Cascleave 2.0, a new approach for predicting caspase and granzyme cleavage targets

Mingjun Wang1, Xing-Ming Zhao, Hao Tan

  • 1National Engineering Laboratory for Industrial Enzymes and Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, Department of Computer Science, School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Victoria 3800, Australia, Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan and ARC Centre of Excellence for Structural and Functional Microbial Genomics, Monash University, Melbourne, Victoria 3800, Australia.

Abstract

Insights

A new bioinformatics tool, Cascleave 2.0, accurately predicts caspase and granzyme B (GrB) cleavage sites. This tool enhances understanding of protease function and aids in discovering new substrates for caspases and GrB.

Area of Science:

  • Proteomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Caspases and granzyme B (GrB) are key proteases in cellular processes like programmed cell death, necrosis, and inflammation.
  • While many substrates are known, a complete understanding of caspases and GrB substrate specificity is lacking.
  • Bioinformatics analysis of cleavage sites can reveal substrate specificity and identify novel substrates.

Purpose of the Study:

  • To develop a bioinformatics tool for predicting caspase-specific and GrB cleavage sites.
  • To improve prediction accuracy by integrating diverse sequence and functional protein information.
  • To facilitate the discovery of novel substrates for caspases and GrB.

Main Methods:

  • Development of the Cascleave 2.0 bioinformatics tool, an advancement of the Cascleave tool.
  • Integration of heterogeneous sequence and protein functional data.
  • Application of maximum relevance minimum redundancy and forward feature selection for feature optimization.
  • Systematic evaluation using benchmark and independent test datasets.

Main Results:

  • Cascleave 2.0 accurately predicts specific cleavage sites for human caspase-1, 3, 6, 7, 8, and GrB.
  • The tool integrates diverse data for enhanced prediction accuracy.
  • Cascleave 2.0 outperforms existing state-of-the-art tools in protease-specific cleavage site prediction.
  • Feature selection methods identified and removed redundant and irrelevant features.

Conclusions:

  • Cascleave 2.0 is a powerful tool for identifying novel caspase and GrB substrates and cleavage sites.
  • The tool aids in understanding the functional roles of these proteases in human proteolytic cascades.
  • Accurate prediction of cleavage sites contributes to a deeper understanding of cellular signaling pathways.

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