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

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-prot...

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Veröffentlicht in:BMC bioinformatics 2023-06, Vol.24 (1), p.263-13, Article 263
Hauptverfasser: Guerler, Aysam, Baker, Dannon, van den Beek, Marius, Gruening, Bjoern, Bouvier, Dave, Coraor, Nate, Shank, Stephen D, Zehr, Jordan D, Schatz, Michael C, Nekrutenko, Anton
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Sprache:eng
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Zusammenfassung: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. We also produced models of SARS-CoV2's spike protein (S) interacting with myelin-oligodendrocyte glycoprotein receptor and dipeptidyl peptidase-4. 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 and usegalaxy.eu.
ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-023-05389-8