Literature DB >> 31034103

Functional analysis tools for post-translational modification: a post-translational modification database for analysis of proteins and metabolic pathways.

Edward R Cruz1, Hung Nguyen2, Tin Nguyen2, Ian S Wallace1,3.   

Abstract

Post-translational modifications (PTMs) are critical regulators of protein function, and nearly 200 different types of PTM have been identified. Advances in high-resolution mass spectrometry have led to the identification of an unprecedented number of PTM sites in numerous organisms, potentially facilitating a more complete understanding of how PTMs regulate cellular behavior. While databases have been created to house the resulting data, most of these resources focus on individual types of PTM, do not consider quantitative PTM analyses or do not provide tools for the visualization and analysis of PTM data. Here, we describe the Functional Analysis Tools for Post-Translational Modifications (FAT-PTM) database (https://bioinformatics.cse.unr.edu/fat-ptm/), which currently supports eight different types of PTM and over 49 000 PTM sites identified in large-scale proteomic surveys of the model organism Arabidopsis thaliana. The FAT-PTM database currently supports tools to visualize protein-centric PTM networks, quantitative phosphorylation site data from over 10 different quantitative phosphoproteomic studies, PTM information displayed in protein-centric metabolic pathways and groups of proteins that are co-modified by multiple PTMs. Overall, the FAT-PTM database provides users with a robust platform to share and visualize experimentally supported PTM data, develop hypotheses related to target proteins or identify emergent patterns in PTM data for signaling and metabolic pathways.
© 2019 The Authors The Plant Journal © 2019 John Wiley & Sons Ltd.

Entities:  

Keywords:  mass spectrometry; metabolic regulation; post-translational modifications; proteomic database; quantitative proteomics

Mesh:

Substances:

Year:  2019        PMID: 31034103     DOI: 10.1111/tpj.14372

Source DB:  PubMed          Journal:  Plant J        ISSN: 0960-7412            Impact factor:   6.417


  11 in total

Review 1.  Associations between phytohormones and cellulose biosynthesis in land plants.

Authors:  Liu Wang; Bret E Hart; Ghazanfar Abbas Khan; Edward R Cruz; Staffan Persson; Ian S Wallace
Journal:  Ann Bot       Date:  2020-10-06       Impact factor: 4.357

2.  The XVP/ NAC003 protein associates with the plasma membrane through KR rich regions and translocates to the nucleus by changing phosphorylation status.

Authors:  Kwang-Hee Lee; Sining Wang; Qian Du; Gaurav Thapa Chhetri; Liying Qi; Huanzhong Wang
Journal:  Plant Signal Behav       Date:  2021-09-09

3.  Post-translational Modifications in Brain Diseases: A Future for Biomarkers.

Authors:  Licia C Silva-Costa; Bradley J Smith
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 3.650

4.  Analysis of Posttranslational Modifications in Arabidopsis Proteins and Metabolic Pathways Using the FAT-PTM Database.

Authors:  Madison N Blea; Ian S Wallace
Journal:  Methods Mol Biol       Date:  2022

5.  Characterization and identification of lysine crotonylation sites based on machine learning method on both plant and mammalian.

Authors:  Rulan Wang; Zhuo Wang; Hongfei Wang; Yuxuan Pang; Tzong-Yi Lee
Journal:  Sci Rep       Date:  2020-11-24       Impact factor: 4.379

6.  Protein phosphorylation associated with drought priming-enhanced heat tolerance in a temperate grass species.

Authors:  Xiaxiang Zhang; Lili Zhuang; Yu Liu; Zhimin Yang; Bingru Huang
Journal:  Hortic Res       Date:  2020-12-01       Impact factor: 6.793

7.  qPTMplants: an integrative database of quantitative post-translational modifications in plants.

Authors:  Han Xue; Qingfeng Zhang; Panqin Wang; Bijin Cao; Chongchong Jia; Ben Cheng; Yuhua Shi; Wei-Feng Guo; Zhenlong Wang; Ze-Xian Liu; Han Cheng
Journal:  Nucleic Acids Res       Date:  2022-01-07       Impact factor: 16.971

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

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

Review 9.  Posttranslational Modification of Waxy to Genetically Improve Starch Quality in Rice Grain.

Authors:  Tosin Victor Adegoke; Yifeng Wang; Lijuan Chen; Huimei Wang; Wanning Liu; Xingyong Liu; Yi-Chen Cheng; Xiaohong Tong; Jiezheng Ying; Jian Zhang
Journal:  Int J Mol Sci       Date:  2021-05-03       Impact factor: 5.923

Review 10.  Central Metabolism in Mammals and Plants as a Hub for Controlling Cell Fate.

Authors:  Jennifer Selinski; Renate Scheibe
Journal:  Antioxid Redox Signal       Date:  2020-08-05       Impact factor: 8.401

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.