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Pripper: prediction of caspase cleavage sites from whole proteomes
BACKGROUND: Caspases are a family of proteases that have central functions in programmed cell death (apoptosis) and inflammation. Caspases mediate their effects through aspartate-specific cleavage of their target proteins, and at present almost 400 caspase substrates are known. There are several met...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2893604/ https://www.ncbi.nlm.nih.gov/pubmed/20546630 http://dx.doi.org/10.1186/1471-2105-11-320 |
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author | Piippo, Mirva Lietzén, Niina Nevalainen, Olli S Salmi, Jussi Nyman, Tuula A |
author_facet | Piippo, Mirva Lietzén, Niina Nevalainen, Olli S Salmi, Jussi Nyman, Tuula A |
author_sort | Piippo, Mirva |
collection | PubMed |
description | BACKGROUND: Caspases are a family of proteases that have central functions in programmed cell death (apoptosis) and inflammation. Caspases mediate their effects through aspartate-specific cleavage of their target proteins, and at present almost 400 caspase substrates are known. There are several methods developed to predict caspase cleavage sites from individual proteins, but currently none of them can be used to predict caspase cleavage sites from multiple proteins or entire proteomes, or to use several classifiers in combination. The possibility to create a database from predicted caspase cleavage products for the whole genome could significantly aid in identifying novel caspase targets from tandem mass spectrometry based proteomic experiments. RESULTS: Three different pattern recognition classifiers were developed for predicting caspase cleavage sites from protein sequences. Evaluation of the classifiers with quality measures indicated that all of the three classifiers performed well in predicting caspase cleavage sites, and when combining different classifiers the accuracy increased further. A new tool, Pripper, was developed to utilize the classifiers and predict the caspase cut sites from an arbitrary number of input sequences. A database was constructed with the developed tool, and it was used to identify caspase target proteins from tandem mass spectrometry data from two different proteomic experiments. Both known caspase cleavage products as well as novel cleavage products were identified using the database demonstrating the usefulness of the tool. Pripper is not restricted to predicting only caspase cut sites, but it gives the possibility to scan protein sequences for any given motif(s) and predict cut sites once a suitable cut site prediction model for any other protease has been developed. Pripper is freely available and can be downloaded from http://users.utu.fi/mijopi/Pripper. CONCLUSIONS: We have developed Pripper, a tool for reading an arbitrary number of proteins in FASTA format, predicting their caspase cleavage sites and outputting the cleaved sequences to a new FASTA format sequence file. We show that Pripper is a valuable tool in identifying novel caspase target proteins from modern proteomics experiments. |
format | Text |
id | pubmed-2893604 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-28936042010-06-30 Pripper: prediction of caspase cleavage sites from whole proteomes Piippo, Mirva Lietzén, Niina Nevalainen, Olli S Salmi, Jussi Nyman, Tuula A BMC Bioinformatics Software BACKGROUND: Caspases are a family of proteases that have central functions in programmed cell death (apoptosis) and inflammation. Caspases mediate their effects through aspartate-specific cleavage of their target proteins, and at present almost 400 caspase substrates are known. There are several methods developed to predict caspase cleavage sites from individual proteins, but currently none of them can be used to predict caspase cleavage sites from multiple proteins or entire proteomes, or to use several classifiers in combination. The possibility to create a database from predicted caspase cleavage products for the whole genome could significantly aid in identifying novel caspase targets from tandem mass spectrometry based proteomic experiments. RESULTS: Three different pattern recognition classifiers were developed for predicting caspase cleavage sites from protein sequences. Evaluation of the classifiers with quality measures indicated that all of the three classifiers performed well in predicting caspase cleavage sites, and when combining different classifiers the accuracy increased further. A new tool, Pripper, was developed to utilize the classifiers and predict the caspase cut sites from an arbitrary number of input sequences. A database was constructed with the developed tool, and it was used to identify caspase target proteins from tandem mass spectrometry data from two different proteomic experiments. Both known caspase cleavage products as well as novel cleavage products were identified using the database demonstrating the usefulness of the tool. Pripper is not restricted to predicting only caspase cut sites, but it gives the possibility to scan protein sequences for any given motif(s) and predict cut sites once a suitable cut site prediction model for any other protease has been developed. Pripper is freely available and can be downloaded from http://users.utu.fi/mijopi/Pripper. CONCLUSIONS: We have developed Pripper, a tool for reading an arbitrary number of proteins in FASTA format, predicting their caspase cleavage sites and outputting the cleaved sequences to a new FASTA format sequence file. We show that Pripper is a valuable tool in identifying novel caspase target proteins from modern proteomics experiments. BioMed Central 2010-06-15 /pmc/articles/PMC2893604/ /pubmed/20546630 http://dx.doi.org/10.1186/1471-2105-11-320 Text en Copyright ©2010 Piippo et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Piippo, Mirva Lietzén, Niina Nevalainen, Olli S Salmi, Jussi Nyman, Tuula A Pripper: prediction of caspase cleavage sites from whole proteomes |
title | Pripper: prediction of caspase cleavage sites from whole proteomes |
title_full | Pripper: prediction of caspase cleavage sites from whole proteomes |
title_fullStr | Pripper: prediction of caspase cleavage sites from whole proteomes |
title_full_unstemmed | Pripper: prediction of caspase cleavage sites from whole proteomes |
title_short | Pripper: prediction of caspase cleavage sites from whole proteomes |
title_sort | pripper: prediction of caspase cleavage sites from whole proteomes |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2893604/ https://www.ncbi.nlm.nih.gov/pubmed/20546630 http://dx.doi.org/10.1186/1471-2105-11-320 |
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