Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Catalytically Perfect Enzymes01:07

Catalytically Perfect Enzymes

4.8K
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...
4.8K
Introduction to Mechanisms of Enzyme Catalysis01:13

Introduction to Mechanisms of Enzyme Catalysis

10.2K
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...
10.2K
Induced-fit Model01:13

Induced-fit Model

87.4K
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...
87.4K
Enzymes02:34

Enzymes

91.3K
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...
91.3K
Allosteric Proteins-ATCase01:19

Allosteric Proteins-ATCase

6.3K
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...
6.3K
Introduction to Enzyme Kinetics01:19

Introduction to Enzyme Kinetics

30.5K
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...
30.5K

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

From First Principles to Function: How AI Is Reshaping Enzyme Design.

Biochemistry·2026
Same author

An engineered closed-shell, two-component, 480-subunit nucleocapsid.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Simple biological controllers drive the evolution of soft modes.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Diversity-generating retroelements for programmable targeted hypermutagenesis.

Nature biotechnology·2026
Same author

Constrained evolutionary funnels shape viral immune escape.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Origins and breadth of pairwise epistasis in an α-helix of β-lactamase TEM-1.

Nature communications·2026

関連する実験動画

Updated: Dec 14, 2025

Modeling an Enzyme Active Site using Molecular Visualization Freeware
14:37

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

11.0K

コリスマート変異酵素の設計のための進化ベースのモデル

William P Russ1, Matteo Figliuzzi2, Christian Stocker3

  • 1University of Texas Southwestern Medical Center, Dallas, TX, USA.

Science (New York, N.Y.)
|July 25, 2020
PubMed
まとめ

科学者は進化のデータを用いて 新しいタンパク質を設計する方法を開発しました このアプローチにより,自然に似た機能と膨大な配列の多様性を持つ酵素が作られ,人工タンパク質の設計への道が開けます.

さらに関連する動画

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.4K
A New Screening Method for the Directed Evolution of Thermostable Bacteriolytic Enzymes
13:30

A New Screening Method for the Directed Evolution of Thermostable Bacteriolytic Enzymes

Published on: November 7, 2012

18.4K

関連する実験動画

Last Updated: Dec 14, 2025

Modeling an Enzyme Active Site using Molecular Visualization Freeware
14:37

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

11.0K
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.4K
A New Screening Method for the Directed Evolution of Thermostable Bacteriolytic Enzymes
13:30

A New Screening Method for the Directed Evolution of Thermostable Bacteriolytic Enzymes

Published on: November 7, 2012

18.4K

科学分野:

  • 生物化学
  • タンパク質工学
  • コンピュータ生物学

背景:

  • 酵素の合理的な設計は 基礎研究と実用的な応用に不可欠です
  • 既存の方法は,タンパク質の配列-機能関係の複雑さで苦労することが多い.

研究 の 目的:

  • 進化に基づいた人工タンパク質の設計のための一般的なプロセスを開発する.
  • タンパク質の仕様制限を 進化の配列データから直接学ぶ

主な方法:

  • 進化のデータから タンパク質配列の制約を学ぶ
  • 合成遺伝子のライブラリを設計し合成する
  • 定量的な補完分析を用いて遺伝子ライブラリを in vivo でテストする.
  • アロマティックアミノ酸のバイオシンセシスの酵素であるコリスマートミュータゼに このプロセスを適用する.

主要な成果:

  • コリスマートミュータゼの大量配列多様性による自然に似た触媒機能の設計が実証された.
  • 配列ベースの統計モデルが 機能的なタンパク質を特定できることを示した.
  • 特定のゲノムコンテキスト内の機能の生成モデルを最適化しました.
  • 機能的なタンパク質の 膨大な領域へのアクセスが確認されました

結論:

  • 進化配列のデータはタンパク質を特定するのに十分です.
  • 開発されたプロセスは,一般的な人工タンパク質設計のための基礎を提供します.
  • この研究は 望ましい機能を持つ タンパク質の設計に 新たな道を開きます