A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers
Study of interface residue pairs is important for understanding the interactions between monomers inside a trimer protein–protein complex. We developed a two-layer support vector machine (SVM) ensemble-classifier that considers physicochemical and geometric properties of amino acids and the influenc...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-09-01
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| Series: | Molecules |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1420-3049/25/19/4353 |
| _version_ | 1797552925436805120 |
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| author | Yanfen Lyu Xinqi Gong |
| author_facet | Yanfen Lyu Xinqi Gong |
| author_sort | Yanfen Lyu |
| collection | DOAJ |
| description | Study of interface residue pairs is important for understanding the interactions between monomers inside a trimer protein–protein complex. We developed a two-layer support vector machine (SVM) ensemble-classifier that considers physicochemical and geometric properties of amino acids and the influence of surrounding amino acids. Different descriptors and different combinations may give different prediction results. We propose feature combination engineering based on correlation coefficients and F-values. The accuracy of our method is 65.38% in independent test set, indicating biological significance. Our predictions are consistent with the experimental results. It shows the effectiveness and reliability of our method to predict interface residue pairs of protein trimers. |
| first_indexed | 2024-03-10T16:08:01Z |
| format | Article |
| id | doaj.art-bc0a8db67a434d6f857dc9338b459cfb |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-10T16:08:01Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-bc0a8db67a434d6f857dc9338b459cfb2023-11-20T14:44:05ZengMDPI AGMolecules1420-30492020-09-012519435310.3390/molecules25194353A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein TrimersYanfen Lyu0Xinqi Gong1Mathematical Intelligence Application Lab, Institute for Mathematical Sciences, School of Math, Renmin University of China, Beijing 100872, ChinaMathematical Intelligence Application Lab, Institute for Mathematical Sciences, School of Math, Renmin University of China, Beijing 100872, ChinaStudy of interface residue pairs is important for understanding the interactions between monomers inside a trimer protein–protein complex. We developed a two-layer support vector machine (SVM) ensemble-classifier that considers physicochemical and geometric properties of amino acids and the influence of surrounding amino acids. Different descriptors and different combinations may give different prediction results. We propose feature combination engineering based on correlation coefficients and F-values. The accuracy of our method is 65.38% in independent test set, indicating biological significance. Our predictions are consistent with the experimental results. It shows the effectiveness and reliability of our method to predict interface residue pairs of protein trimers.https://www.mdpi.com/1420-3049/25/19/4353a two-layer SVM ensemble-classifiertrimer protein–protein complexesfeature combination engineering |
| spellingShingle | Yanfen Lyu Xinqi Gong A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers Molecules a two-layer SVM ensemble-classifier trimer protein–protein complexes feature combination engineering |
| title | A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers |
| title_full | A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers |
| title_fullStr | A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers |
| title_full_unstemmed | A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers |
| title_short | A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers |
| title_sort | two layer svm ensemble classifier to predict interface residue pairs of protein trimers |
| topic | a two-layer SVM ensemble-classifier trimer protein–protein complexes feature combination engineering |
| url | https://www.mdpi.com/1420-3049/25/19/4353 |
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