Molecular networking applied to toxicology

Overview

This project consists of 5 modules to facilitate the analysis of mass spectrometry data by molecular networking :

• Metabolites: annotation of molecules in a .clustersummary file from the GNPS site from a reference file.
• Biotransformation: annotates the links in a .selfloop file from the GNPS site with the biotransformations corresponding to the mass difference between the molecules.
• InSilico: in silico prediction of a list of molecules whose SMILES code is provided by 3 software packages (BioTransformer3, SyGMa, MetaTrans).
• MetGem: allows export to Cytoscape of molecular network link information generated by the MetGem software.
• ProteoWizard: converts mass spectrometry data from proprietary to open formats. Uses the docker version to run on a Linux system.

Linux and Windows (WSL) compatible. Not tested on Mac

Instruction

Required packages:

• Zenity apt install zenity

=> As this project was designed for non-bioinformaticians, a graphical interface via zenity was included. However, modules can be used separately.

• bc command apt install bc
• gawk apt install gawk
• Java apt install default-jre
• Docker (https://docs.docker.com/desktop/install/linux-install/)
• Conda (https://github.com/conda/conda)

Download Tools folder and place the following folder in it:

• Biotranformer3.0 folder containing the various files of Biotransformer3 (see link below). Rename the Biotranformer3.0.jar.
• MetaTrans-master folder containing the various files of MetaTrans (see link below)

Set Main.sh to the root of Tools folder and make it executable chmod +x Main.sh

Run the Main.sh ./Main.sh

To use the in silico mode, create a text file with each line = namemolecule,smilecode

Sources & Documentations

GNPS : https://gnps.ucsd.edu/ProteoSAFe/static/gnps-splash.jsp

BioTransformer3 : https://bitbucket.org/wishartlab/biotransformer3.0jar/src/master/

SyGMa : https://github.com/3D-e-Chem/sygma

MetaTrans : https://github.com/KavrakiLab/MetaTrans

ProteoWizard : https://proteowizard.sourceforge.io/

Cytoscape : https://cytoscape.org/

MetGem : https://github.com/metgem/metgem

SdftoSmi & SmitoStr scripts : https://github.com/MunibaFaiza/cheminformatics/tree/main

References

Wang, M. et al. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nat Biotechnol 34, 828–837 (2016).

Djoumbou-Feunang, Y. et al. BioTransformer: a comprehensive computational tool for small molecule metabolism prediction and metabolite identification. J Cheminform 11, 2 (2019)

Ridder, L. & Wagener, M. SyGMa: Combining Expert Knowledge and Empirical Scoring in the Prediction of Metabolites. ChemMedChem 3, 821–832 (2008).

Litsa, E. E., Das, P. & Kavraki, L. E. Prediction of drug metabolites using neural machine translation. Chem. Sci. 11, 12777–12788 (2020).

Chambers, M. C. et al. A cross-platform toolkit for mass spectrometry and proteomics. Nat Biotechnol 30, 918–920 (2012).

Shannon, P. et al. Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks. Genome Res. 13, 2498–2504 (2003).

Olivon, F. et al. MetGem Software for the Generation of Molecular Networks Based on the t-SNE Algorithm. Anal. Chem. 90, 13900–13908 (2018).