Fluorescence techniques applied to root-state detection in protein folding

荧光技术应用于蛋白质折叠根态检测

基本信息

项目摘要

The one-dimensional amino acid sequence of a protein determines its three-dimensional native structure, its folding mechanism, and biological activity. One hypothesis on how folding of the polypeptide chain proceeds is that it starts with the formation of long loops closed by loop nodes, by pairs of short residue segments separated by twenty to hundred residues along the 1D sequence. This hypothesis has been extensively tested on E.coli adenylate kinase by steady-state and time-resolved Förster-resonance energy transfer spectroscopic experiments coupled to stopped-flow double mixing. While these experiments revealed which loops are formed early and which only later, they could not answer the following questions: 1. What is the independent stability of a loop, the stability that only involves intra-loop residues and no assisting contacts with non-loop residues? 2. What is the independent stability of the loop node, crucial for early loop formation? 3. How can we measure the metastability of a loop node if it becomes only marginally populated during early refolding? 4. What is the molecular driving force and mechanism of loop-node formation? We consider these questions critical for the ultimate goal of sequence-to-structure prediction.We aim to address the four questions by applying methods based on a unique spectroscopic probe, on diazabicyclo-[2.2.2]-oct-2-ene or DBO, incorporated into polypeptides, where the polypeptides model either a single loop node or a whole loop of adenylate kinase. DBO, when used in combination with tryptophan, tyrosine or other suitable partner probes, currently provides the FRET method of highest distance resolution, named short-distance FRET or sdFRET, and this resolution is required to detect the native-likeness of a loop node. The use of DBO simultaneously affords a contact-quenching method, named collision-induced fluorescence quenching or CIFQ. These methods and their combination allow us to determine even marginal populations of metastable nodes. CIFQ and pressure jump measurements allow us to determine the folding rates of loops that are sufficiently populated in water or become sufficiently populated upon addition of stabilizing co-agents: This constitutes the required basis to probe the molecular mechanism of loop-node formation.
蛋白质的一维氨基酸序列决定了其三维天然结构、折叠机制和生物活性。关于多肽链如何折叠的一个假设是,它开始于由环节点闭合的长环的形成,由沿着1D序列的沿着20至100个残基分隔的短残基片段对闭合。这一假设已经通过稳态和时间分辨的Förster共振能量转移光谱实验结合停流双混合在大肠杆菌腺苷酸激酶上进行了广泛的测试。虽然这些实验揭示了哪些环路形成得早,哪些环路形成得晚,但他们无法回答以下问题:1。什么是环的独立稳定性,即只涉及环内残基而不涉及与非环残基的辅助接触的稳定性?2.什么是环路节点的独立稳定性,这对早期环路形成至关重要? 3.如果一个循环节点在早期的重折叠过程中只被少量填充,我们如何衡量它的亚稳定性?4.环结形成的分子驱动力和机制是什么?我们认为这些问题对于序列到结构预测的最终目标至关重要,我们的目标是通过应用基于独特的光谱探针的方法来解决这四个问题,所述光谱探针在二氮杂双环-[2.2.2]-辛-2-烯或DBO上被并入多肽中,其中多肽模拟腺苷酸激酶的单环节点或整个环。当与色氨酸、酪氨酸或其他合适的伴侣探针组合使用时,DBO目前提供了最高距离分辨率的FRET方法,称为短距离FRET或sdFRET,并且需要这种分辨率来检测环节点的天然相似性。DBO的使用同时提供了一种接触猝灭方法,称为碰撞诱导荧光猝灭或CIFQ。这些方法和它们的组合使我们能够确定亚稳节点的边缘种群。CIFQ和压力跃变测量使我们能够确定在水中充分填充或在添加稳定助剂后变得充分填充的环的折叠速率:这构成了探测环结形成的分子机制所需的基础。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Method-Unifying View of Loop-Formation Kinetics in Peptide and Protein Folding.
肽和蛋白质折叠中环形成动力学的方法统一观点
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Professor Dr. Werner Nau其他文献

Professor Dr. Werner Nau的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Professor Dr. Werner Nau', 18)}}的其他基金

London Dispersion Interactions inside Macrocycles
大环内的伦敦色散相互作用
  • 批准号:
    271456295
  • 财政年份:
    2015
  • 资助金额:
    --
  • 项目类别:
    Priority Programmes
Polypeptide dynamics and structure studied simultaneously by collision-induced fluorescence quenching and resonance energy transfer in the 10-Å domain
通过碰撞诱导的荧光猝灭和 10-Å 域中的共振能量转移同时研究多肽动力学和结构
  • 批准号:
    168513691
  • 财政年份:
    2010
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Supramolecular tandem assays for monitoring enzymatic activity
用于监测酶活性的超分子串联测定
  • 批准号:
    106373163
  • 财政年份:
    2008
  • 资助金额:
    --
  • 项目类别:
    Research Grants

相似国自然基金

EstimatingLarge Demand Systems with MachineLearning Techniques
  • 批准号:
  • 批准年份:
    2024
  • 资助金额:
    万元
  • 项目类别:
    外国学者研究基金
计算电磁学高稳定度辛算法研究
  • 批准号:
    60931002
  • 批准年份:
    2009
  • 资助金额:
    200.0 万元
  • 项目类别:
    重点项目

相似海外基金

Functional plasticity in retinal degenerative disease
视网膜退行性疾病的功能可塑性
  • 批准号:
    10637293
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
An innovative and straightforward approach to construct and manipulate viral infectious clones
构建和操作病毒感染性克隆的创新且简单的方法
  • 批准号:
    10667766
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
Integrating cell identities and morphodynamics through extracellular cues
通过细胞外线索整合细胞身份和形态动力学
  • 批准号:
    10644461
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
The immunogenicity and pathogenicity of HLA-DQ in solid organ transplantation
HLA-DQ在实体器官移植中的免疫原性和致病性
  • 批准号:
    10658665
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
Investigating the relationship between Sympathetic Nervous System Development and Neuroblastoma
研究交感神经系统发育与神经母细胞瘤之间的关系
  • 批准号:
    10658015
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
Artificial Intelligence Applied to Video and Speech for Objectively Evaluating Social Interaction and Depression in Mild Cognitive Impairment
人工智能应用于视频和语音,客观评估轻度认知障碍患者的社交互动和抑郁情况
  • 批准号:
    10810965
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
Accurate and Reliable Diagnostics for Injured Children: Machine Learning for Ultrasound
为受伤儿童提供准确可靠的诊断:超声机器学习
  • 批准号:
    10572582
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
CSHL Single Cell Analysis Course (2023-2027)
CSHL单细胞分析课程(2023-2027)
  • 批准号:
    10627446
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
Enhancing water Cherenkov detector technology with machine learning techniques applied at a test beam experiment
通过在测试光束实验中应用机器学习技术来增强水切伦科夫探测器技术
  • 批准号:
    EP/X027368/1
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
    Fellowship
2023 Liquid Crystals Gordon Research Conference & Gordon Research Seminar
2023年液晶戈登研究会议
  • 批准号:
    10683604
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了