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Related Concept Videos

Enzymes02:34

Enzymes

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...
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 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 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 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...

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Updated: Jul 10, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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Published on: July 25, 2013

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

Sebastian Lindner1, Florence J Hardy2,3, Donald Hilvert1

  • 1Laboratory of Organic Chemistry, ETH Zurich, Zurich 8093, Switzerland.

Biochemistry
|July 9, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence is revolutionizing enzyme engineering. AI-enhanced methods are creating novel enzymes with unprecedented catalytic functions, paving the way for on-demand enzyme design.

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Area of Science:

  • Biotechnology and Biochemistry
  • Computational Biology

Background:

  • Artificial intelligence (AI) is a transformative technology impacting scientific research.
  • De novo enzyme design is a rapidly advancing field with significant industrial and medical potential.

Purpose of the Study:

  • To survey emerging AI-driven strategies and computational models in enzyme engineering.
  • To examine the opportunities and challenges in achieving on-demand enzyme design.

Main Methods:

  • Review of recent literature on AI applications in enzyme design.
  • Analysis of computational models and methodologies for enzyme engineering.

Main Results:

  • AI-enhanced approaches have successfully generated enzymes with novel catalytic activities.
  • These methods offer capabilities beyond traditional enzyme engineering techniques.

Conclusions:

  • AI is redefining enzyme engineering, enabling the creation of enzymes with tailored functions.
  • Further advancements are needed to realize the goal of truly on-demand enzyme design.