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相关概念视频

Turnover Number and Catalytic Efficiency01:19

Turnover Number and Catalytic Efficiency

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The turnover number of an enzyme is the maximum number of substrate molecules it can transform per unit time. Turnover numbers for most enzymes range from 1 to 1000 molecules per second. Catalase has the known highest turnover number, capable of converting up to 2.8×106 molecules of hydrogen peroxide into water and oxygen per second. Lysozyme has the lowest known turnover number of half a molecule per second.
Chymotrypsin is a pancreatic enzyme that breaks down proteins during digestion....
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Introduction to Enzyme Kinetics01:19

Introduction to Enzyme Kinetics

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Enzyme kinetics studies the rates of biochemical reactions. Scientists monitor the reaction rates for a particular enzymatic reaction at various substrate concentrations. Additional trials with inhibitors or other molecules that affect the reaction rate may also be performed.
The experimenter can then plot the initial reaction rate or velocity (Vo) of a given trial against the substrate concentration ([S]) to obtain a graph of the reaction properties. For many enzymatic reactions involving a...
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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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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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One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
331
Enzymes02:34

Enzymes

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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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相关实验视频

Updated: May 26, 2025

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes
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Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes

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使用RealKcat对酶变异动力学的可靠预测.

Karuna Anna Sajeevan1,2, Abraham Osinuga3, Arunraj B1

  • 1Department of Chemical and Biological Engineering, Iowa State University, Ames, Iowa, USA.

bioRxiv : the preprint server for biology
|February 24, 2025
PubMed
概括

研究人员开发了RealKcat,这是一个用于预测酶动态的新型计算模型. 这种工具准确地预测了对酶活性的突变影响,推进了酶设计和生物催化剂应用.

关键词:
生物意识机器学习机器学习生物催化剂是一种生物催化剂.生物化学 生物化学生物物理和计算生物学数据库策划数据库策划酶工程是什么?酶工程是什么?酶动力学 酶动力学系统生物学 系统生物学

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Hot Biological Catalysis: Isothermal Titration Calorimetry to Characterize Enzymatic Reactions
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Hot Biological Catalysis: Isothermal Titration Calorimetry to Characterize Enzymatic Reactions

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Steady-state, Pre-steady-state, and Single-turnover Kinetic Measurement for DNA Glycosylase Activity
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相关实验视频

Last Updated: May 26, 2025

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Hot Biological Catalysis: Isothermal Titration Calorimetry to Characterize Enzymatic Reactions
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Steady-state, Pre-steady-state, and Single-turnover Kinetic Measurement for DNA Glycosylase Activity
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科学领域:

  • 生物催化和酶工程 生物催化和酶工程
  • 计算生物学和生物信息学
  • 蛋白质科学 蛋白质科学

背景情况:

  • 精确预测酶动力学参数 (催化周转率,基质亲和力) 对于理解酶功能和设计新型生物催化剂至关重要.
  • 现有的计算模型往往难以准确预测突变对催化必需残留物的影响,这阻碍了它们在酶设计中的应用.
  • 开发复杂的预测模型是必要的,以克服这些局限性,并使精确的酶工程.

研究的目的:

  • 开发和验证一个新的计算框架,RealKcat,用于准确预测酶动力学参数,特别是催化周转率 (kcat) 和基质亲和力 (Km).
  • 解决当前模型在捕获对催化必需残留物突变效应方面的局限性.
  • 为预测由遗传修饰引起的酶活性变化建立一个新的基准.

主要方法:

  • 在10个模型架构和25671个超参数组合中进行了广泛的网格搜索.
  • 开发了一个基于梯度的增材框架,名为RealKcat.
  • 在手工策划的数据集 (KinHub-27k) 上训练模型,该数据集包括来自2,158篇科学文章的27,176个实验条目.
  • 将动力参数 (kcat,Km) 按合理数量级进行集群,以便进行可靠的分析.

主要成果:

  • 在预测动力参数方面,RealKcat实现了>85%的测试准确度.
  • 与现有方法相比,该模型对突变诱导的变异性表现出更高的灵敏度.
  • RealKcat是第一个准确预测催化残留物删除后酶活性完全丧失的模型.
  • 在工业性酸酶 (PafA) 突变数据集上实现了最先进的96%的验证准确性,证实了概括性.

结论:

  • RealKcat在预测酶动力学和突变影响方面取得了重大进展.
  • 该模型能够准确地捕获每残留的催化相关性,这提高了其在酶设计和定向进化的实用性.
  • RealKcat在工业数据集上的表现验证了其在生物催化和酶工程中的实际应用潜力.