New SDC function prediction based on protein-protein interaction using bioinformatics tools. (December 2019)

• Record Type: Journal Article
• Authors: Zandonadi, Flávia S.; Castañeda Santa Cruz, Elisa; Korvala, Johanna
• Is Part Of: Computational biology and chemistry. Volume 83(2019)
• Publication Date: 2019-12
• Subjects: Syndecans -- Bioinformatics tools -- Multifunctional partners -- Biological function; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2019.107087
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: Researching procedure to predict new biology descriptions to SDC. Computacional approach to search Protein-interaction networks from re-assign LC-MS/MS data identification. Assigning and reanalyzing protein to predict SDC new function in non-canonical secretion system. The identification new SDC rules based on bioinformatics tools from potential ectodomain ligands perspective. Abstract: The precise roles for SDC have been complex to specify. Assigning and reanalyzing protein and peptide identification to novel protein functions is one of the most important challenges in postgenomic era. Here, we provide SDC molecular description to support, contextualize and reanalyze the corresponding protein-protein interaction (PPI). From SDC-1 data mining, we discuss the potential of bioinformatics tools to predict new biological rules of SDC. Using these methods, we have assembled new possibilities for SDC biology from PPI data, once, the understanding of biology complexity cannot be capture from one simple question.