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Related Concept Videos

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.
 
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Introduction to Enzymes01:22

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The use of enzymes by humans dates to 7000 BCE. Humans first used enzymes to ferment sugars and produce alcohol without knowing that this was an enzyme-catalyzed reaction. Wilhelm Kuhne coined the term 'enzyme' in 1877 from the Greek words ‘en’ meaning ‘in’ or ‘within’ and ‘zyme’ meaning ‘yeast.’
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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.
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Turnover Number and Catalytic Efficiency01:19

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The turnover number of an enzyme is the maximum number of substrate molecules it can transform per unit time. Turnover numbers for most enzymes range from 1 to 1000 molecules per second. Catalase has the known highest turnover number, capable of converting up to 2.8×106 molecules of hydrogen peroxide into water and oxygen per second. Lysozyme has the lowest known turnover number of half a molecule per second.
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Enzyme-linked receptors are proteins that act as both receptor and enzyme, activating multiple intracellular signals. This is a large group of receptors that include the receptor tyrosine kinase (RTK) family. Many growth factors and hormones bind to and activate the RTKs.
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EzCatDB: the enzyme reaction database, 2015 update.

Nozomi Nagano1, Naoko Nakayama2, Kazuyoshi Ikeda3

  • 1Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Tokyo Waterfront Bio-IT Research Building, 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan n.nagano@aist.go.jp.

Nucleic Acids Research
|October 18, 2014
PubMed
Summary
This summary is machine-generated.

EzCatDB classifies enzyme reactions using active-site structures and catalytic mechanisms. This updated database offers advanced search tools for enzyme reaction and active-site structure exploration.

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Area of Science:

  • Biochemistry
  • Structural Biology
  • Bioinformatics

Background:

  • Enzyme classification is crucial for understanding catalytic mechanisms.
  • Databases integrating structural and mechanistic data are valuable research tools.
  • Existing resources may lack comprehensive integration of active-site structures and reaction classifications.

Purpose of the Study:

  • To present the updated EzCatDB database, focusing on enzyme reaction classification.
  • To highlight the integration of active-site structures, catalytic mechanisms, and ligand information.
  • To introduce new search functionalities for enhanced data retrieval.

Main Methods:

  • Manual classification of enzyme reactions based on literature, UniProtKB sequences, and PDB structures.
  • Categorization of ligands (cofactors, substrates, products, intermediates) associated with enzyme structures.
  • Development of new search tools: EzCat-BLAST, EzCat-FORTE, and EzMetAct.

Main Results:

  • EzCatDB provides a structured classification of enzyme reactions (RLCP).
  • The database links enzyme active-site 3D structures with detailed catalytic information.
  • New search systems (EzCat-BLAST, EzCat-FORTE, EzMetAct) enhance data accessibility and analysis.

Conclusions:

  • The updated EzCatDB facilitates in-depth study of enzyme catalytic mechanisms.
  • Integrated structural and reaction data aids in understanding enzyme function.
  • Advanced search tools improve the utility of EzCatDB for researchers.