FastProtein-an automated software for in silico proteomic analysis

PeerJ. 2024 Oct 31:12:e18309. doi: 10.7717/peerj.18309. eCollection 2024.

Abstract

Although various tools provide proteomic information, each tool has limitations related to execution platforms, libraries, versions, and data output format. Integrating data generated from different software is a laborious process that can prolong analysis time. Here, we present FastProtein, a protein analysis pipeline that is user-friendly, easily installable, and outputs important information about subcellular location, transmembrane domains, signal peptide, molecular weight, isoelectric point, hydropathy, aromaticity, gene ontology, endoplasmic reticulum retention domains, and N-glycosylation domains. It also helps determine the presence of glycosylphosphatidylinositol and obtain functional information from InterProScan, PANTHER, Pfam, and alignment-based annotation searches. FastProtein provides the scientific community with an easy-to-use computational tool for proteomic data analysis. It is applicable to both small datasets and proteome-wide studies. It can be used through the command line interface mode or a web interface installed on a local server. FastProtein significantly enhances proteomics analysis workflows by producing multiple results in a single-step process, thereby streamlining and accelerating the overall analysis. 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 available at https://github.com/bioinformatics-ufsc/FastProtein.

Keywords: Docker; Proteomics; User-friendly proteomics; Web-based software.

MeSH terms

  • Computational Biology / methods
  • Computer Simulation
  • Databases, Protein
  • Humans
  • Proteomics* / methods
  • Software*

Grants and funding

This work was supported by Santa Catarina Research Foundation (Fundação de Amparo à Pesquisa e Inovação of Santa Catarina, FAPESC, Santa Catarina, Brazil) and CAPES (Coordination for the Improvement of Higher Education Personnel, Brazil, Grant: 88881.311316/2018-01). Eric Kazuo Kawagoe, Guilherme Augusto Maia, and Vilmar Benetti Filho received scholarships from CAPES (Coordination for the Improvement of Higher Education Personnel, Brazil). Tatiany AT Soratto was a recipient of a scholarship from Santa Catarina Research Foundation (Fundação de Amparo à Pesquisa e Inovação of Santa Catarina, FAPESC, Santa Catarina, Brazil). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.