PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy

Jiangning Song, Fuyi Li, Andre Leier, Tatiana Marquez-Lago, Tatsuya Akutsu, Gholamreza Haffari, Kuo-Chen Chou, Geoffrey Ian Bawtree Webb, Robert Neil Pike

Research output: Contribution to journalArticleResearchpeer-review

48 Citations (Scopus)

Abstract

Summary Proteases are enzymes that specifically cleave the peptide backbone of their target proteins. As an important type of irreversible post-translational modification, protein cleavage underlies many key physiological processes. When dysregulated, proteases' actions are associated with numerous diseases. Many proteases are highly specific, cleaving only those target substrates that present certain particular amino acid sequence patterns. Therefore, tools that successfully identify potential target substrates for proteases may also identify previously unknown, physiologically relevant cleavage sites, thus providing insights into biological processes and guiding hypothesis-driven experiments aimed at verifying protease-substrate interaction. In this work, we present PROSPERous, a tool for rapid in silico prediction of protease-specific cleavage sites in substrate sequences. Our tool is based on logistic regression models and uses different scoring functions and their pairwise combinations to subsequently predict potential cleavage sites. PROSPERous represents a state-of-the-art tool that enables fast, accurate and high-throughput prediction of substrate cleavage sites for 90 proteases. Availability and implementation http://prosperous.erc.monash.edu/ Contact jiangning.song@monash.edu or geoff.webb@monash.edu or r.pike@latrobe.edu.au Supplementary informationSupplementary dataare available at Bioinformatics online.

Original languageEnglish
Pages (from-to)684-687
Number of pages4
JournalBioinformatics
Volume34
Issue number4
DOIs
Publication statusPublished - 15 Feb 2018

Cite this

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title = "PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy",
abstract = "Summary Proteases are enzymes that specifically cleave the peptide backbone of their target proteins. As an important type of irreversible post-translational modification, protein cleavage underlies many key physiological processes. When dysregulated, proteases' actions are associated with numerous diseases. Many proteases are highly specific, cleaving only those target substrates that present certain particular amino acid sequence patterns. Therefore, tools that successfully identify potential target substrates for proteases may also identify previously unknown, physiologically relevant cleavage sites, thus providing insights into biological processes and guiding hypothesis-driven experiments aimed at verifying protease-substrate interaction. In this work, we present PROSPERous, a tool for rapid in silico prediction of protease-specific cleavage sites in substrate sequences. Our tool is based on logistic regression models and uses different scoring functions and their pairwise combinations to subsequently predict potential cleavage sites. PROSPERous represents a state-of-the-art tool that enables fast, accurate and high-throughput prediction of substrate cleavage sites for 90 proteases. Availability and implementation http://prosperous.erc.monash.edu/ Contact jiangning.song@monash.edu or geoff.webb@monash.edu or r.pike@latrobe.edu.au Supplementary informationSupplementary dataare available at Bioinformatics online.",
author = "Jiangning Song and Fuyi Li and Andre Leier and Tatiana Marquez-Lago and Tatsuya Akutsu and Gholamreza Haffari and Kuo-Chen Chou and Webb, {Geoffrey Ian Bawtree} and Pike, {Robert Neil}",
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PROSPERous : high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy. / Song, Jiangning; Li, Fuyi; Leier, Andre; Marquez-Lago, Tatiana; Akutsu, Tatsuya; Haffari, Gholamreza; Chou, Kuo-Chen; Webb, Geoffrey Ian Bawtree; Pike, Robert Neil.

In: Bioinformatics, Vol. 34, No. 4, 15.02.2018, p. 684-687.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Song, Jiangning

AU - Li, Fuyi

AU - Leier, Andre

AU - Marquez-Lago, Tatiana

AU - Akutsu, Tatsuya

AU - Haffari, Gholamreza

AU - Chou, Kuo-Chen

AU - Webb, Geoffrey Ian Bawtree

AU - Pike, Robert Neil

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N2 - Summary Proteases are enzymes that specifically cleave the peptide backbone of their target proteins. As an important type of irreversible post-translational modification, protein cleavage underlies many key physiological processes. When dysregulated, proteases' actions are associated with numerous diseases. Many proteases are highly specific, cleaving only those target substrates that present certain particular amino acid sequence patterns. Therefore, tools that successfully identify potential target substrates for proteases may also identify previously unknown, physiologically relevant cleavage sites, thus providing insights into biological processes and guiding hypothesis-driven experiments aimed at verifying protease-substrate interaction. In this work, we present PROSPERous, a tool for rapid in silico prediction of protease-specific cleavage sites in substrate sequences. Our tool is based on logistic regression models and uses different scoring functions and their pairwise combinations to subsequently predict potential cleavage sites. PROSPERous represents a state-of-the-art tool that enables fast, accurate and high-throughput prediction of substrate cleavage sites for 90 proteases. Availability and implementation http://prosperous.erc.monash.edu/ Contact jiangning.song@monash.edu or geoff.webb@monash.edu or r.pike@latrobe.edu.au Supplementary informationSupplementary dataare available at Bioinformatics online.

AB - Summary Proteases are enzymes that specifically cleave the peptide backbone of their target proteins. As an important type of irreversible post-translational modification, protein cleavage underlies many key physiological processes. When dysregulated, proteases' actions are associated with numerous diseases. Many proteases are highly specific, cleaving only those target substrates that present certain particular amino acid sequence patterns. Therefore, tools that successfully identify potential target substrates for proteases may also identify previously unknown, physiologically relevant cleavage sites, thus providing insights into biological processes and guiding hypothesis-driven experiments aimed at verifying protease-substrate interaction. In this work, we present PROSPERous, a tool for rapid in silico prediction of protease-specific cleavage sites in substrate sequences. Our tool is based on logistic regression models and uses different scoring functions and their pairwise combinations to subsequently predict potential cleavage sites. PROSPERous represents a state-of-the-art tool that enables fast, accurate and high-throughput prediction of substrate cleavage sites for 90 proteases. Availability and implementation http://prosperous.erc.monash.edu/ Contact jiangning.song@monash.edu or geoff.webb@monash.edu or r.pike@latrobe.edu.au Supplementary informationSupplementary dataare available at Bioinformatics online.

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