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相关概念视频

Ladder Diagrams: Redox Equilibria01:30

Ladder Diagrams: Redox Equilibria

735
Ladder diagrams are useful tools for understanding redox equilibrium reactions, especially the effects of concentration changes on the electrochemical potential of the reaction. The vertical axis in the redox ladder diagrams represents the electrochemical potential, E. The area of predominance is demarcated using the Nernst equation.
Consider the Fe3+/Fe2+ half-reaction, which has a standard-state potential of +0.771 V. At potentials more positive than +0.771 V, Fe3+ predominates, whereas Fe2+...
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Redox Reactions01:24

Redox Reactions

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Oxidation-reduction or redox reactions involve the transfer of electrons from one molecule or atom to another. When an atom gains an electron, another atom must lose an electron, meaning oxidation and reduction must occur together. Since the redox occurs in pairs, the atom that gets oxidized is also called the reducing agent or reductant, and the atom that is reduced is also called the oxidizing agent or oxidant. A straightforward way to remember the definitions of oxidation and reduction is...
58.1K
Redox Equilibria: Overview01:23

Redox Equilibria: Overview

1.5K
A reduction-oxidation reaction is commonly called a redox reaction. In a redox reaction, electrons are transferred from one species to another rather than being shared between or among atoms. The reducing agent or reductant is the species that loses electrons and gets oxidized in the process. The species that gains electrons and gets reduced in the process is the oxidizing agent or oxidant. Redox reactions are represented as two separate equations called half-reactions, where one equation...
1.5K
Redox Titration: Overview01:21

Redox Titration: Overview

4.8K
Redox titration is a chemical analysis technique used to determine the concentration of an unknown substance by measuring the electron transfer in a redox (reduction-oxidation) reaction. The process involves gradually adding a titrant with a known concentration of an oxidizing or reducing agent, to the analyte, the solution with an unknown concentration, until reaching the endpoint, which indicates the completion of the reaction between the two substances. Ensuring the analyte is in a single...
4.8K
Corrosion02:49

Corrosion

28.0K
The degradation of metals due to natural electrochemical processes is known as corrosion. Rust formation on iron, tarnishing of silver, and the blue-green patina that develops on copper are examples of corrosion. Corrosion involves the oxidation of metals. Sometimes it is protective, such as the oxidation of copper or aluminum, wherein a protective layer of metal oxide or its derivatives forms on the surface, protecting the underlying metal from further oxidation. In other cases, corrosion is...
28.0K
Redox Titration: Other Oxidizing and Reducing Agents01:26

Redox Titration: Other Oxidizing and Reducing Agents

1.3K
Besides iodine, other oxidizing or reducing agents can serve as titrants in redox titrations. Common oxidizing titrants include KMnO4, cerium(IV), and K2Cr2O7. The choice of oxidizing titrants depends on factors like stability, cost, analyte strength, and reaction rate between the analyte and titrant. KMnO4 is a strong oxidizing titrant that reduces from Mn(VII) to Mn(II) in a highly acidic solution, simultaneously oxidizing the analyte to a higher oxidation state. In this case, KMnO4 acts as a...
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相关实验视频

Updated: Jan 6, 2026

Setup of Capillary Electrophoresis-Inductively Coupled Plasma Mass Spectrometry CE-ICP-MS for Quantification of Iron Redox Species FeII, FeIII
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Setup of Capillary Electrophoresis-Inductively Coupled Plasma Mass Spectrometry CE-ICP-MS for Quantification of Iron Redox Species FeII, FeIII

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通过机器学习预测金属蛋白还氧化潜力:关注铁硫系统

Francesca Persico1, Bruno G Galuzzi2,3, Miriana Pellegrino4

  • 1Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza Dell'Ateneo Nuovo 1, Milano 20126, Italy.

Journal of chemical information and modeling
|October 30, 2025
PubMed
概括
此摘要是机器生成的。

我们开发了FeS-RedPred,这是一种机器学习模型,用于预测铁硫 (Fe-S) 蛋白质的降解潜力. 这个工具准确地预测了氧化还原行为,有助于蛋白质的设计和理解生物能量学.

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Setup of Capillary Electrophoresis-Inductively Coupled Plasma Mass Spectrometry CE-ICP-MS for Quantification of Iron Redox Species FeII, FeIII
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科学领域:

  • 生物化学和生物物理学
  • 计算生物学 计算生物学
  • 生物能源学 生物能源学

背景情况:

  • 铁硫 (Fe-S) 蛋白对于许多生物过程至关重要,包括能量转化和DNA修复.
  • 它们的功能依赖于由金属辅助因子确定的微调降解潜力 (RP),但从结构中预测RP是具有挑战性的.
  • 这种困难阻碍了针对蛋白质设计的RP系统调制.

研究的目的:

  • 引入FeS-RedPred,一个机器学习 (ML) 框架,用于准确和可扩展的预测Fe-S蛋白中的RP.
  • 提供一个工具,帮助理解RP的决定因素,并指导蛋白质工程的努力.
  • 为了使各种金属蛋白家族的氧化还原潜力的高通量预测.

主要方法:

  • 开发了一个机器学习 (ML) 框架,FeS-RedPred,使用极端梯度增强 (XGB) 模型.
  • 在多个空间尺度 (从本地到全球) 上计算的结构衍生分子描述器.
  • 专注于单核和双核Fe-S集群 (例如,rubredoxins, [2Fe-2S] ferredoxins),并提供可用的数据.

主要成果:

  • 在RP预测中达到约40mV的平均绝对误差,与最先进的方法相竞争.
  • 证明了预测准确性和计算成本之间的高效平衡.
  • 该模型为RP的关键决定因素提供了洞察力,促进了解释.

结论:

  • FeS-RedPred为了解金属蛋白的氧化还原行为提供了有价值的基础.
  • 能够对氧化还原潜力的高通量预测,为数据驱动的蛋白质设计提供信息.
  • 通过提高我们设计Fe-S蛋白质的能力,推进生物能学和人类健康领域.