PACE model for the study of folding, insertion, and pore formation of membrane associated peptides.评估混合分辨率 PACE 模型在研究与膜相关的肽的折叠、插入和孔形成中的应用。
J Comput Chem. 2017 Jun 15;38(16):1462-1471. doi: 10.1002/jcc.24694. Epub 2017 Jan 19.
7
Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics.用于大分子结构与动力学建模的采样方法原理与概述
PLoS Comput Biol. 2016 Apr 28;12(4):e1004619. doi: 10.1371/journal.pcbi.1004619. eCollection 2016 Apr.
8
Estimating first-passage time distributions from weighted ensemble simulations and non-Markovian analyses.从加权系综模拟和非马尔可夫分析估计首次通过时间分布。
Protein Sci. 2016 Jan;25(1):67-78. doi: 10.1002/pro.2738. Epub 2015 Sep 9.
9
Systematically constructing kinetic transition network in polypeptide from top to down: trajectory mapping.从顶向下系统构建多肽中的动力学转变网络:轨迹映射。
PLoS One. 2015 May 11;10(5):e0125932. doi: 10.1371/journal.pone.0125932. eCollection 2015.
10
Markov state models provide insights into dynamic modulation of protein function.马尔可夫状态模型有助于深入了解蛋白质功能的动态调节。
Acc Chem Res. 2015 Feb 17;48(2):414-22. doi: 10.1021/ar5002999. Epub 2015 Jan 3.
Science. 2011 Oct 28;334(6055):517-20. doi: 10.1126/science.1208351.
4
Markov state model reveals folding and functional dynamics in ultra-long MD trajectories.马科夫状态模型揭示了超长 MD 轨迹中的折叠和功能动力学。
J Am Chem Soc. 2011 Nov 16;133(45):18413-9. doi: 10.1021/ja207470h. Epub 2011 Oct 26.
5
Atomistic folding simulations of the five-helix bundle protein λ(6−85).五螺旋束蛋白 λ(6−85)的原子折叠模拟。
J Am Chem Soc. 2011 Feb 2;133(4):664-7. doi: 10.1021/ja106936n.
6
Protein folded states are kinetic hubs.蛋白质折叠状态是动力学枢纽。
Proc Natl Acad Sci U S A. 2010 Jun 15;107(24):10890-5. doi: 10.1073/pnas.1003962107. Epub 2010 Jun 1.
7
Molecular simulation of ab initio protein folding for a millisecond folder NTL9(1-39).从头算蛋白质折叠的分子模拟研究 NTL9(1-39)毫秒折叠体。
J Am Chem Soc. 2010 Feb 10;132(5):1526-8. doi: 10.1021/ja9090353.
8
Dynamic order-disorder in atomistic models of structural glass formers.结构玻璃形成体原子模型中的动态有序-无序
Science. 2009 Mar 6;323(5919):1309-13. doi: 10.1126/science.1166665. Epub 2009 Feb 5.
9
The protein folding problem.蛋白质折叠问题。
Annu Rev Biophys. 2008;37:289-316. doi: 10.1146/annurev.biophys.37.092707.153558.
10
Heterogeneity even at the speed limit of folding: large-scale molecular dynamics study of a fast-folding variant of the villin headpiece.即使在折叠速度极限下仍存在异质性:对绒毛蛋白头部结构域快速折叠变体的大规模分子动力学研究
J Mol Biol. 2007 Nov 30;374(3):806-16. doi: 10.1016/j.jmb.2007.09.069. Epub 2007 Sep 29.