LAceP: lysine acetylation site prediction using logistic regression classifiers

PLoS One. 2014 Feb 20;9(2):e89575. doi: 10.1371/journal.pone.0089575. eCollection 2014.


Background: Lysine acetylation is a crucial type of protein post-translational modification, which is involved in many important cellular processes and serious diseases. However, identification of protein acetylated sites through traditional experiment methods is time-consuming and laborious. Those methods are not suitable to identify a large number of acetylated sites quickly. Therefore, computational methods are still very valuable to accelerate lysine acetylated site finding.

Result: In this study, many biological characteristics of acetylated sites have been investigated, such as the amino acid sequence around the acetylated sites, the physicochemical property of the amino acids and the transition probability of adjacent amino acids. A logistic regression method was then utilized to integrate these information for generating a novel lysine acetylation prediction system named LAceP. When compared with existing methods, LAceP overwhelms most of state-of-the-art methods. Especially, LAceP has a more balanced prediction capability for positive and negative datasets.

Conclusion: LAceP can integrate different biological features to predict lysine acetylation with high accuracy. An online web server is freely available at

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acetylation
  • Algorithms
  • Computational Biology*
  • Databases, Protein
  • Humans
  • Logistic Models
  • Lysine / metabolism*
  • Protein Processing, Post-Translational*
  • Proteins / metabolism*
  • Software*


  • Proteins
  • Lysine

Grants and funding

This work was supported by grants from the National Natural Science Foundation of China (61272250, .31100957), the National Basic Research Program of China (2013CB956103), SA-SIBS Scholarship Program, and the National High-Tech R&D Program (863) (2012AA101601). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.