Literature DB >> 25236462

Proteomic analysis and prediction of human phosphorylation sites in subcellular level reveal subcellular specificity.

Xiang Chen1, Shao-Ping Shi2, Sheng-Bao Suo1, Hao-Dong Xu1, Jian-Ding Qiu2.   

Abstract

MOTIVATION: Protein phosphorylation is the most common post-translational modification (PTM) regulating major cellular processes through highly dynamic and complex signaling pathways. Large-scale comparative phosphoproteomic studies have frequently been done on whole cells or organs by conventional bottom-up mass spectrometry approaches, i.e at the phosphopeptide level. Using this approach, there is no way to know from where the phosphopeptide signal originated. Also, as a consequence of the scale of these studies, important information on the localization of phosphorylation sites in subcellular compartments (SCs) is not surveyed.
RESULTS: Here, we present a first account of the emerging field of subcellular phosphoproteomics where a support vector machine (SVM) approach was combined with a novel algorithm of discrete wavelet transform (DWT) to facilitate the identification of compartment-specific phosphorylation sites and to unravel the intricate regulation of protein phosphorylation. Our data reveal that the subcellular phosphorylation distribution is compartment type dependent and that the phosphorylation displays site-specific sequence motifs that diverge between SCs.
AVAILABILITY AND IMPLEMENTATION: The method and database both are available as a web server at: http://bioinfo.ncu.edu.cn/SubPhos.aspx. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 25236462     DOI: 10.1093/bioinformatics/btu598

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  9 in total

Review 1.  Electrostatic Interactions in Protein Structure, Folding, Binding, and Condensation.

Authors:  Huan-Xiang Zhou; Xiaodong Pang
Journal:  Chem Rev       Date:  2018-01-10       Impact factor: 60.622

2.  Multiple Protein Subcellular Locations Prediction Based on Deep Convolutional Neural Networks with Self-Attention Mechanism.

Authors:  Hanhan Cong; Hong Liu; Yi Cao; Yuehui Chen; Cheng Liang
Journal:  Interdiscip Sci       Date:  2022-01-23       Impact factor: 2.233

3.  A homology-based pipeline for global prediction of post-translational modification sites.

Authors:  Xiang Chen; Shao-Ping Shi; Hao-Dong Xu; Sheng-Bao Suo; Jian-Ding Qiu
Journal:  Sci Rep       Date:  2016-05-13       Impact factor: 4.379

4.  Nuclear Proteomics Uncovers Diurnal Regulatory Landscapes in Mouse Liver.

Authors:  Jingkui Wang; Daniel Mauvoisin; Eva Martin; Florian Atger; Antonio Núñez Galindo; Loïc Dayon; Federico Sizzano; Alessio Palini; Martin Kussmann; Patrice Waridel; Manfredo Quadroni; Vjekoslav Dulić; Felix Naef; Frédéric Gachon
Journal:  Cell Metab       Date:  2016-11-03       Impact factor: 27.287

5.  Quantitative analysis of the human ovarian carcinoma mitochondrial phosphoproteome.

Authors:  Na Li; Shehua Qian; Biao Li; Xianquan Zhan
Journal:  Aging (Albany NY)       Date:  2019-08-22       Impact factor: 5.682

6.  Computational Phosphorylation Network Reconstruction: An Update on Methods and Resources.

Authors:  Min Zhang; Guangyou Duan
Journal:  Methods Mol Biol       Date:  2021

Review 7.  Phosphoproteomics in the Age of Rapid and Deep Proteome Profiling.

Authors:  Nicholas M Riley; Joshua J Coon
Journal:  Anal Chem       Date:  2015-11-19       Impact factor: 6.986

8.  Sequence- and Structure-Based Analysis of Tissue-Specific Phosphorylation Sites.

Authors:  Nermin Pinar Karabulut; Dmitrij Frishman
Journal:  PLoS One       Date:  2016-06-22       Impact factor: 3.240

9.  Identifying Acetylation Protein by Fusing Its PseAAC and Functional Domain Annotation.

Authors:  Wang-Ren Qiu; Ao Xu; Zhao-Chun Xu; Chun-Hua Zhang; Xuan Xiao
Journal:  Front Bioeng Biotechnol       Date:  2019-12-06
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.