Prediction of Kunitz ion channel effectors and protease inhibitors from the Ixodes ricinus sialome
Language English Country Netherlands Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
25108785
DOI
10.1016/j.ttbdis.2014.07.016
PII: S1877-959X(14)00161-7
Knihovny.cz E-resources
- Keywords
- Function prediction, Kunitz, Machine learning, Tick, Transcriptome,
- MeSH
- Algorithms MeSH
- Protease Inhibitors MeSH
- Ion Channels genetics MeSH
- Ixodes genetics MeSH
- Protein Domains MeSH
- Arthropod Proteins genetics MeSH
- Amino Acid Sequence MeSH
- Sequence Analysis, DNA MeSH
- Cluster Analysis MeSH
- Salivary Proteins and Peptides genetics MeSH
- Transcriptome * MeSH
- High-Throughput Nucleotide Sequencing MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- Protease Inhibitors MeSH
- Ion Channels MeSH
- Arthropod Proteins MeSH
- Salivary Proteins and Peptides MeSH
In the next generation sequencing era we are encountering hundreds of thousands of sequences from specific organisms. Such massive data must be accurately classified both functionally and structurally. Determining appropriate sequences with a specific function from next generation sequencing, however, is a daunting experimental task. A recent salivary gland transcriptome from the hard tick Ixodes ricinus, a European disease vector, has been made publicly available. Among the protein families sequenced by the salivary gland transcriptome of I. ricinus, the Kunitz-domain is one of the highly represented protein families. Thus far, recent tick transciptomes solely classify (computationally) Kunitz sequences as putative serine protease inhibitors. We present here a novel method using a machine-learning algorithm to "fish" for candidate ion-channel effectors and loss of serine protease inhibitor function within the Kunitz-domain protein family of the I. ricinus salivary gland transcriptome. The models, data and scripts used in this work are available online from http://life.bsc.es/pid/web/imoal/kunitz-classification.html.
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