On the reproducibility of enzyme reactions and kinetic modelling
DownloadBecause 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:
- the linear fits of the raw data used to calculate the initial reaction rates
- 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 14:38
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
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Created: 23rd Mar 2022 at 14:38
Last updated: 23rd Mar 2022 at 14:39
