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相关概念视频

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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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...
20.2K
Introduction to Mechanisms of Enzyme Catalysis01:13

Introduction to Mechanisms of Enzyme Catalysis

8.3K
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...
8.3K
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...
97.2K
Determination of Michaelis Constant and Maximum Elimination Rate01:20

Determination of Michaelis Constant and Maximum Elimination Rate

135
The Michaelis constant (KM) and the theoretical maximum process rate (Vmax) are vital parameters in the Michaelis-Menten equation, central to many biochemical reactions. They provide essential insights into enzyme kinetics and drug metabolism.
These parameters can be estimated by analyzing plasma concentration data post-drug administration. A notable example of this application is phenytoin, a drug with capacity-limited kinetics. It's recommended that phenytoin should be administered at two...
135
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: Jul 18, 2025

Modeling an Enzyme Active Site using Molecular Visualization Freeware
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一个定制的贝叶斯算法来优化酶催化反应.

Ryo Tachibana1,2, Kailin Zhang1, Zhi Zou1

  • 1Department of Chemistry, University of Basel, Mattenstrasse 24a, BPR 1096, CH-4058, Basel, Switzerland.

ACS sustainable chemistry & engineering
|August 25, 2023
PubMed
概括
此摘要是机器生成的。

一个新的贝叶斯优化算法 (BOA) 有效地优化了酶催化反应,显著优于响应表面方法 (RSM) 等传统方法,以提高催化性能.

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科学领域:

  • 化学工程是化学工程的重要组成部分.
  • 生物催化剂是一种生物催化剂.
  • 计算化学的计算化学

背景情况:

  • 实验设计 (DoE) 对于优化化学反应性能至关重要.
  • 响应表面方法 (RSM) 是一种常见的DoE方法,但需要大量的实验,变量越来越多.
  • 酶催化反应需要有效优化连续参数.

研究的目的:

  • 开发和验证一个改进的贝叶斯优化算法 (BOA) 来优化酶催化反应.
  • 为了解决RSM在处理大量实验变量的局限性.
  • 在有限的实验资源下最大限度地提高酶催化反应的催化性能.

主要方法:

  • 实现一个新的贝叶斯优化算法 (BOA).
  • 优化连续参数,如温度,反应时间和反应剂/酶度.
  • 与响应表面方法 (RSM) 和现有的贝叶斯优化算法对比BOA的基准测试.
  • 使用生物催化C-C键形成和氨化反应进行验证.

主要成果:

  • 拟议的BOA在优化营业额方面取得了重大改进.
  • 与RSM相比,观察到高达80%的改善.
  • 与之前的贝叶斯优化算法相比,获得了高达360%的改进.
  • 证明了酶活性和选择性的同时优化,用于交叉佐因凝结.

结论:

  • 开发的BOA为优化酶催化反应提供了更高效和有效的方法.
  • 在RSM和现有的贝叶斯方法相比,BOA提供了优越的性能,特别是在资源限制下.
  • 这一策略增强了酶活性和选择性,为先进的生物催化应用铺平了道路.