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Turnover Number and Catalytic Efficiency

Turnover Number and Catalytic Efficiency

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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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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Related Experiment Video

Updated: Aug 1, 2025

Crystallization and Structural Determination of an Enzyme:Substrate Complex by Serial Crystallography in a Versatile Microfluidic Chip

Crystallization and Structural Determination of an Enzyme:Substrate Complex by Serial Crystallography in a Versatile Microfluidic Chip

Published on: March 20, 2021

Reconciling experimental catalytic data stemming from structure sensitivity.

Xue Zong^1,2, Dionisios G Vlachos^1,2

¹Department of Chemical and Biomolecular Engineering, University of Delaware 150 Academy St. Newark Delaware 19716 USA vlachos@udel.edu.

Chemical Science

|May 1, 2023

Summary

This summary is machine-generated.

Catalyst structure sensitivity explains most variations in experimental reaction kinetics data. Smaller platinum nanoparticles show low reactivity due to carbon poisoning, with an optimal coordination number for maximum reaction rates.

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Last Updated: Aug 1, 2025

Crystallization and Structural Determination of an Enzyme:Substrate Complex by Serial Crystallography in a Versatile Microfluidic Chip

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Published on: March 20, 2021

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Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

Area of Science:

Chemical kinetics
Catalysis science
Nanoparticle characterization

Background:

Experimental kinetics data are crucial for model validation but show significant inter-laboratory variability.
The reasons for these discrepancies in literature data for the same catalyst and reaction remain unclear.
Understanding data variability is key to reliable catalyst development and kinetic modeling.

Purpose of the Study:

To rationalize the variability in literature kinetics data using catalyst structure sensitivity.
To develop a methodology for building structure-descriptor-based microkinetic models.
To investigate the relationship between nanoparticle structure and reaction kinetics for methane oxidation on platinum.

Main Methods:

Literature data mining of experimental kinetics for methane oxidation on platinum.
Development of a structure-descriptor-based microkinetic modeling approach.
Analysis of structure-reactivity relationships, focusing on nanoparticle size and coordination number.

Main Results:

A volcano-like trend in reaction rate was observed, correlating with an optimal coordination number.
Smaller platinum nanoparticles exhibited significantly reduced reactivity, attributed to carbon poisoning.
The majority of the observed data variation was successfully explained by catalyst structure sensitivity.

Conclusions:

Catalyst structure sensitivity is a primary driver of variability in experimental kinetics data.
The developed methodology enables prediction of kinetic performance and identification of optimal catalyst structures.
This approach serves as a valuable tool for assessing data quality and identifying experimental outliers.