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相关概念视频

Introduction to Mechanisms of Enzyme Catalysis01:13

Introduction to Mechanisms of Enzyme Catalysis

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For many years, scientists thought that enzyme-substrate binding took place in a simple "lock-and-key" fashion. This model stated that the enzyme and substrate fit together perfectly in one instantaneous step. However, current research supports a more refined view scientists call induced fit. The induced-fit model expands upon the lock-and-key model by describing a more dynamic interaction between enzyme and substrate. As the enzyme and substrate come together, their interaction causes...
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Catalytically Perfect Enzymes01:07

Catalytically Perfect Enzymes

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The theory of catalytically perfect enzymes was first proposed by W.J. Albery and J. R. Knowles in 1976. These enzymes catalyze biochemical reactions at high-speed. Their catalytic efficiency values range from 108-109 M-1s-1. These enzymes are also called 'diffusion-controlled' as the only rate-limiting step in the catalysis is that of the substrate diffusion into the active site. Examples include triose phosphate isomerase, fumarase, and superoxide dismutase.
 
Most enzymes...
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Enzymes02:34

Enzymes

82.6K
Inside living organisms, enzymes act as catalysts for many biochemical reactions involved in cellular metabolism. The role of enzymes is to reduce the activation energies of biochemical reactions by forming complexes with its substrates. The lowering of activation energies favor an increase in the rates of biochemical reactions.
Enzyme deficiencies can often translate into life-threatening diseases. For example, a genetic abnormality resulting in the deficiency of the enzyme G6PD...
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Enzyme Kinetics01:19

Enzyme Kinetics

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Enzymes speed up reactions by lowering the activation energy of the reactants. The speed at which the enzyme turns reactants into products is called the rate of reaction. Several factors impact the rate of reaction, including the number of available reactants. Enzyme kinetics is the study of how an enzyme changes the rate of a reaction.
Scientists typically study enzyme kinetics with a fixed amount of enzyme in the controlled environment of a test tube. When more reactant, or substrate, is...
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Introduction to Enzymes01:22

Introduction to Enzymes

19.4K
The use of enzymes by humans dates to 7000 BCE. Humans first used enzymes to ferment sugars and produce alcohol without knowing that this was an enzyme-catalyzed reaction. Wilhelm Kuhne coined the term 'enzyme' in 1877 from the Greek words ‘en’ meaning ‘in’ or ‘within’ and ‘zyme’ meaning ‘yeast.’
Most enzymes are proteins that speed up biochemical reactions without being consumed. Enzymes contain one or more active sites that...
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Cofactors and Coenzymes01:27

Cofactors and Coenzymes

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Enzymes require additional components for proper function. There are two such classes of molecules: cofactors and coenzymes. Cofactors are metallic ions and coenzymes are non-protein organic molecules. Both of these types of helper molecule can be tightly bound to the enzyme or bound only when the substrate binds.
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相关实验视频

Updated: Sep 9, 2025

Immobilization of Multi-biocatalysts in Alginate Beads for Cofactor Regeneration and Improved Reusability
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Immobilization of Multi-biocatalysts in Alginate Beads for Cofactor Regeneration and Improved Reusability

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多维协同工程促进纳米酶催化

Yuechun Li1, Zhaowen Cui1, Chenxin Ji1

  • 1College of Food Science and Engineering, Northwest A&F University, 22 Xinong Road, Yangling, Shaanxi, 712100, China.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|August 29, 2025
PubMed
概括
此摘要是机器生成的。

这项研究分析了通过整合形态,电子结构,外部刺激和机器学习来增强纳米酶催化剂的前沿策略. 这些进步旨在释放纳米酶的环境和其他应用潜力.

关键词:
促进纳米酶催化电子结构外部调节机器学习形态结构

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Multi-enzyme Screening Using a High-throughput Genetic Enzyme Screening System
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Multi-enzyme Screening Using a High-throughput Genetic Enzyme Screening System
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科学领域:

  • 材料科学
  • 催化工程
  • 人工智能

背景情况:

  • 纳米酶在环境修复及其他领域具有很大的应用潜力.
  • 提高纳米酶催化活性仍然是一个重大挑战.

研究的目的:

  • 系统地分析提高纳米酶催化力的前沿策略.
  • 开发一个整合形态,电子结构,外部刺激和机器学习 (ML) 辅助设计的理论框架.

主要方法:

  • 基于纳米结构的结构活动关系分析.
  • 深入讨论电子结构优化 (例如,d频段中心,缺陷工程).
  • 通过外部刺激 (超声波,光,电场) 总结动态调节机制.
  • 强调ML驱动的高通量选以加速纳米酶发现.

主要成果:

  • 阐明纳米形态与催化性能之间的关系.
  • 了解电子结构在催化活动中的作用.
  • 外部刺激对催化调节的影响
  • 突出 ML 在分析复杂的结构-活动关系中的作用.

结论:

  • 跨学科融合是克服当前纳米酶开发瓶的关键.
  • 这项工作为推进纳米细胞学提供了新的视角.
  • 释放纳米酶应对全球挑战的潜力.