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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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Introduction to Enzyme Kinetics01:19

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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.
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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.
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Introduction to Mechanisms of Enzyme Catalysis01:13

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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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Enzyme Kinetics01:19

Enzyme Kinetics

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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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A New Screening Method for the Directed Evolution of Thermostable Bacteriolytic Enzymes
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Understanding enzyme function evolution from a computational perspective.

Jonathan D Tyzack1, Nicholas Furnham2, Ian Sillitoe3

  • 1EMBL-EBI, Wellcome Genome Campus, CB10 1SD, United Kingdom.

Current Opinion in Structural Biology
|September 12, 2017
PubMed
Summary
This summary is machine-generated.

This review explores computational methods to understand enzyme evolution by analyzing protein structure and dynamics. These approaches reveal evolutionary steps, aiding in predicting enzyme evolvability and guiding protein design.

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Area of Science:

  • Biochemistry and Molecular Biology
  • Computational Biology
  • Evolutionary Biology

Background:

  • Enzyme evolution drives the development of new functions.
  • Understanding evolutionary mechanisms is crucial for protein engineering.
  • Current methods lack quantitative measures of evolutionary steps.

Purpose of the Study:

  • To review computational approaches for studying enzyme evolution.
  • To present quantitative methods for assessing evolutionary steps in protein domains.
  • To provide insights into enzyme evolvability and guide protein design.

Main Methods:

  • Review of recent computational strategies.
  • Quantitative analysis of evolutionary steps within structural domains.
  • Correlation of substrate changes with domain structure evolution.

Main Results:

  • Development of methods to measure the size and type of evolutionary steps.
  • Assessment of the relationship between substrate changes and structural evolution.
  • Identification of factors influencing enzyme evolvability.

Conclusions:

  • Computational approaches offer powerful tools to understand enzyme evolution.
  • Quantitative analysis of evolutionary steps enhances insights into protein adaptation.
  • These methods can guide de novo enzyme design and directed evolution.