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bioRxiv · 10.1101/2023.12.19.572382

FastProtein: An automated software for in silico proteomic analysis

Abstract

BackgroundAlthough various tools provide proteomic information, each has its limitations regarding execution platforms, libraries, versions, and data output format. Therefore, integrating data analyses generated using different software programs is a manual process that can prolong the analysis time. ResultsThis paper presents FastProtein, a protein analysis pipeline tool developed in Java. This tool is user-friendly, easily installable, and provides important information regarding the subcellular location, transmembrane domains, signal peptide, molecular weight, isoelectric point, hydropathy, aromaticity, gene ontology, endoplasmic reticulum retention domains, and N- glycosylation domains of a protein. Furthermore, it helps determine the presence of glycosylphosphatidylinositol and obtain annotation information using InterProScan, PANTHER, PFam, and alignment-based annotation searches. Additionally, the software outputs a protein dataset with evidence of membrane localization. ConclusionsThe proposed tool provides the scientific community with an easy and user-friendly computational tool for proteomics data analysis. The tool is applicable to both small datasets and proteome-wide studies. It can be used in either the command line interface mode or through a web interface installed on a local server or via the BioLib web interface (http://biolib.com/UFSC/FastProtein). FastProtein also accelerates proteomics analysis routines by generating multiple results in a one-step run. The software is open-source and freely available. Installation and execution instructions, as well as the source code and test files generated for tool validation, are provided at https://github.com/bioinformatics-ufsc/FastProtein.

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BibTeXRIS

Moreira, R. S., Filho, V. B., Maia, G. A., Soratto, T. A. T., Kawagoe, E. K., Russi, B. C., Miletti, L. C., Wagner, G.. 2023-12-20. FastProtein: An automated software for in silico proteomic analysis. https://doi.org/10.1101/2023.12.19.572382

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