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Updated: Aug 24, 2025
Oligopeptide Competition Assay for Phosphorylation Site Determination
Published on: May 18, 2017
Accurately predicting microbial phosphorylation sites using evolutionary and structural features
Faisal Ahmed1, Iman Dehzangi2, Md Mehedi Hasan3
1Department of Computer Science and Engineering, United International University, Dhaka, Bangladesh; Department of Computer Science and Engineering, Premier University, Chattogram, Bangladesh.
Abstract:
Post-translational modification (PTM) is a biological process involving a protein's enzymatic changes after its translation by the ribosome. Phosphorylation is one of the most critical PTMs that occurs when a phosphate group interacts with an amino acid residue along protein sequence. It contributes to cell communication, DNA repair, and gene regulation. Predicting microbial phosphorylation sites can provide better understanding of host-pathogen interaction and the development of anti-microbial agents. Experimental methods such as mass spectrometry are time-consuming, laborious, and expensive. This paper proposes a new approach, called RotPhoPred, for predicting phospho-serine (pS), phospho-threonine (pT), and phospho-tyrosine (pY) sites in the microbial organism by integrating evolutionary bigram profile with structural information and using Rotation Forest as the classification technique. To the best of our knowledge, our extracted features and employed classifier have never been utilized for this task. Comparative results demonstrate that the RotPhoPred surpasses its peers in terms of different metrics such as sensitivity (90.0%, 75.4% and 78.2%), specificity (92.1%, 97.2% and 94.7%), accuracy (91.0%, 86.3%, 86.4%), and MCC (0.82, 0.74 and 0.74) for pS, pT, and pY sites predictions, respectively. RotPhoPred as a standalone predictor and all its source codes are publicly available at: https://github.com/faisalahm3d/RotPredPho.
Insights
This study introduces RotPhoPred, a novel computational tool for predicting microbial phosphorylation sites (pS, pT, pY). RotPhoPred integrates evolutionary and structural data, offering a faster, more accurate alternative to experimental methods for understanding host-pathogen interactions.
Area of Science:
- Biochemistry
- Bioinformatics
- Computational Biology
Background:
- Post-translational modifications (PTMs) are crucial for protein function.
- Phosphorylation, a key PTM, regulates vital cellular processes like communication and gene regulation.
- Predicting microbial phosphorylation sites aids in understanding host-pathogen interactions and developing antimicrobials, but experimental methods are costly and time-consuming.
Purpose of the Study:
- To develop an accurate and efficient computational method for predicting microbial phosphorylation sites.
- To introduce RotPhoPred, a novel predictor for phospho-serine (pS), phospho-threonine (pT), and phospho-tyrosine (pY) sites.
Main Methods:
- Integration of evolutionary bigram profiles with structural information.
- Utilizing Rotation Forest as the classification algorithm.
- Development of RotPhoPred, a novel approach for predicting microbial phosphorylation sites.
Main Results:
- RotPhoPred achieved high performance metrics: sensitivity (90.0% for pS, 75.4% for pT, 78.2% for pY), specificity (92.1% for pS, 97.2% for pT, 94.7% for pY), and accuracy (91.0% for pS, 86.3% for pT, 86.4% for pY).
- The study highlights the novelty of the extracted features and the employed classifier for this specific task.
- Comparative analysis demonstrated RotPhoPred's superiority over existing methods.
Conclusions:
- RotPhoPred offers a significant advancement in predicting microbial phosphorylation sites.
- The tool provides a valuable, cost-effective alternative to experimental prediction methods.
- RotPhoPred is publicly available, facilitating further research in microbial pathogenesis and drug development.
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