PT  - JOURNAL ARTICLE
AU  - Guerler, Aysam
AU  - Baker, Dannon
AU  - van den Beek, Marius
AU  - Bouvier, Dave
AU  - Coraor, Nate
AU  - Schatz, Michael C.
AU  - Nekrutenko, Anton
TI  - Fast and accurate genome-wide predictions and structural modeling of protein-protein interactions using Galaxy
AID  - 10.1101/2021.03.17.435706
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.03.17.435706
4099  - http://biorxiv.org/content/early/2021/03/19/2021.03.17.435706.short
4100  - http://biorxiv.org/content/early/2021/03/19/2021.03.17.435706.full
AB  - 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 StatementAG, 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.