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相关概念视频

Enzyme Inhibition01:30

Enzyme Inhibition

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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.
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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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Induced-fit Model01:13

Induced-fit Model

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Most chemical reactions in cells require enzymes—biological catalysts that speed up the reaction without being consumed or permanently changed. They reduce the activation energy needed to convert the reactants into products. Enzymes are proteins, that usually work by binding to a substrate—a reactant molecule that they act upon.
Enzymes exhibit substrate specificity, meaning that they can only bind to certain substrates. This is mainly determined by the shape and chemical...
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Ligand Binding and Linkage00:49

Ligand Binding and Linkage

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Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
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Allosteric Proteins-ATCase01:19

Allosteric Proteins-ATCase

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Binding sites linkages can regulate a protein's function.  For example, enzyme activity is often regulated through a feedback mechanism where the end product of the biochemical process serves as an inhibitor.
Aspartate transcarbamoylase (ATCase) is a cytosolic enzyme that catalyzes the condensation of L-aspartate and carbamoyl phosphate to  N-carbamoyl-L-aspartate. This reaction is the first step in pyrimidine biosynthesis. UTP and CTP, the end products of the pyrimidine synthesis...
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Allosteric Regulation01:08

Allosteric Regulation

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Allosteric regulation of enzymes occurs when the binding of an effector molecule to a site that is different from the active site causes a change in the enzymatic activity. This alternate site is called an allosteric site, and an enzyme can contain more than one of these sites. Allosteric regulation can either be positive or negative, resulting in an increase or decrease in enzyme activity. Most enzymes that display allosteric regulation are metabolic enzymes involved in the degradation or...
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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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通过机器学习修改同类酶的抑制特异性

Dor S Gozlan1, Reut Meiri2, Gili Shapira1

  • 1Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel.

The FEBS journal
|September 5, 2025
PubMed
概括

机器学习简化了选择性蛋白酶抑制剂的设计. 一种新的N-TIMP2变体对矩阵金属蛋白酶 (MMPs) 具有增强的选择性,表明实验力度降低,对同类酶的向性得到改善.

关键词:
深度突变扫描基质金属蛋白酶神经网络蛋白质工程蛋白质与蛋白质的相互作用

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科学领域:

  • 生物化学和分子生物学
  • 计算生物学
  • 药物发现

背景情况:

  • 选择性酶抑制剂对于向治疗和生物研究至关重要.
  • 设计特定的抑制剂,特别是对同类酶,在实验规模和特异性调整方面面临挑战.
  • 目前用于蛋白质设计的机器学习 (ML) 方法受到能量计算精度和预测多变异效应的限制.

研究的目的:

  • 开发和验证一种基于ML的新方法来设计选择性蛋白酶抑制剂.
  • 为了简化对同类酶的特异性配置的抑制剂的识别.
  • 将该方法应用于设计矩阵金属蛋白酶 (MMP) 的选择性抑制剂.

主要方法:

  • 通过ML模型利用高通量选 (HTS) 数据来训练预测性结合性.
  • 设计一种针对MMP-1,MMP-3和MMP-9的新型N-TIMP2变体.
  • 设计变体的结合亲和力和选择性的实验验证.
  • 使用分子建模和能源最小化进行结构洞察.

主要成果:

  • 成功设计了一种新型N-TIMP2变体,在MMP-1,MMP-3和MMP-9之间具有不同的特异性.
  • 实验验证证了与野生型N-TIMP2相比显著的特异性转变和增强的选择性.
  • 结构分析提供了对变种选择性改善的分子基础的见解.

结论:

  • 开发的基于ML的方法有效地减少了抑制剂设计中的实验工作量.
  • 这种方法有助于合理设计同类酶家族的高度选择性抑制剂.
  • 这项工作促进了对酶-抑制剂相互作用和选择性向的理解.