iSuc-PseOpt: Identifying lysine succinylation sites in proteins by incorporating sequence-coupling effects into...

Area of Science:

• Biochemistry
• Proteomics
• Bioinformatics

Background:

• Succinylation is a critical posttranslational modification (PTM) involving the addition of a succinyl group to lysine residues.
• Lysine succinylation impacts numerous biological processes and is implicated in various diseases.
• Accurately identifying succinylated sites is essential for both fundamental biological research and therapeutic drug development.

Purpose of the Study:

• To develop a computational method for predicting succinylation sites in protein sequences.
• To address the challenge of identifying specific lysine residues prone to succinylation within uncharacterized proteins.
• To provide a tool that assists in basic research and drug development by predicting succinylation sites.

Main Methods:

• Incorporation of sequence-coupling effects into the general pseudo amino acid composition.
• Optimization of the training dataset using K-nearest neighbors cleaning (KNNC) and inserting hypothetical training samples (IHTS) treatments.
• Development of a predictor named iSuc-PseOpt.

Main Results:

• The developed predictor, iSuc-PseOpt, demonstrated superior performance compared to existing methods.
• Rigorous cross-validation confirmed the remarkable accuracy and effectiveness of iSuc-PseOpt.
• A user-friendly web server for iSuc-PseOpt was established for easy access and utilization.

Conclusions:

• iSuc-PseOpt provides an effective computational solution for identifying protein succinylation sites.
• The tool simplifies the prediction process, making it accessible to researchers without deep computational expertise.
• This advancement supports further investigation into the roles of succinylation in biological systems and disease pathologies.