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Merging in-silico and in vitro salivary protein complex partners using the STRING database: A tutorial
Karla Tonelli Bicalho Crosara1, Eduardo Buozi Moffa2, Yizhi Xiao1
1Schulich Dentistry and Department of Biochemistry, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, ON, Canada.
Journal of Proteomics
|August 8, 2017
Summary
This study demonstrates how the STRING database aids in identifying protein-protein interactions. Bioinformatics tools combined with experimental data accelerate the understanding of protein networks and the Human Interactome.
Area of Science:
- Biochemistry
- Bioinformatics
- Systems Biology
Background:
- Protein-protein interactions are crucial for physiological functions and cellular actions.
- Understanding these interactions is vital for comprehending organismal physiology and protein efficacy.
- Previous in vitro mass spectrometry identified 43 proteins interacting with histatin 1, including 6 known and 37 novel partners.
Purpose of the Study:
- To demonstrate the utility of the STRING database for studying protein-protein interactions.
- To simulate a protein-protein interaction network for histatin 1 using bioinformatics tools.
- To integrate experimental findings with in silico predictions for advancing knowledge.
Main Methods:
- Utilized an in silico approach combined with the STRING database (http://string-db.org/).
- Simulated a novel protein-protein interaction network for histatin 1.
- Incorporated previously known, predicted, and newly identified interactors.
Main Results:
- Successfully constructed a histatin 1 protein-protein interaction network using the STRING database.
- Validated the usefulness of bioinformatics tools in conjunction with experimental data.
- Highlighted the ability of STRING to integrate known and predicted protein associations.
Conclusions:
- Bioinformatics tools like the STRING database are essential for advancing the study of protein-protein interactions.
- Integrating in silico methods with in vitro findings accelerates knowledge acquisition.
- The STRING database can predict potential protein interactions, guiding future research in the Human Interactome.