Dataset Information

Dataset of cocoa aspartic protease cleavage sites.

ABSTRACT: The data provide information in support of the research article, "The cleavage specificity of the aspartic protease of cocoa beans involved in the generation of the cocoa-specific aroma precursors" (Janek et al., 2016) [1]. Three different protein substrates were partially digested with the aspartic protease isolated from cocoa beans and commercial pepsin, respectively. The obtained peptide fragments were analyzed by matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/TOF-MS/MS) and identified using the MASCOT server. The N- and C-terminal ends of the peptide fragments were used to identify the corresponding in-vitro cleavage sites by comparison with the amino acid sequences of the substrate proteins. The same procedure was applied to identify the cleavage sites used by the cocoa aspartic protease during cocoa fermentation starting from the published amino acid sequences of oligopeptides isolated from fermented cocoa beans.

SUBMITTER: Janek K

PROVIDER: S-EPMC4950170 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Dataset of cocoa aspartic protease cleavage sites.

Janek Katharina K Niewienda Agathe A Wöstemeyer Johannes J Voigt Jürgen J

Data in brief 20160624

The data provide information in support of the research article, "The cleavage specificity of the aspartic protease of cocoa beans involved in the generation of the cocoa-specific aroma precursors" (Janek et al., 2016) [1]. Three different protein substrates were partially digested with the aspartic protease isolated from cocoa beans and commercial pepsin, respectively. The obtained peptide fragments were analyzed by matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry (M ...[more]

PMID: 27508221

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Project description:The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s). Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database) with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate sequence using machine learning techniques. It is freely available at http://lightning.med.monash.edu.au/PROSPER/.

Dataset Information

Dataset of cocoa aspartic protease cleavage sites.

Publications

Dataset of cocoa aspartic protease cleavage sites.

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