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Merging in-silico and in vitro salivary protein complex partners using the STRING database: A tutorial. | LitMetric

Merging in-silico and in vitro salivary protein complex partners using the STRING database: A tutorial.

J Proteomics

Schulich Dentistry and Department of Biochemistry, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, ON, Canada. Electronic address:

Published: January 2018

AI Article Synopsis

  • Protein-protein interactions are essential for understanding physiological mechanisms in organisms, and identifying these interactions can enhance our knowledge of protein functions.
  • A previous study revealed 43 proteins interacting with histatin 1, including 6 known partners and 37 novel ones, utilizing mass spectrometry for confirmation.
  • This tutorial demonstrates how the STRING database can be used to analyze and simulate protein-protein networks effectively, combining bioinformatics with experimental findings to advance research in protein interactions and the Human Interactome.

Article Abstract

Unlabelled: Protein-protein interaction is a common physiological mechanism for protection and actions of proteins in an organism. The identification and characterization of protein-protein interactions in different organisms is necessary to better understand their physiology and to determine their efficacy. In a previous in vitro study using mass spectrometry, we identified 43 proteins that interact with histatin 1. Six previously documented interactors were confirmed and 37 novel partners were identified. In this tutorial, we aimed to demonstrate the usefulness of the STRING database for studying protein-protein interactions. We used an in-silico approach along with the STRING database (http://string-db.org/) and successfully performed a fast simulation of a novel constructed histatin 1 protein-protein network, including both the previously known and the predicted interactors, along with our newly identified interactors. Our study highlights the advantages and importance of applying bioinformatics tools to merge in-silico tactics with experimental in vitro findings for rapid advancement of our knowledge about protein-protein interactions. Our findings also indicate that bioinformatics tools such as the STRING protein network database can help predict potential interactions between proteins and thus serve as a guide for future steps in our exploration of the Human Interactome.

Significance: Our study highlights the usefulness of the STRING protein database for studying protein-protein interactions. The STRING database can collect and integrate data about known and predicted protein-protein associations from many organisms, including both direct (physical) and indirect (functional) interactions, in an easy-to-use interface.

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Source
http://dx.doi.org/10.1016/j.jprot.2017.08.002DOI Listing

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