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Computational prediction of furin cleavage sites by a hybrid method and understanding mechanism underlying diseases.

ABSTRACT: Furin cleaves diverse types of protein precursors in the secretory pathway. The substrates for furin cleavage possess a specific 20-residue recognition sequence motif. In this report, based on the functional characterisation of the 20-residue sequence motif, we developed a furin cleavage site prediction tool, PiTou, using a hybrid method composed of a hidden Markov model and biological knowledge-based cumulative probability score functions. PiTou can accurately predict the presence and location of furin cleavage sites in protein sequences with high sensitivity (96.9%) and high specificity (97.3%). PiTou's prediction scores are biological meaningful and reflect binding strength and solvent accessibility of furin substrates. A prediction result is interpreted within cellular contexts: subcellular localisation, cellular function and interference by other dynamic protein modifications. Combining next-generation sequencing, PiTou can help with elucidating the molecular mechanism of furin cleavage-associated human diseases. PiTou has been made freely available at the associated website.

SUBMITTER: Tian S

PROVIDER: S-EPMC3281273 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Computational prediction of furin cleavage sites by a hybrid method and understanding mechanism underlying diseases.

Tian Sun S Huajun Wang W Wu Jianhua J

Scientific reports 20120216

Furin cleaves diverse types of protein precursors in the secretory pathway. The substrates for furin cleavage possess a specific 20-residue recognition sequence motif. In this report, based on the functional characterisation of the 20-residue sequence motif, we developed a furin cleavage site prediction tool, PiTou, using a hybrid method composed of a hidden Markov model and biological knowledge-based cumulative probability score functions. PiTou can accurately predict the presence and location ...[more]

PMID: 22355773

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Project description:BackgroundCaspases 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.ResultsThree 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.ConclusionsWe 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.

Dataset Information

Computational prediction of furin cleavage sites by a hybrid method and understanding mechanism underlying diseases.

Publications

Computational prediction of furin cleavage sites by a hybrid method and understanding mechanism underlying diseases.

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