Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Protein Folding01:22

Protein Folding

117.0K
Overview
117.0K
Molecular Chaperones and Protein Folding03:00

Molecular Chaperones and Protein Folding

17.6K
The native conformation of a protein is formed by interactions between the side chains of its constituent amino acids. When the amino acids cannot form these interactions, the protein cannot fold by itself and needs chaperones. Notably, chaperones do not relay any additional information required for the folding of polypeptides; the native conformation of a protein is determined solely by its amino acid sequence. Chaperones catalyze protein folding without being a part of the folded protein.
The...
17.6K
Protein Organization01:24

Protein Organization

6.1K
Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....
6.1K
Protein and Protein Structure02:15

Protein and Protein Structure

77.8K
Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...
77.8K
Globular and Fibrous Proteins02:21

Globular and Fibrous Proteins

43.1K
Many proteins can be classified into two distinct subtypes - globular or fibrous. These two types differ in their shapes and solubilities.
Globular proteins are also known as spheroproteins and typically are approximately round in shape. They contain a mix of amino acid types and contain differing sequences in their primary structures. Globular proteins have many different functions, such as enzymes, cellular messengers, and molecular transporters. These roles often require the proteins to be...
43.1K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Native Charge Detection Mass Spectrometry of Kilobase-Scale Messenger RNAs.

Analytical chemistry·2026
Same author

Molecular insights into the interaction between a disordered protein and a folded RNA.

bioRxiv : the preprint server for biology·2024
Same author

Recent advances in gas phase unfolding: Instrumentation and applications.

Journal of mass spectrometry : JMS·2024
Same author

Cyclic Ion Mobility-Mass Spectrometry and Tandem Collision Induced Unfolding for Quantification of Elusive Protein Biomarkers.

Analytical chemistry·2024
Same author

Collision-Induced Unfolding Reveals Disease-Associated Stability Shifts in Mitochondrial Transfer Ribonucleic Acids.

Journal of the American Chemical Society·2024
Same author

Expanding Native Mass Spectrometry to the Masses.

Journal of the American Society for Mass Spectrometry·2024

相关实验视频

Updated: May 22, 2025

Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine
08:53

Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine

Published on: January 26, 2024

919

表面诱导的展开揭示了独特的结构特征,并增强了机器学习分类模型.

Rowan Matney1, Gabrielle Blake1, Varun V Gadkari1

  • 1Department of Chemistry, University of Minnesota, Minneapolis, Minnesota 55455, United States.

Analytical chemistry
|March 14, 2025
PubMed
概括

表面诱导的展开 (SIU) 为蛋白质分析提供了与碰撞诱导的展开 (CIU) 相似的可复制性. SIU增强了敏感性,并改善了蛋白质子类的分化,使其成为生物治疗特征的有价值工具.

科学领域:

  • 生物物理化学 生物物理化学
  • 分析化学 分析化学
  • 结构生物学 结构生物学

背景情况:

  • 具有碰撞诱导展开 (CIU) 的原生离子运动质谱 (IM-MS) 是蛋白质表征的关键,为结构稳定提供了洞察力.
  • 表面诱导解离 (SID) 装置现在已经商业化,使得表面诱导展开 (SIU) 测量能够得到更广泛的使用.
  • 与CIU对SIU的性能和可重复性进行评估对于其在蛋白质分析中的采用至关重要.

研究的目的:

  • 为了比较表面诱导展开 (SIU) 与碰撞诱导展开 (CIU) 的可重现性和性能.
  • 评估SIU在区分密切相关的蛋白质子类和增强机器学习模型方面的能力.
  • 建立SIU作为蛋白质表征的补充分析方法.

主要方法:

  • 在使用模型蛋白质的Waters CyclicIMS仪器上对SIU和CIU进行比较分析:β-乳糖球蛋白 (β-lac),牛血清白蛋白 (BSA) 和免疫球蛋白G1 kappa (IgG1κ).
  • 在多个电荷状态中使用根平均平方偏差 (RMSD) 进行可复制性评估.
  • 使用SIU和CIU数据应用监督机器学习模型进行IgG子类分类.

主要成果:

  • SIU和CIU的可复制性相似,平均RMSD值低于4%.

更多相关视频

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

3.9K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

449

相关实验视频

Last Updated: May 22, 2025

Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine
08:53

Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine

Published on: January 26, 2024

919
A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

3.9K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

449
  • SIU在较低的能量下诱导了展开,揭示了微妙的结构差异和独特的展开特征.
  • 基于SIU的机器学习模型在分类IgG子类和像Adalimumab和Nivolumab这样的生物治疗药物方面取得了高的交叉验证准确率 (>90%),表现优于或匹配CIU模型.
  • 结论:

    • 表面诱导的展开 (SIU) 是一种可重复和高效的替代方案,用于蛋白质的特征化碰撞诱导展开 (CIU).
    • SIU提供了增强的灵敏度和分析深度,改善了蛋白质子类和密切相关变体的差异化.
    • 将SIU集成到工作流中,特别是在高通量和机器学习应用中,提供了显著的分析优势.