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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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Synthetic Biology02:55

Synthetic Biology

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Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
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Amplifying Signals via Enzymatic Cascade01:22

Amplifying Signals via Enzymatic Cascade

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When a ligand binds to a cell-surface receptor, the receptor's intracellular domain changes shape, which may either activate its enzyme function or allow its binding to other molecules. The initial signal is amplified by most signal transduction pathways. This means that a single ligand molecule can activate multiple molecules of a downstream target. Proteins that relay a signal are most commonly phosphorylated at one or more sites, activating or inactivating the protein. Kinases catalyze...
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What is Genetic Engineering?

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Overview
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Introduction to Mechanisms of Enzyme Catalysis01:13

Introduction to Mechanisms of Enzyme Catalysis

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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...
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Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

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An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
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相关实验视频

Updated: Jul 12, 2025

Author Spotlight: Advancing Protein Engineering – Harnessing Evolution Through PRANCE and Lab Automation
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利用生成性AI来解码酶催化和进化,用于增强工程的进化.

Wen Jun Xie1,2, Arieh Warshel1

  • 1Department of Chemistry, University of Southern California, Los Angeles, CA, USA.

bioRxiv : the preprint server for biology
|October 24, 2023
PubMed
概括

生成型人工智能 (AI) 有助于理解酶序-功能关系. 这种方法有助于预测酶突变,并为各种应用设计新型生物催化剂.

科学领域:

  • 生物化学和分子生物学
  • 计算生物学和生物信息学
  • 酵素工程和生物技术

背景情况:

  • 酶是重要的蛋白质催化剂,在许多科学领域推动了进步.
  • 了解酶序-功能关系是具有挑战性的,限制了理性酶工程.
  • 生成型人工智能 (AI) 为分析复杂的生物数据提供了先进的功能.

研究的目的:

  • 审查应用生成AI用于酶序列分析的最新进展.
  • 探索生成AI对预测酶特性和设计新酶的影响.
  • 突出AI如何解码蛋白质序列语义,并指导生物催化剂的开发.

主要方法:

  • 应用生成性AI模型来分析庞大的酶序列数据.
  • 研究生成性人工智能用于预测对酶适应性,活性和稳定性的突变效应.
  • 利用人工智能合理化实验室进化和新酶的设计.

主要成果:

  • 生成型人工智能可以在酶序列空间中识别复杂的模式.
  • 人工智能有助于发现新的功能性酶序列.
  • 使用自然序列预测酶活性和稳定性将催化与进化联系在一起.
关键词:
酶工程是指酶工程的工程.酵素进化演变的过程进化-催化关系的关系.生成型的人工智能突变的影响 突变效应

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结论:

  • 生成型人工智能显著提高了我们对酶机制和进化的理解.
  • 整合生成性AI加速了优质生物催化剂的开发.
  • 人工智能驱动的方法有望彻底改变酶工程及其应用.