ArticlePloS one2014
Discriminating between lysine sumoylation and lysine acetylation using mRMR feature selection and analysis.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 15 citations in OpenAlex.
- PhoglyStruct: Prediction of phosphoglycerylated lysine residues using structural properties of amino acids.Scientific reports · 2018Article
- SUMOgo: Prediction of sumoylation sites on lysines by motif screening models and the effects of various post-translational modifications.Scientific reports · 2018Article
- Implications of Newly Identified Brain eQTL Genes and Their Interactors in Schizophrenia.Molecular therapy. Nucleic acids · 2018Article
- Identification and Analysis of Blood Gene Expression Signature for Osteoarthritis With Advanced Feature Selection Methods.Frontiers in genetics · 2018Article
- PhosphoPredict: A bioinformatics tool for prediction of human kinase-specific phosphorylation substrates and sites by integrating heterogeneous feature selection.Scientific reports · 2017Article
- Mal-Lys: prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection.Scientific reports · 2016Article
- DNABP: Identification of DNA-Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues.PloS one · 2016Article
- Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection.BioMed research international · 2015Article
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Authors and funding
7 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Post-translational modifications (PTMs) are crucial steps in protein synthesis and are important factors contributing to protein diversity. PTMs play important roles in the regulation of gene expression, protein stability and metabolism. Lysine residues in protein sequences have been found to be targeted for both types of PTMs: sumoylations and acetylations; however, each PTM has a different cellular role. As experimental approaches are often laborious and time consuming, it is challenging to distinguish the two types of PTMs on lysine residues using computational methods. In this study, we developed a method to discriminate between sumoylated lysine residues and acetylated residues. The method incorporated several features: PSSM 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 was selected from all of the incorporated features, with which the classifier achieved 92.14% accuracy with an MCC value of 0.7322. Analysis of the optimal feature set revealed some differences between acetylation and sumoylation. The results from our study also supported the previous finding that there exist different consensus motifs for the two types of PTMs. The results could suggest possible dominant factors governing the acetylation and sumoylation of lysine residues, shedding some light on the modification dynamics and molecular mechanisms of the two types of PTMs, and provide guidelines for experimental validations.
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