Shrestha Dutta, Amity University Kolkata
ConCysFind is a Java-based pipeline instrument that uses BioJava as a web-based tool to recognize preserved Amino acids such as cysteine, tryptophan, serine, threonine, tyrosine, and methionine, etc. ConCysFind assesses numerous arrangements considering the proteome of 21 plant species. This model investigation aimed at Cy’s as an evolutionarily preserved target for different redox PTM.
Post-translational modifications (PTM) of amino acid (AA) side chains in peptides control protein structure and process. PTMs rely upon particular AA characteristics. The reactivity of cysteine thiol-based PTMs is novel among all proteinaceous AA. This pipeline intends to help to recognize preserved AA of polypeptides or protein families dependent on the phylogenetic occurrence in the plant kingdom. The device is adjustable to incorporate any species. The level of AA preservation is taken as a marker for auxiliary and useful essentialness, particularly for PTM-based regulation. Further, this pipeline instrument gives knowledge into the advancement of these potentially regulated peptides. Examination of 33 translation elongation and release factors close by known redox proteins from Arabidopsis thaliana for preserved Cys residues affirmed the appropriateness of the tool for distinguishing preserved and functional PTM sites. Exemplarily, the redox affectability of cysteines in the eukaryotic release factor 1-1 (eRF1-1) was experimentally approved.
ConCysFind is an important device for the prediction of new potential protein PTM focuses on a wide range of species, in light of preserved AA throughout the plant kingdom. The recognized targets were effectively confirmed through protein biochemical assays. The pipeline is globally applicable to other phylogenetic branches by customization of the database.
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Source:- ConCysFind: a pipeline tool to predict conserved amino acids of protein sequences across the plant kingdom–Marten Moore, Corinna Wesemann, Nikolaj Gossmann, Arne Sahm, Jan Krüger, Alexander Sczyrba & Karl-Josef Dietz; BMC Bioinformatics volume 21, Article number: 490 (2020)
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