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相关概念视频

Enzyme Inhibition01:30

Enzyme Inhibition

91.0K
Inhibitors are molecules that reduce enzyme activity by binding to the enzyme. In a normally functioning cell, enzymes are regulated by a variety of inhibitors. Drugs and other toxins can also inhibit enzymes. Some inhibitors bind to the enzyme’s active site, while others inhibit enzymatic activity by binding to other sites on the protein structure.
91.0K
Introduction to Enzyme Kinetics01:19

Introduction to Enzyme Kinetics

31.7K
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...
31.7K
Enzyme Kinetics01:19

Enzyme Kinetics

103.4K
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...
103.4K
Determination of Michaelis Constant and Maximum Elimination Rate01:20

Determination of Michaelis Constant and Maximum Elimination Rate

386
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...
386
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

9.9K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
9.9K
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

1.1K
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
1.1K

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相关实验视频

Updated: Jan 6, 2026

A Semi-High-Throughput Adaptation of the NADH-Coupled ATPase Assay for Screening Small Molecule Inhibitors
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A Semi-High-Throughput Adaptation of the NADH-Coupled ATPase Assay for Screening Small Molecule Inhibitors

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梯度下降以预测酶抑制的发生

Amauri Duarte da Silva1, Walter Filgueira de Azevedo2

  • 1Graduate Program in Information Technologies and Health Management, Federal University of Health Sciences of Porto Alegre, Porto Alegre, RS, Brazil.

Methods in molecular biology (Clifton, N.J.)
|October 11, 2025
PubMed
概括
此摘要是机器生成的。

这项研究使用渐变下降机器学习方法来预测药物发现的蛋白质向抑制. 研究人员开发了一种针对抗癌药物点的回归模型,例如循环林依赖激酶2.

关键词:
人工智能的人工智能是人工智能.生物系统是生物系统.复杂的系统复杂的系统.梯度下降是一种梯度下降.机器学习 机器学习桑德里斯 2.0 的版本评分功能的空间空间.随机梯度下降 随机梯度下降

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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
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Anaerobic Protein Purification and Kinetic Analysis via Oxygen Electrode for Studying DesB Dioxygenase Activity and Inhibition
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Anaerobic Protein Purification and Kinetic Analysis via Oxygen Electrode for Studying DesB Dioxygenase Activity and Inhibition

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相关实验视频

Last Updated: Jan 6, 2026

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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
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Anaerobic Protein Purification and Kinetic Analysis via Oxygen Electrode for Studying DesB Dioxygenase Activity and Inhibition
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科学领域:

  • 计算化学和药物发现.
  • 人工智能在生物信息学中的应用.
  • 机器学习用于分子建模.

背景情况:

  • 蛋白质标在药物发现中至关重要,可以使用机器学习进行分析.
  • 梯度下降是一种强大的优化算法,用于机器学习模型.
  • 预测酶抑制是开发向疗法的关键.

研究的目的:

  • 描述和应用梯度下降方法来预测蛋白质标抑制.
  • 为识别潜在的抗癌药物构建回归模型.
  • 展示机器学习工具在药物发现管道中的集成.

主要方法:

  • 使用批量梯度下降和随机梯度下降 (来自Scikit-Learn的SGDRegressor).
  • 集成的AutoDock Vina用于计算蛋白质 - 配体相互作用数据.
  • 使用SAnDReS 2.0程序来实现SGDRegressor模型.
  • 使用Jupyter笔记本和可用的数据集开发了一种实践方法.

主要成果:

  • 成功创建回归模型来预测酶抑制.
  • 证明了对林依赖性激酶2的抑制预测,这是抗癌药物的标.
  • 结合对接数据与机器学习进行准确的预测.

结论:

  • 梯度下降变种,特别是SGDRegressor,对于预测蛋白位抑制是有效的.
  • 开发的方法促进了药物发现过程,使潜在的候选药物的有效选成为可能.
  • 提供开源工具和数据,以支持进一步的计算药物发现研究.