Literature DB >> 28917035

SelGenAmic: An Algorithm for Selenoprotein Gene Assembly.

Liang Jiang1, Qiong Liu2.   

Abstract

Computational methods for identifying selenoproteins have been developed rapidly in recent years. However, it is still difficult to identify the open reading frame (ORF) of eukaryotic selenoprotein gene, because the TGA codon for a selenocysteine (Sec) residue in the active center of selenoprotein is traditionally a terminal signal of protein translation. A gene assembly algorithm SelGenAmic has been constructed and presented in this chapter for identifying selenoprotein genes from eukaryotic genomes. A method based on this algorithm was developed to build an optimal TGA-containing-ORF for each TGA in a genome, followed by protein similarity analysis through conserved sequence alignments to screen out selenoprotein genes from these ORFs. This method improved the sensitivity of detecting selenoproteins from a genome due to the design that all TGAs in the genome were investigated for its possibility of decoding as a Sec residue. The method based on the SelGenAmic algorithm is capable of identifying eukaryotic selenoprotein genes from their genomes.

Entities:  

Keywords:  Gene assembly algorithm; Selenocysteine; Selenoprotein

Mesh:

Substances:

Year:  2018        PMID: 28917035     DOI: 10.1007/978-1-4939-7258-6_3

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  3 in total

1.  Bioinformatics of Selenoproteins.

Authors:  Didac Santesmasses; Marco Mariotti; Vadim N Gladyshev
Journal:  Antioxid Redox Signal       Date:  2020-04-23       Impact factor: 8.401

Review 2.  Bioinformatics of Metalloproteins and Metalloproteomes.

Authors:  Yan Zhang; Junge Zheng
Journal:  Molecules       Date:  2020-07-24       Impact factor: 4.411

Review 3.  Characterization and Quantification of Selenoprotein P: Challenges to Mass Spectrometry.

Authors:  Jérémy Lamarche; Luisa Ronga; Joanna Szpunar; Ryszard Lobinski
Journal:  Int J Mol Sci       Date:  2021-06-11       Impact factor: 5.923

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.