Assays

ITC multiple injection (MIM) experiments to determine the kinetic parameters of NDK (nitrononane-2,8-dione) and NADPH with Gre2p in 1x PBS buffer pH 7.5 Data from ITC recurrent single injection (rSIM) experiments were used to achieve proper fitting of kcat values.

ITC multiple injection (MIM) experiments to determine the kinetic parameters of NDK (nitrononane-2,8-dione) and NADPH with Gre2p in 100 mM HEPES buffer pH 7.5 Data from ITC recurrent single injection (rSIM) experiments were used to achieve proper fitting of kcat values.

ITC recurrent single injection (rSIM) to determine the kinetic parameters of NDK (nitrononane-2,8-dione) and NADPH with Gre2p in 100 mM KPi buffer, 1x PBS buffer and 100 mM HEPES buffer, all with pH 7.5

Python workflow for the analysis of ITC-BIND, ITC-MIM and ITC-(r)SIM experiments. Organized in a *.zip folder. Requires the following directory structure:

./ITC_analysis.py ./input/BINDING/.apj ./input/BINDING/.csv ./input/KINETICS/.apj ./input/KINETICS/.csv ./scripts/binding_neu.py ./scripts/kinetics_neu.py

And can be executed by running python ITC_analysis.py in the directory. Filenames for the input *.apj and *.csv files are defined in ITC_analysis.py. The output directory is written by ...

ITC multiple injection (MIM) experiments to determine the kinetic parameters of NDK (nitrononane-2,8-dione) and NADPH with Gre2p in 0.1%Tween-20-100 mM KPi buffer pH 7.5 Data from ITC recurrent single injection (rSIM) experiments were used to achieve proper fitting of kcat values.

ITC binding (BIND) experiments to determine the binding parameters of NADP+ to Gre2p in 1x PBS Buffer.

ITC binding (BIND) experiments to determine the binding parameters of NADP+ to Gre2p in 100 mM HEPES Buffer.

ITC binding (BIND) experiments to determine the binding parameters of NDK (nitrononane-2,8-dione) to Gre2p in 100 mM KPi Buffer. Experiments failed due to very weak binding and poor solubility of NDK in buffer.

ITC binding (BIND) experiments to determine the binding parameters of HK ((5S,8S)-anti hydroxyketone) to Gre2p in 100 mM KPi Buffer. Experiments failed due to very weak binding and poor solubility of HK in buffer.

Python workflow for the analysis of ITC-BIND, ITC-MIM and ITC-(r)SIM experiments. Organized in a *.zip folder. Requires the following directory structure:

./ITC_analysis.py ./input/BINDING/.apj ./input/BINDING/.csv ./input/KINETICS/.apj ./input/KINETICS/.csv ./scripts/binding_neu.py ./scripts/kinetics_neu.py

And can be executed by running python ITC_analysis.py in the directory. Filenames for the input *.apj and *.csv files are defined in ITC_analysis.py. The output directory is written by ...

ITC binding (BIND) experiment to determine the binding parameters of NADPH to Gre2p in 100 mM KPi Buffer with 0.1% Tween-20 added.

Specific activity of Gre2p measured by following the change in absorbance of NADPH at 340 nm for the conversion of nitrononane-2,8-dione (NDK).

Kinetic parameters (Km, kcat) of Gre2p measured by following the change in absorbance of NADPH at 340 nm for the conversion of nitrononane-2,8-dione (NDK) or hexane-2,5-dione. Initial rates at different substrate concentrations are measured.

Specific activity of Gre2p measured by following the change in absorbance of NADPH at 340 nm for the conversion of nitrononane-2,8-dione (NDK) using different enzyme concentrations.

ITC binding (BIND) experiment to determine the binding parameters of NADPH to Gre2p in 100 mM KPi Buffer.

ITC binding (BIND) experiment to determine the binding parameters of NADPH to Gre2p in 1x PBS Buffer.

ITC binding (BIND) experiments to determine the binding parameters of NADPH to Gre2p in 100 mM HEPES Buffer.

ITC binding (BIND) experiments to determine the binding parameters of NADP+ to Gre2p in 100 mM KPi Buffer.

Build the chemical defensome gene list for 5 fish: Zebrafish (Danio rerio), Atlantic cod (Gadus morhua), medaka (Oryzias latipes), Atlantic killifish (Fundulus heteroclitus) and stickleback (Gasterosteus aculeatus). Source code and relevant files can be found on GitHub: https://github.com/zhxiaokang/fishDefensome/tree/main/defensomeGenes

To study the defensome genes' expression in early developmental stages of zebrafish and stickleback. Souce code and relevant files can be found on GitHub: https://github.com/zhxiaokang/fishDefensome/tree/main/developmentalStages

Compound data and computational prediction of physicochemical properties

This section contains the links to the tools used for reproducing the computational results presented in U2019. This is required because SloppyCell is under the risk of becoming rotting code. Using Docker we can assure some persistence for the computational environment that allows to run SloppyCell.

The associated git repository can be found in https://github.com/jurquiza/Urquiza2019a.git which can be cloned.

The docker image can either be pulled from the docker hub site

docker pull ...

this assay include the hub genes of modules from different mapping schemes with highly functional similarities.

A Weighted Gene Co-Expression Network Analysis (WGCNA) of breast cancer prognostic genes (derived from transcriptome data from the TCGA Genomics Data Commons (GDC) data portal (https://portal.gdc.cancer.gov/)), and cancer hallmark genes.

A Jaccard Index of the overlap between prognostic and hallmark genes for 17 cancer types across different mapping schemes. The impact of selecting different mapping schemes was assessed by pairwise comparisons where there were 5 or more shared genes.

Model files for FMv1.5. The model is based on FMv1 of Chew et al. PNAS 2014, which is also in FAIRDOMHub and linked to the Model record as an 'Attribution'. FMv1 was extended in this work by Hannah Kinmonth-Schultz and Daniel Seaton, in Matlab.