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Fast and accurate genome-wide predictions and structural modeling of protein-protein interactions using Galaxy

View ORCID ProfileAysam Guerler, View ORCID ProfileDannon Baker, View ORCID ProfileMarius van den Beek, View ORCID ProfileDave Bouvier, Nate Coraor, View ORCID ProfileMichael C. Schatz, View ORCID ProfileAnton Nekrutenko
doi: https://doi.org/10.1101/2021.03.17.435706
Aysam Guerler
1Dept. of Computer Science, Johns Hopkins University, Baltimore, USA
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  • For correspondence: aysam.guerler@gmail.com
Dannon Baker
1Dept. of Computer Science, Johns Hopkins University, Baltimore, USA
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Marius van den Beek
2Dept. of Biochemistry and Molecular Biology, Penn State University, College Park, USA
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Dave Bouvier
2Dept. of Biochemistry and Molecular Biology, Penn State University, College Park, USA
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Nate Coraor
2Dept. of Biochemistry and Molecular Biology, Penn State University, College Park, USA
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Michael C. Schatz
1Dept. of Computer Science, Johns Hopkins University, Baltimore, USA
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Anton Nekrutenko
2Dept. of Biochemistry and Molecular Biology, Penn State University, College Park, USA
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  • ORCID record for Anton Nekrutenko
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Abstract

Protein-protein interactions play a crucial role in almost all cellular processes. Identifying interacting proteins reveals insight into living organisms and yields novel drug targets for disease treatment. Here, we present a publicly available, automated pipeline to predict genome-wide protein-protein interactions and produce high-quality multimeric structural models.

Application of our method to the Human and Yeast genomes yield protein-protein interaction networks similar in quality to common experimental methods. We identified and modeled Human proteins likely to interact with the papain-like protease of SARS-CoV2’s non-structural protein 3 (Nsp3). We also produced models of SARS-CoV2’s spike protein (S) interacting with myelin-oligodendrocyte glycoprotein receptor (MOG) and dipeptidyl peptidase-4 (DPP4). The presented method is capable of confidently identifying interactions while providing high-quality multimeric structural models for experimental validation.

The interactome modeling pipeline is available at usegalaxy.org.

Competing Interest Statement

AG, DB, NC and AN are founders of and hold equity in GalaxyWorks, LLC. The results of the study discussed in this publication could affect the value of GalaxyWorks, LLC.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted March 19, 2021.
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Fast and accurate genome-wide predictions and structural modeling of protein-protein interactions using Galaxy
Aysam Guerler, Dannon Baker, Marius van den Beek, Dave Bouvier, Nate Coraor, Michael C. Schatz, Anton Nekrutenko
bioRxiv 2021.03.17.435706; doi: https://doi.org/10.1101/2021.03.17.435706
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Fast and accurate genome-wide predictions and structural modeling of protein-protein interactions using Galaxy
Aysam Guerler, Dannon Baker, Marius van den Beek, Dave Bouvier, Nate Coraor, Michael C. Schatz, Anton Nekrutenko
bioRxiv 2021.03.17.435706; doi: https://doi.org/10.1101/2021.03.17.435706

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