ArticleProtein science : a publication of the Protein Society1996
Cleavage site analysis in picornaviral polyproteins: discovering cellular targets by neural networks.
Article in Protein science : a publication of the Protein Society, 1996. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers.
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126 citing papers in PubMed.
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- Automated SSHHPS Analysis Predicts a Potential Host Protein Target Common to Several Neuroinvasive (+)ssRNA Viruses.Viruses · 2023Article
- Pseudotyped Viruses for Enterovirus.Advances in experimental medicine and biology · 2023Article
- Re-examination of nepovirus polyprotein cleavage sites highlights the diverse specificities and evolutionary relationships of nepovirus 3C-like proteases.Archives of virology · 2022Article
- Thirty years of molecular dynamics simulations on posttranslational modifications of proteins.Physical chemistry chemical physics : PCCP · 2022Review
- SARS-CoV-2 3CLpro whole human proteome cleavage prediction and enrichment/depletion analysis.Computational biology and chemistry · 2022Article
- An Emerging Duck Egg-Reducing Syndrome Caused by a Novel Picornavirus Containing Seven Putative 2A Peptides.Viruses · 2022Article
- Seneca Valley Virus 3CMicrobiology spectrum · 2022Article
- In silico prediction of Severe Acute Respiratory Syndrome Coronavirus 2 main protease cleavage sites.Proteins · 2022Article
- Seneca Valley Virus 3CFrontiers in microbiology · 2022Article
66 more citing papers are in PubMed but not listed here.
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4 authors.
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Abstract
Picornaviral proteinases are responsible for maturation cleavages of the viral polyprotein, but also catalyze the degradation of cellular targets. Using graphical visualization techniques and neural network algorithms, we have investigated the sequence specificity of the two proteinases 2Apro and 3Cpro. The cleavage of VP0 (giving rise to VP2 and VP4), which is carried out by a so-far unknown proteinase, was also examined. In combination with a novel surface exposure prediction algorithm, our neural network approach successfully distinguishes known cleavage sites from noncleavage sites and yields a more consistent definition of features common to these sites. The method is able to predict experimentally determined cleavage sites in cellular proteins. We present a list of mammalian and other proteins that are predicted to be possible targets for the viral proteinases. Whether these proteins are indeed cleaved awaits experimental verification. Additionally, we report several errors detected in the protein databases. A computer server for prediction of cleavage sites by picornaviral proteinases is publicly available at the e-mail address NetPicoRNA@cbs.dtu.dk or via WWW at http:@www.cbs.dtu.dk/services/NetPicoRNA/.
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