Galaxy InteractoMIX: An Integrated Computational Platform for the Study of Protein-Protein Interaction Data

Authors

Mirela-Bota, P., Aguirre-Plans, J., Meseguer, A., Galletti, C., Segura, J., Planas-Iglesias, J., Garcia-Garcia, J., Guney, E., Oliva, B., Fernandez-Fuentes, N.

Source

JOURNAL OF MOLECULAR BIOLOGY 433: 166656 (2021)

Abstract

Protein interactions play a crucial role among the different functions of a cell and are central to our understanding of cellular processes both in health and disease. Here we present Galaxy InteractoMIX ( http://galaxy.interactomix.com ) a platform composed of thirteen different computational tools each addressing specific aspects of the study of protein-protein interactions, ranging from large-scale cross-specie protein-wide interactomes to atomic resolution level of protein complexes. Galaxy InteractoMIX provides an intuitive interface where users can retrieve consolidated interactomics data spread across several databases or uncover links between diseases and genes by analysing the interactomes underlying these diseases. The platform makes possible large-scale prediction and curation protein interactions using conservation of motifs, interology or presence or absence of key sequence signatures. The range of structurebased tools includes modelling and analysis of protein complexes, delineation of interfaces for the modelling of peptides acting as inhibitors of protein-protein interactions. Galaxy InteractoMIX includes a range of ready-to-use workflows to run complex analyses requiring minimal intervention by users. The potential range of application of the platform covers different aspects of Life Science, Biomedicine, Biotechnology and drug discovery where protein associations are studied.

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Citation

Mirela-Bota, P., Aguirre-Plans, J., Meseguer, A., Galletti, C., Segura, J., Planas-Iglesias, J., Garcia-Garcia, J., Guney, E., Oliva, B., Fernandez-Fuentes, N., 2021: Galaxy InteractoMIX: An Integrated Computational Platform for the Study of Protein-Protein Interaction Data. Journal of Molecular Biology 433: 166656.

David Awarded by MUNI Scientist Award
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