Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine
The peptides derived from envelope proteins have been shown to inhibit the protein-protein interactions in the virus membrane fusion process and thus have a great potential to be developed into effective antiviral therapies. There are three types of envelope proteins each exhibiting distinct structu...
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my.um.eprints.162412017-07-05T08:41:25Z http://eprints.um.edu.my/16241/ Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine Xu, Y. Yu, S. Zou, J.W. Hu, G. Rahman, N.A. Othman, R. Tao, X. Huang, M. Q Science (General) T Technology (General) The peptides derived from envelope proteins have been shown to inhibit the protein-protein interactions in the virus membrane fusion process and thus have a great potential to be developed into effective antiviral therapies. There are three types of envelope proteins each exhibiting distinct structure folds. Although the exact fusion mechanism remains elusive, it was suggested that the three classes of viral fusion proteins share a similar mechanism of membrane fusion. The common mechanism of action makes it possible to correlate the properties of self-derived peptide inhibitors with their activities. Here we developed a support vector machine model using sequence-based statistical scores of self-derived peptide inhibitors as input features to correlate with their activities. The model displayed 92% prediction accuracy with the Matthew's correlation coefficient of 0.84, obviously superior to those using physicochemical properties and amino acid decomposition as input. The predictive support vector machine model for self-derived peptides of envelope proteins would be useful in development of antiviral peptide inhibitors targeting the virus fusion process. Public Library of Science 2015 Article PeerReviewed Xu, Y. and Yu, S. and Zou, J.W. and Hu, G. and Rahman, N.A. and Othman, R. and Tao, X. and Huang, M. (2015) Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine. PLoS ONE, 10 (12). ISSN 1932-6203 https://doi.org/10.1371/journal.pone.0144171 DOI:10.1371/journal.pone.0144171 |
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Q Science (General) T Technology (General) Xu, Y. Yu, S. Zou, J.W. Hu, G. Rahman, N.A. Othman, R. Tao, X. Huang, M. Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine |
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The peptides derived from envelope proteins have been shown to inhibit the protein-protein interactions in the virus membrane fusion process and thus have a great potential to be developed into effective antiviral therapies. There are three types of envelope proteins each exhibiting distinct structure folds. Although the exact fusion mechanism remains elusive, it was suggested that the three classes of viral fusion proteins share a similar mechanism of membrane fusion. The common mechanism of action makes it possible to correlate the properties of self-derived peptide inhibitors with their activities. Here we developed a support vector machine model using sequence-based statistical scores of self-derived peptide inhibitors as input features to correlate with their activities. The model displayed 92% prediction accuracy with the Matthew's correlation coefficient of 0.84, obviously superior to those using physicochemical properties and amino acid decomposition as input. The predictive support vector machine model for self-derived peptides of envelope proteins would be useful in development of antiviral peptide inhibitors targeting the virus fusion process. |
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Article |
author |
Xu, Y. Yu, S. Zou, J.W. Hu, G. Rahman, N.A. Othman, R. Tao, X. Huang, M. |
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Xu, Y. Yu, S. Zou, J.W. Hu, G. Rahman, N.A. Othman, R. Tao, X. Huang, M. |
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Xu, Y. |
title |
Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine |
title_short |
Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine |
title_full |
Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine |
title_fullStr |
Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine |
title_full_unstemmed |
Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine |
title_sort |
identification of peptide inhibitors of enveloped viruses using support vector machine |
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Public Library of Science |
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2015 |
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http://eprints.um.edu.my/16241/ https://doi.org/10.1371/journal.pone.0144171 |
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13.18916 |