Faculty Opinions recommendation of Regulation of cellular metabolism by protein lysine acetylation.

2010 ◽  
Author(s):  
Jean Francois Dufour
Keyword(s):  
Cellular Metabolism ◽  
Lysine Acetylation ◽  
Protein Lysine Acetylation

scholarly journals Regulation of Cellular Metabolism by Protein Lysine Acetylation

Science ◽  
2010 ◽  
Vol 327 (5968) ◽  
pp. 1000-1004 ◽  
Author(s):  
S. Zhao ◽  
W. Xu ◽  
W. Jiang ◽  
W. Yu ◽  
Y. Lin ◽  
...  
Keyword(s):  
Cellular Metabolism ◽  
Lysine Acetylation ◽  
Protein Lysine Acetylation

scholarly journals HDAC4 Protein Regulates HIF1α Protein Lysine Acetylation and Cancer Cell Response to Hypoxia

2011 ◽  
Vol 286 (44) ◽  
pp. 38095-38102 ◽  
Author(s):  
Hao Geng ◽  
Chris T. Harvey ◽  
Janet Pittsenbarger ◽  
Qiong Liu ◽  
Tomasz M. Beer ◽  
...  
Keyword(s):  
Cancer Cell ◽  
Cell Response ◽  
Lysine Acetylation ◽  
Protein Lysine Acetylation

scholarly journals Protein lysine acetylation plays a regulatory role in Bacillus subtilis multicellularity

PLoS ONE ◽  
2018 ◽  
Vol 13 (9) ◽  
pp. e0204687 ◽  
Author(s):  
Alicyn Reverdy ◽  
Yun Chen ◽  
Evan Hunter ◽  
Kevin Gozzi ◽  
Yunrong Chai
Keyword(s):  
Bacillus Subtilis ◽  
Regulatory Role ◽  
Lysine Acetylation ◽  
Protein Lysine Acetylation

Deep learning based prediction of reversible HAT/HDAC-specific lysine acetylation

2019 ◽  
Vol 21 (5) ◽  
pp. 1798-1805 ◽  
Author(s):  
Kai Yu ◽  
Qingfeng Zhang ◽  
Zekun Liu ◽  
Yimeng Du ◽  
Xinjiao Gao ◽  
...  
Keyword(s):  
Deep Learning ◽  
Protein Interactions ◽  
Web Server ◽  
Data Sets ◽  
Lysine Acetylation ◽  
Protein Acetylation ◽  
Protein Protein Interactions ◽  
Cellular Processes ◽  
Protein Lysine Acetylation ◽  
Specific Regulation

Abstract Protein lysine acetylation regulation is an important molecular mechanism for regulating cellular processes and plays critical physiological and pathological roles in cancers and diseases. Although massive acetylation sites have been identified through experimental identification and high-throughput proteomics techniques, their enzyme-specific regulation remains largely unknown. Here, we developed the deep learning-based protein lysine acetylation modification prediction (Deep-PLA) software for histone acetyltransferase (HAT)/histone deacetylase (HDAC)-specific acetylation prediction based on deep learning. Experimentally identified substrates and sites of several HATs and HDACs were curated from the literature to generate enzyme-specific data sets. We integrated various protein sequence features with deep neural network and optimized the hyperparameters with particle swarm optimization, which achieved satisfactory performance. Through comparisons based on cross-validations and testing data sets, the model outperformed previous studies. Meanwhile, we found that protein–protein interactions could enrich enzyme-specific acetylation regulatory relations and visualized this information in the Deep-PLA web server. Furthermore, a cross-cancer analysis of acetylation-associated mutations revealed that acetylation regulation was intensively disrupted by mutations in cancers and heavily implicated in the regulation of cancer signaling. These prediction and analysis results might provide helpful information to reveal the regulatory mechanism of protein acetylation in various biological processes to promote the research on prognosis and treatment of cancers. Therefore, the Deep-PLA predictor and protein acetylation interaction networks could provide helpful information for studying the regulation of protein acetylation. The web server of Deep-PLA could be accessed at http://deeppla.cancerbio.info.

Sign in / Sign up

Export Citation Format

Share Document