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Related Concept Videos

Catalytically Perfect Enzymes01:07

Catalytically Perfect Enzymes

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.
Introduction to Mechanisms of Enzyme Catalysis01:13

Introduction to Mechanisms of Enzyme Catalysis

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 a mild...
Introduction to Mechanisms of Enzyme Catalysis01:13

Introduction to Mechanisms of Enzyme Catalysis

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 a mild...
Induced-fit Model01:13

Induced-fit Model

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 characteristics of...
Introduction to Enzymes01:22

Introduction to Enzymes

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.’
Most enzymes are proteins that speed up biochemical reactions without being consumed. Enzymes contain one or more active sites that bind the substrates and convert them into products. Many enzymes also...
Introduction to Enzyme Kinetics01:19

Introduction to Enzyme Kinetics

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...

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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

Iterative approach to computational enzyme design.

Heidi K Privett1, Gert Kiss, Toni M Lee

  • 1Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.

Proceedings of the National Academy of Sciences of the United States of America
|February 24, 2012
PubMed
Summary
This summary is machine-generated.

This study presents an iterative computational approach to design highly efficient enzymes. An improved enzyme for Kemp elimination was developed through cycles of design, simulation, and structural analysis, achieving significant catalytic activity.

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Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

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Area of Science:

  • Protein engineering and computational biology
  • Enzyme catalysis and design

Background:

  • Developing computational methods for designing enzymes to catalyze specific reactions is a key goal in protein design.
  • Previous efforts involved synthesizing and screening numerous variants for computationally designed enzymes.

Purpose of the Study:

  • To present an iterative computational approach for designing enzymes.
  • To develop the most catalytically efficient computationally designed enzyme for Kemp elimination to date.

Main Methods:

  • Utilized established computational techniques for initial enzyme design (HG-1).
  • Employed molecular dynamics (MD) simulations and X-ray crystallography to analyze enzyme structures and guide improvements.
  • Iteratively refined the design based on structural and simulation data, leading to HG-2 and HG-3.

Main Results:

  • The initial design (HG-1) was catalytically inactive; analysis suggested issues with bound waters and active site flexibility.
  • An iterative design process yielded an active Kemp eliminase (HG-2).
  • Further refinement through MD analysis resulted in HG-3, exhibiting a threefold increase in activity compared to HG-2.

Conclusions:

  • An iterative computational design strategy, integrating MD simulations and structural analysis, enhances enzyme development.
  • This approach advances the understanding of enzymatic catalysis and the reliable production of active enzymes.