Galaxy QCxMS for straightforward semi-empirical quantum mechanical EI-MS prediction

High-performance computing (HPC) environments are crucial for computational research, including quantum chemistry (QC), but pose challenges for non-expert users. Researchers with limited computational knowledge struggle to utilise domain-specific software and access mass spectra prediction for in s...

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Main Authors: Wudmir Y. Rojas, Zargham Ahmad, Julia Jakiela, Helge Hecht, Jana Klánová, Elliott J. Price
Format: Article
Language:English
Published: GigaScience Press 2025-07-01
Series:GigaByte
Online Access:https://gigabytejournal.com/articles/160
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author Wudmir Y. Rojas
Zargham Ahmad
Julia Jakiela
Helge Hecht
Jana Klánová
Elliott J. Price
author_facet Wudmir Y. Rojas
Zargham Ahmad
Julia Jakiela
Helge Hecht
Jana Klánová
Elliott J. Price
author_sort Wudmir Y. Rojas
collection DOAJ
description High-performance computing (HPC) environments are crucial for computational research, including quantum chemistry (QC), but pose challenges for non-expert users. Researchers with limited computational knowledge struggle to utilise domain-specific software and access mass spectra prediction for in silico annotation. Here, we provide a robust workflow that leverages interoperable file formats for molecular structures to ensure integration across various QC tools. The quantum chemistry package for mass spectral predictions after electron ionization or collision-induced dissociation has been integrated into the Galaxy platform, enabling automated analysis of fragmentation mechanisms. The extended tight binding quantum chemistry package, chosen for its balance between accuracy and computational efficiency, provides molecular geometry optimisation. A Docker image encapsulates the necessary software stack. We demonstrated the workflow for four molecules, highlighting the scalability and efficiency of our solution via runtime performance analysis. This work shows how non-HPC users can make these predictions effortlessly, using advanced computational tools without needing in-depth expertise.
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spelling doaj-art-a2b84464c3914bc1a339f709d412c6bf2025-08-20T03:15:39ZengGigaScience PressGigaByte2709-47152025-07-0110.46471/gigabyte.160Galaxy QCxMS for straightforward semi-empirical quantum mechanical EI-MS predictionWudmir Y. Rojas 0https://orcid.org/0000-0001-7036-9987Zargham Ahmad 1https://orcid.org/0000-0002-6096-224XJulia Jakiela 2https://orcid.org/0009-0001-2017-8805Helge Hecht 3https://orcid.org/0000-0001-6744-996XJana Klánová 4https://orcid.org/0000-0002-8818-5307Elliott J. Price 5https://orcid.org/0000-0001-5691-7000Faculty of Science, https://ror.org/02j46qs45Masaryk University, RECETOX, Kotlářská 2, 60200, Brno, Czech RepublicFaculty of Science, https://ror.org/02j46qs45Masaryk University, RECETOX, Kotlářská 2, 60200, Brno, Czech RepublicSchool of Chemistry, https://ror.org/01nrxwf90University of Edinburgh, Edinburgh, UKFaculty of Science, https://ror.org/02j46qs45Masaryk University, RECETOX, Kotlářská 2, 60200, Brno, Czech RepublicFaculty of Science, https://ror.org/02j46qs45Masaryk University, RECETOX, Kotlářská 2, 60200, Brno, Czech RepublicFaculty of Science, https://ror.org/02j46qs45Masaryk University, RECETOX, Kotlářská 2, 60200, Brno, Czech Republic High-performance computing (HPC) environments are crucial for computational research, including quantum chemistry (QC), but pose challenges for non-expert users. Researchers with limited computational knowledge struggle to utilise domain-specific software and access mass spectra prediction for in silico annotation. Here, we provide a robust workflow that leverages interoperable file formats for molecular structures to ensure integration across various QC tools. The quantum chemistry package for mass spectral predictions after electron ionization or collision-induced dissociation has been integrated into the Galaxy platform, enabling automated analysis of fragmentation mechanisms. The extended tight binding quantum chemistry package, chosen for its balance between accuracy and computational efficiency, provides molecular geometry optimisation. A Docker image encapsulates the necessary software stack. We demonstrated the workflow for four molecules, highlighting the scalability and efficiency of our solution via runtime performance analysis. This work shows how non-HPC users can make these predictions effortlessly, using advanced computational tools without needing in-depth expertise. https://gigabytejournal.com/articles/160
spellingShingle Wudmir Y. Rojas
Zargham Ahmad
Julia Jakiela
Helge Hecht
Jana Klánová
Elliott J. Price
Galaxy QCxMS for straightforward semi-empirical quantum mechanical EI-MS prediction
GigaByte
title Galaxy QCxMS for straightforward semi-empirical quantum mechanical EI-MS prediction
title_full Galaxy QCxMS for straightforward semi-empirical quantum mechanical EI-MS prediction
title_fullStr Galaxy QCxMS for straightforward semi-empirical quantum mechanical EI-MS prediction
title_full_unstemmed Galaxy QCxMS for straightforward semi-empirical quantum mechanical EI-MS prediction
title_short Galaxy QCxMS for straightforward semi-empirical quantum mechanical EI-MS prediction
title_sort galaxy qcxms for straightforward semi empirical quantum mechanical ei ms prediction
url https://gigabytejournal.com/articles/160
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