1. Merging in-silico and in vitro salivary protein complex partners using the STRING database: A tutorial
- Author
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Eduardo Buozi Moffa, Karla Tonelli Bicalho Crosara, Yizhi Xiao, and Walter L. Siqueira
- Subjects
0301 basic medicine ,In silico ,Biophysics ,Histatins ,Computational biology ,In Vitro Techniques ,Biology ,computer.software_genre ,Biochemistry ,Interactome ,03 medical and health sciences ,0302 clinical medicine ,Human interactome ,Protein Interaction Mapping ,Humans ,Computer Simulation ,Salivary Proteins and Peptides ,Databases, Protein ,Saliva ,String database ,Computational Biology ,In vitro ,030104 developmental biology ,Multiprotein Complexes ,030220 oncology & carcinogenesis ,Salivary Proteins ,Data mining ,Protein network ,computer ,Merge (version control) - Abstract
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.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.
- Published
- 2018