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SVM-Based Prediction of Propeptide Cleavage Sites in Spider Toxins Identifies Toxin Innovation in an Australian Tarantula
Spider neurotoxins are commonly used as pharmacological tools and are a popular source of novel compounds with therapeutic and agrochemical potential. Since venom peptides are inherently toxic, the host spider must employ strategies to avoid adverse effects prior to venom use. It is partly for this...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3718798/ https://www.ncbi.nlm.nih.gov/pubmed/23894279 http://dx.doi.org/10.1371/journal.pone.0066279 |
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author | Wong, Emily S. W. Hardy, Margaret C. Wood, David Bailey, Timothy King, Glenn F. |
author_facet | Wong, Emily S. W. Hardy, Margaret C. Wood, David Bailey, Timothy King, Glenn F. |
author_sort | Wong, Emily S. W. |
collection | PubMed |
description | Spider neurotoxins are commonly used as pharmacological tools and are a popular source of novel compounds with therapeutic and agrochemical potential. Since venom peptides are inherently toxic, the host spider must employ strategies to avoid adverse effects prior to venom use. It is partly for this reason that most spider toxins encode a protective proregion that upon enzymatic cleavage is excised from the mature peptide. In order to identify the mature toxin sequence directly from toxin transcripts, without resorting to protein sequencing, the propeptide cleavage site in the toxin precursor must be predicted bioinformatically. We evaluated different machine learning strategies (support vector machines, hidden Markov model and decision tree) and developed an algorithm (SpiderP) for prediction of propeptide cleavage sites in spider toxins. Our strategy uses a support vector machine (SVM) framework that combines both local and global sequence information. Our method is superior or comparable to current tools for prediction of propeptide sequences in spider toxins. Evaluation of the SVM method on an independent test set of known toxin sequences yielded 96% sensitivity and 100% specificity. Furthermore, we sequenced five novel peptides (not used to train the final predictor) from the venom of the Australian tarantula Selenotypus plumipes to test the accuracy of the predictor and found 80% sensitivity and 99.6% 8-mer specificity. Finally, we used the predictor together with homology information to predict and characterize seven groups of novel toxins from the deeply sequenced venom gland transcriptome of S. plumipes, which revealed structural complexity and innovations in the evolution of the toxins. The precursor prediction tool (SpiderP) is freely available on ArachnoServer (http://www.arachnoserver.org/spiderP.html), a web portal to a comprehensive relational database of spider toxins. All training data, test data, and scripts used are available from the SpiderP website. |
format | Online Article Text |
id | pubmed-3718798 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37187982013-07-26 SVM-Based Prediction of Propeptide Cleavage Sites in Spider Toxins Identifies Toxin Innovation in an Australian Tarantula Wong, Emily S. W. Hardy, Margaret C. Wood, David Bailey, Timothy King, Glenn F. PLoS One Research Article Spider neurotoxins are commonly used as pharmacological tools and are a popular source of novel compounds with therapeutic and agrochemical potential. Since venom peptides are inherently toxic, the host spider must employ strategies to avoid adverse effects prior to venom use. It is partly for this reason that most spider toxins encode a protective proregion that upon enzymatic cleavage is excised from the mature peptide. In order to identify the mature toxin sequence directly from toxin transcripts, without resorting to protein sequencing, the propeptide cleavage site in the toxin precursor must be predicted bioinformatically. We evaluated different machine learning strategies (support vector machines, hidden Markov model and decision tree) and developed an algorithm (SpiderP) for prediction of propeptide cleavage sites in spider toxins. Our strategy uses a support vector machine (SVM) framework that combines both local and global sequence information. Our method is superior or comparable to current tools for prediction of propeptide sequences in spider toxins. Evaluation of the SVM method on an independent test set of known toxin sequences yielded 96% sensitivity and 100% specificity. Furthermore, we sequenced five novel peptides (not used to train the final predictor) from the venom of the Australian tarantula Selenotypus plumipes to test the accuracy of the predictor and found 80% sensitivity and 99.6% 8-mer specificity. Finally, we used the predictor together with homology information to predict and characterize seven groups of novel toxins from the deeply sequenced venom gland transcriptome of S. plumipes, which revealed structural complexity and innovations in the evolution of the toxins. The precursor prediction tool (SpiderP) is freely available on ArachnoServer (http://www.arachnoserver.org/spiderP.html), a web portal to a comprehensive relational database of spider toxins. All training data, test data, and scripts used are available from the SpiderP website. Public Library of Science 2013-07-22 /pmc/articles/PMC3718798/ /pubmed/23894279 http://dx.doi.org/10.1371/journal.pone.0066279 Text en © 2013 Wong et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Wong, Emily S. W. Hardy, Margaret C. Wood, David Bailey, Timothy King, Glenn F. SVM-Based Prediction of Propeptide Cleavage Sites in Spider Toxins Identifies Toxin Innovation in an Australian Tarantula |
title | SVM-Based Prediction of Propeptide Cleavage Sites in Spider Toxins Identifies Toxin Innovation in an Australian Tarantula |
title_full | SVM-Based Prediction of Propeptide Cleavage Sites in Spider Toxins Identifies Toxin Innovation in an Australian Tarantula |
title_fullStr | SVM-Based Prediction of Propeptide Cleavage Sites in Spider Toxins Identifies Toxin Innovation in an Australian Tarantula |
title_full_unstemmed | SVM-Based Prediction of Propeptide Cleavage Sites in Spider Toxins Identifies Toxin Innovation in an Australian Tarantula |
title_short | SVM-Based Prediction of Propeptide Cleavage Sites in Spider Toxins Identifies Toxin Innovation in an Australian Tarantula |
title_sort | svm-based prediction of propeptide cleavage sites in spider toxins identifies toxin innovation in an australian tarantula |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3718798/ https://www.ncbi.nlm.nih.gov/pubmed/23894279 http://dx.doi.org/10.1371/journal.pone.0066279 |
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