※ Computational resources of protein acetylation
Last updated: December 25, 2014
Introduction:
Protein acetylation especially lysine acetylation is one of the most ubiquitous post-translational modification (PTM), and plays important roles in most of biological processes. Identification of site-specific acetylated substrates is fundamental for understanding the molecular mechanisms of acetylation. Besides experimental approaches, prediction of potential candidates with computational methods has also attracted great attention for its convenience and fast-speed. Here, we present a summarization of computational resources of protein acetylation, including acetylation databases, prediction of acetylation sites, while N-alpha-terminal acetylation as well as internal lysine acetylation were included.
We apologized that the computational studies without any web links of databases or tools will not be included in this compendium, since it's not easy for experimentalists to use studies directly. We are grateful for users feedback. Please inform Dr. Zexian Liu, Dr. Yu Xue or Dr. Jian Ren to add, remove or update one or multiple web links below.
Index:
<2> Prediction of acetylation sites
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1. CPLA : CPLA 1.0: a self-developed integrated database of protein lysine acetylation (Liu Z., et al., 2011).
2. CPLM: CPLM: a self-developed database of protein lysine modifications including acetylation (Liu Z., et al., 2014).
3. HPRD release 9 : HPRD currently contains information for 16,972 PTMs which belong to various categories such as acetylation (259), while phosphorylation (10,858), dephosphorylation (3,118) and glycosylation (1,860) form the majority of the annotated PTMs. At least one enzyme responsible for PTMs has been annotated for 8,960 PTMs, which resulted in the documentation of 7,253 enzyme - substrate relationships (Keshava Prasad, et al., 2009).
4. dbPTM 2.0: integrates experimentally verified PTMs from several databases, and to annotate the predicted PTMs on Swiss-Prot proteins ,2,071 acetylation sites were included while most of which were N-alpha-terminal ones(Lee, et al., 2006).
5. SysPTM 1.1 (Mirror website): provides a systematic and sophisticated platform for proteomic PTM research, equipped not only with a knowledge base of manually curated multi-type modification data, but also with four fully developed, in-depth data mining tools. (Li, et al., 2009).
6. PhosphoSitePlus: a new version of PhosphoSite, is a web-based database to collect protein modification sites, including protein phosphorylation sites from scientific literature as well as high-throughput discovery programs. 8,052 acetylation sites were included while most of which were N-alpha-terminal ones(Hornbeck, et al., 2004).
7. HHMD: a comprehensive database for human histone modifications, which focuses on integrating useful histone modification information from experimental data. The acetylation sites on human histones were included (Zhang, et al., 2010).
<2> Prediction of acetylation sites:
1. PAIL 1.0: Prediction of Nepsilon-acetylation on internal lysines implemented in Bayesian Discriminant Method (Li, et al., 2006).
2. NetAcet 1.0: a web server predicts N-terminal acetylation sites. The method was trained on yeast data but, as mentioned in the article describing the method, it obtains similar performance values on mammalian substrates acetylated by NatA orthologs. (Kiemer, et al., 2005).
3. PredMod: combine experimental methods with clustering analysis of protein sequences to predict protein acetylation based on the sequence characteristics of acetylated lysines within histones (Basu, et al., 2009).
4. LysAcet 1.1: prediction of lysine acetylation by support vector machines (Li, et al., 2009).
5. PHOSIDA: a database as well as a predictor for in vivo human acetylation sites (Gnad et al. 2010).
6. N-Ace: a web tool for predicting the protein Acetylation site based on Support Vector Machine (SVM) (Lee, et al., 2010 ).
7. EnsemblePail: lysine Acetylation sites prediction using ensembles of Support Vector Machine classifiers (Xu, et al., 2010).
8. ASEB: a web server for KAT-specific acetylation site prediction (Li, et al., 2012).
9. PSKAcePred: position-specific analysis and prediction for protein lysine acetylation based on multiple features (Suo, et al., 2012).
10. bpbphka: accurate prediction of human lysine acetylation through bi-relative adapted binomial score Bayes feature representation (Shao, et al., 2012).
11. PLMLA: prediction of lysine methylation and lysine acetylation by combining multiple features (Shi, et al., 2012).
12. SSPKA: In silico identification of species-specific acetylation sites by integrating protein sequence-derived and functional features (Li,et al., 2014 ).