Proteomic analysis and prediction of amino acid variations that influence protein posttranslational modifications. (17th May 2018)

• Record Type: Journal Article
• Authors: Shi, Shaoping; Wang, Lina; Cao, Man; Chen, Guodong; Yu, Jialin
• Is Part Of: Briefings in bioinformatics. Volume 20:Number 5(2020)
• Page Start: 1597
• Page End: 1606
• Publication Date: 2018-05-17
• Subjects: posttranslational modifications -- amino acid variations -- computational mutation analysis -- protein PTM predictor -- network biology; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bby036
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: Accumulative studies have indicated that amino acid variations through changing the type of residues of the target sites or key flanking residues could directly or indirectly influence protein posttranslational modifications (PTMs) and bring about a detrimental effect on protein function. Computational mutation analysis can greatly narrow down the efforts on experimental work. To increase the utilization of current computational resources, we first provide an overview of computational prediction of amino acid variations that influence protein PTMs and their functional analysis. We also discuss the challenges that are faced while developing novel in silico approaches in the future. The development of better methods for mutation analysis-related protein PTMs will help to facilitate the development of personalized precision medicine.