iSuc-PseAAC: predicting lysine succinylation in proteins by incorporating peptide position-specific propensity
Yan Xu1, Ya-Xin Ding1, Jun Ding1
1Department of Information and Computer Science, University of Science and Technology Beijing, Beijing 100083, China.
Scientific Reports
|June 19, 2015
Summary
A new computational method, iSuc-PseAAC, predicts lysine succinylation sites on proteins. This post-translational modification predictor achieves high accuracy and offers a user-friendly web server for researchers.
Area of Science:
- Biochemistry
- Proteomics
- Bioinformatics
Background:
- Lysine succinylation is a crucial post-translational modification (PTM) of proteins.
- Succinylation is implicated in various disease states.
- Experimental identification of succinylated sites is recent, necessitating computational approaches.
Purpose of the Study:
- To develop an accurate computational method for identifying protein lysine succinylation sites.
- To create a user-friendly web server for predicting succinylation sites.
Main Methods:
- Incorporation of peptide position-specific propensity into pseudo amino acid composition.
- Development of the iSuc-PseAAC predictor.
- Utilizing a support vector machine algorithm with rigorous leave-one-out cross-validation on a benchmark dataset.
Main Results:
- The iSuc-PseAAC predictor achieved 79.94% accuracy, 51.07% sensitivity, 89.42% specificity, and a MCC of 0.431.
- The predictor demonstrated promising performance on a stringent benchmark dataset.
- A user-friendly web server is available for public use.
Conclusions:
- The iSuc-PseAAC predictor is a promising computational tool for identifying protein lysine succinylation sites.
- This method can serve as a valuable high-throughput tool in PTM research.
- The accessible web server facilitates research without requiring deep mathematical understanding.
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