SVM-based prediction of propeptide cleavage sites in spider toxins identifies toxin innovation in an Australian tarantula.

ABSTRACT: 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 predict

SUBMITTER: Wong ES 

PROVIDER: S-EPMC3718798 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature