Supervised learning approaches for predicting Ebola-Human Protein-Protein interactions
Lopamudra Dey1, Sanjay Chakraborty2
1Department of Biomedical and Clinical Sciences, Linköping University, Sweden; Department of Computer Science & Engineering, Meghnad Saha Institute of Technology, Kolkata, India.
Gene
|January 19, 2025
Summary
This study predicts Ebola virus-human protein-protein interactions (PPIs) using machine learning. Deep feed-forward multi-layer perceptron (DMLP) achieved the highest accuracy, identifying 2655 potential human targets.
Area of Science:
- Computational Biology
- Bioinformatics
- Machine Learning in Virology
Background:
- Limited protein-protein interaction (PPI) data exists for the Ebola virus.
- Understanding host-pathogen interactions is crucial for combating viral infections.
Purpose of the Study:
- To predict novel protein-protein interactions (PPIs) between Ebola virus and human proteins.
- To develop a comprehensive database (EbolaInt) for Ebola virus PPIs.
- To identify potential human drug targets for Ebola virus infection.
Main Methods:
- Creation of a comprehensive Ebola virus-human PPI database (EbolaInt).
- Utilized sequence-based protein features, including amino acid structure and conjoint triad.
- Applied supervised machine learning algorithms: K-nearest neighbors (KNN), Random Forest (RF), Support Vector Machine (SVM), and Deep Feed-Forward Multi-Layer Perceptron (DMLP).
Main Results:
- The Deep Feed-Forward Multi-Layer Perceptron (DMLP) model demonstrated the highest predictive accuracy.
- DMLP successfully predicted 2655 potential human target proteins for interaction with Ebola virus proteins.
- Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses validated the predictions.
Conclusions:
- Machine learning, particularly DMLP, is effective for predicting Ebola virus-human PPIs.
- The identified potential targets offer avenues for developing antiviral therapies.
- The EbolaInt database serves as a valuable resource for future Ebola virus research.
Keywords:
Deep neural networkEbolaMachine learningMulti-layer perceptronProtein-Protein interactionsViral-host interactionMore Related Videos
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