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Part 1: Document Description
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Citation |
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Title: |
Catalysis of L-cysteine by IscS in the presence of IscU |
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Identification Number: |
doi:10.18419/darus-2483 |
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Distributor: |
DaRUS |
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Date of Distribution: |
2022-02-15 |
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Version: |
1 |
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Bibliographic Citation: |
Pinto, Maria Filipa, 2022, "Catalysis of L-cysteine by IscS in the presence of IscU", https://doi.org/10.18419/darus-2483, DaRUS, V1 |
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Citation |
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Title: |
Catalysis of L-cysteine by IscS in the presence of IscU |
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Identification Number: |
doi:10.18419/darus-2483 |
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Authoring Entity: |
Pinto, Maria Filipa |
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Software used in Production: |
PyEnzyme |
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Grant Number: |
EXC 2075 - 390740016 |
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Distributor: |
DaRUS |
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Access Authority: |
Range, Jan |
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Holdings Information: |
https://doi.org/10.18419/darus-2483 |
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Study Scope |
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Keywords: |
Chemistry, Medicine, Health and Life Sciences, Kinetic Modeling, Kinetic Model, Enzymology, Desulfurase, Biotechnology, EnzymeML |
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Abstract: |
Measured was the reaction from cysteine to alanine by the Cysteine desulfurase, for six different initial concentrations of cysteine. The data consists of three data points over the course of 2.5 minutes for alanine. Additionally, the concentration of cysteine over time was calculated from the given values, for the later modelling. |
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Notes: |
This dataset consists of two Jupyter notebooks that perform modelling based on InterferEnzy as well as a custom one written in Python that utilizes <b>lmfit</b> and <b>PyEnzyme</b>. In addition, the modeled EnzymeML files are included as well as the InterferEnzy output. The latter can be reproduced by using the <a href="https://interferenzy.i3s.up.pt">web-based API</a> and the generated input file "Desulfuration_Cysteine_Pinto_input_interferENZY.txt". In order to investigate the dataset, it is advised to use the <a href="https://github.com/EnzymeML/PyEnzyme">PyEnzyme</a> library. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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Related Studies |
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Pinto, Maria Filipa. (2020). Catalysis of L-cysteine by IscS in the presence of IscU (dataset formatted for analysis by interferENZY) [Data set]. Zenodo. doi:<a href="https://doi.org/10.5281/zenodo.3957403">10.5281/zenodo.3957403</a> |
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Label: |
AnalysingInitialRateDataUsingMichaelisMentenKineticsinterferENZY.ipynb |
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Text: |
Used to generate an InterferEnzy file from an OMEX EnzymeML archive, which was the sent to the modeling platform to estimate the parameters. |
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Notes: |
application/x-ipynb+json |
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Label: |
AnalysingInitialRateDataUsingMichaelisMentenKineticsJupyterNotebook.ipynb |
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Text: |
Used to model the given OMEX EnzymeML archive using the Python package lmfit. |
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Notes: |
application/x-ipynb+json |
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Label: |
Desulfuration_Cysteine_Pinto.omex |
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Text: |
OMEX EnzymeML archive that was generated from the data using the given spreadsheet. |
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Notes: |
application/octet-stream |
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Label: |
Desulfuration_Cysteine_Pinto_input_interferENZY.txt |
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Text: |
Text file that is used as input for InterferEnzy |
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Notes: |
text/plain |
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Label: |
model.svg |
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Notes: |
image/svg+xml |
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Label: |
Pinto_Measurements_(modelled_by_interferENZY)_Modelled.omex |
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Text: |
Resulting OMEX EnzymeML archive from the given Jupyter Notebook |
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Notes: |
application/octet-stream |
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Label: |
Pinto_Measurements_(modelled_by_Jupyter_Notebook).omex |
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Text: | |
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Notes: |
text/plain |
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Label: |
Pinto_output_interferENZY.txt |
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Text: |
Output that was given by InterferEnzy |
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Notes: |
text/plain |
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Label: |
time-course.svg |
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Notes: |
image/svg+xml |