A method to distinguish between lysine acetylation and lysine ubiquitination with feature selection and analysis

Abstract

Lysine acetylation and ubiquitination are two primary post-translational modifications (PTMs) in most eukaryotic proteins. Lysine residues are targets for both types of PTMs, resulting in different cellular roles. With the increasing availability of protein sequences and PTM data, it is challenging to distinguish the two types of PTMs on lysine residues. Experimental approaches are often laborious and time consuming. There is an urgent need for computational tools to distinguish between lysine acetylation and ubiquitination. In this study, we developed a novel method, called DAUFSA (distinguish between lysine acetylation and lysine ubiquitination with feature selection and analysis), to discriminate ubiquitinated and acetylated lysine residues. The method incorporated several types of features: PSSM (position-specific scoring matrix) conservation scores, amino acid factors, secondary structures, solvent accessibilities, and disorder scores. By using the mRMR (maximum relevance minimum redundancy) method and the IFS (incremental feature selection) method, an optimal feature set containing 290 features was selected from all incorporated features. A dagging-based classifier constructed by the optimal features achieved a classification accuracy of 69.53%, with an MCC of .3853. An optimal feature set analysis showed that the PSSM conservation score features and the amino acid factor features were the most important attributes, suggesting differences between acetylation and ubiquitination. Our study results also supported previous findings that different motifs were employed by acetylation and ubiquitination. The feature differences between the two modifications revealed in this study are worthy of experimental validation and further investigation.

Keywords:

• ubiquitination
• acetylation
• post-translational modification
• dagging
• incremental feature selection

Additional information

Funding

This work was supported by grants from the National Basic Research Program of China [grant numbers 2011CB510101, 2011CB510102]; the National Natural Science Foundation of China [grant numbers 61401302, 31371335, 81171342, 81201148, 31050110432, 31150110577]; the Tianjin Research Program of Application Foundation and Advanced Technology [grant number 14JCQNJC09500], the Specialized Research Fund for the Doctoral Program of Higher Education of China [grant numbers 20130032120070, 20130031120001, 20120032120073]; the Seed Foundation of Tianjin University [grant numbers 60302064, 60302069]; and the Innovation Program of Shanghai Municipal Education Commission [grant number 12ZZ087] for the grant titled ‘The First-class Discipline of Universities in Shanghai.’