On the reproducibility of enzyme reactions and kinetic modelling

Because enzyme activity depends very much on the reaction conditions, it is crucial to report all these metadata (see for example the STRENDA Guidelines:https://www.beilstein-strenda-db.org/strenda/public/guidelines.xhtml).

Another challenge in experiments to determine enzyme reaction parameters is the choice of suitable substrate concentrations to enable optimal kinetic fits and the informed choice of a kinetic model.

A Jupyter notebook is given to assist in the choice of substrate concentrations for initial rate experiments and show the impact of noise in the raw data on the linear fit of the initial rates.

To be able to fully judge the quality of experimental reaction parameters, more information is needed on the modelling process:

  1. the linear fits of the raw data used to calculate the initial reaction rates
  2. the fits of the initial reaction rates with the Michaelis-Menten

A Jupyter notebook to automatically provide these data is given. This notebook works with data from https://fairdomhub.org/investigations/464, which is included here again.

DOI: 10.15490/fairdomhub.1.investigation.483.1

Zenodo URL: None

Created at: 23rd Mar 2022 at 15:38

Contents

Design an Initial Rate Experiment

This study explores how to design an initial rate experiment. It starts with a "zero-round" experiment, which is used to design a "first-round" experiment, which then leads to the design of a "gold-round" experiment.

Use a Jupyter Notebook to design an initital rate experiment

This Jupyter Notebook assists you in the design of initial rate experiments.

For help on installing the classical Jupyter Notebook, see here: https://jupyter.org/install

For documentation about Juypter Notebooks, see here: https://jupyter-notebook.readthedocs.io/en/stable/

There are multiple tutorials online that help you to learn how to use a Jupyter notebook.

The notebook is provided as an .ipynb and as a .pdf file.

The plots the script generates with the default values are also given as .png
...

A simulated bad first-round experiment

Badly chosen substrate concentrations for an intital rate experiment give data that makes it difficult to fit with a kinetic model and judge the quality of the fit.

  • simulated_firstround_experiment_bad.png

A simulated good first-round experiment

Well chosen substrate concentrations for an intital rate experiment give data that makes it easy to fit with a kinetic model and judge the quality of the fit and use it as a basis for the final gold-round experiment.

  • simulated_firstround_experiment_good.png

A simulated gold-round experiment

Very well chosen substrate concentrations for an intital rate experiment give data that makes it very easy to fit with a kinetic model and judge the quality of the fit.

  • simulated_goldround_experiment.png

A simulated zero-round experiment

An initial choice of 5 widely spaced substrates enables a first, rough estimate of Km to inform the design of first-round experiments.

  • simulated_zeroround_experiment.png

Design an initial rate experiment

This is the Jupyter Notebook to allow editing and working with the code.

Design an initial rate experiment in four steps

This script aims to help you design high-quality initial rate experiments. It uses the Michaelis-Menten equation to simulate data for an enzyme with unknown enzyme reaction parameters. Four steps are needed:
1. Estimate the enzyme reaction parameters

Input: estimates of Km and vmax

and indicate the enzyme concentration concentration you are planning to use.
If you have no
...

  • Design_an_Initial_Rate_Experiment.ipynb

Design an initial rate experiment (pdf)

This is the pdf of the Jupyter Notebook to allow looking at the notebook without installing anything.

Design an initial rate experiment in four steps

This script aims to help you design high-quality initial rate experiments. It uses the Michaelis-Menten equation to simulate data for an enzyme with unknown enzyme reaction parameters. Four steps are needed: 1. Estimate the enzyme reaction parameters

Input: estimates of Km and vmax

and indicate the enzyme concentration concentration you are planning
...

  • Design_an_Initial_Rate_Experiment.pdf

Analyse an Initial Rate Experiment

TBD

Use a Jupyter Notebook to model Michaelis-Menten Kinetics on experimental data

This Jupyter Notebook assists you in the analysis of initial rate experiments.

For help on installing the classical Jupyter Notebook, see here: https://jupyter.org/install

For documentation about Juypter Notebooks, see here: https://jupyter-notebook.readthedocs.io/en/stable/

There are multiple tutorials online that help you to learn how to use a Jupyter notebook.

The notebook is provided as an .ipynb and as a .pdf file. The plots the script generates with the default input data are also given as
...

Linear Fits and Michaelis Menten plot

This is a zip file containing all the files and folders needed to analyse raw data, fit initial rates and create a "Michaelis-Menten plot".
Instructions on usage are added in the notebook.

  • MichaelisMentenKinetics.zip

Linear Fits and Michaelis Menten plot (pdf)

This is the pdf of the Jupyter Notebook to allow looking at the notebook without installing anything.

NOTE THAT this pdf may be mangled when viewed on FAIRDOMHub, but should look fine when downloaded.

  • MichaelisMentenNotebook.pdf

Selwyn Test

This study briefly shows how a Selwyn test can be performed.

Use a Jupyter Notebook to understand how the Selwyn test works

This Jupyter Notebook assists you in understanding how a Selwyn Test works.

For help on installing the classical Jupyter Notebook, see here: https://jupyter.org/install

For documentation about Juypter Notebooks, see here: https://jupyter-notebook.readthedocs.io/en/stable/

There are multiple tutorials online that help you to learn how to use a Jupyter notebook.

The notebook is provided as an .ipynb and as a .pdf file.

The plots the script generates with the default values are also given as .png
...

Selwyn Test Simulated Example

This is the Jupyter Notebook to allow editing and working with the code.
It is a simple example of how a Selwyn test can look like if it is passed (1.) or failed (2.).

  • Selwyn_Test.ipynb

Selwyn Test Simulated Example (pdf)

This is the pdf of the Jupyter Notebook to allow looking at the notebook without installing anything. It is a simple example of how a Selwyn test can look like if it is passed (1.) or failed (2.).

  • Selwyn_Test.pdf

Progress Curve Analysis

This study briefly shows how a Progress Curve (Time-Course) Analysis can look like.

Use a Jupyter Notebook to understand how a progress curve experiment can look like

This Jupyter Notebook assists you in understanding how a progress curve experiment can look like.

For help on installing the classical Jupyter Notebook, see here: https://jupyter.org/install

For documentation about Juypter Notebooks, see here: https://jupyter-notebook.readthedocs.io/en/stable/

There are multiple tutorials online that help you to learn how to use a Jupyter notebook.

The notebook is provided as an .ipynb and as a .pdf file.

The plots the script generates with the default values are
...

Progress Curve Experiment Simulated Example

This is the Jupyter Notebook to allow editing and working with the code. It is a simple example of how a progress curve experiment can look like.

  • ProgressCurve_TimeCourse.ipynb

Progress Curve Experiment Simulated Example (pdf)

This is the pdf of the Jupyter Notebook to allow looking at the notebook without installing anything. It is a simple example of how a progress curve experiment can look like.

  • ProgressCurve_TimeCourse.pdf
Fingerprints

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MD5: f14430984a7b07a3de1e855476d27939

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Citation
Gygli, G. (2022). On the reproducibility of enzyme reactions and kinetic modelling. FAIRDOMHub. https://doi.org/10.15490/FAIRDOMHUB.1.INVESTIGATION.483.1
Snapshots
Snapshot 1 (23rd Mar 2022) DOI
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Created: 23rd Mar 2022 at 15:38

Last updated: 23rd Mar 2022 at 15:39

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