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Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches
Published on: October 13, 2022
Caspase cleavage sites in the human proteome: CaspDB, a database of predicted substrates
Sonu Kumar1, Bram J van Raam1, Guy S Salvesen1
1Sanford Burnham Medical Research Institute, La Jolla, California, United States of America.
Abstract:
Caspases are enzymes belonging to a conserved family of cysteine-dependent aspartic-specific proteases that are involved in vital cellular processes and play a prominent role in apoptosis and inflammation. Determining all relevant protein substrates of caspases remains a challenging task. Over 1500 caspase substrates have been discovered in the human proteome according to published data and new substrates are discovered on a daily basis. To aid the discovery process we developed a caspase cleavage prediction method using the recently published curated MerCASBA database of experimentally determined caspase substrates and a Random Forest classification method. On both internal and external test sets, the ranking of predicted cleavage positions is superior to all previously developed prediction methods. The in silico predicted caspase cleavage positions in human proteins are available from a relational database: CaspDB. Our database provides information about potential cleavage sites in a verified set of all human proteins collected in Uniprot and their orthologs, allowing for tracing of cleavage motif conservation. It also provides information about the positions of disease-annotated single nucleotide polymorphisms, and posttranslational modifications that may modulate the caspase cleaving efficiency.
Insights
Researchers developed a new method to predict caspase cleavage sites in proteins, aiding the discovery of caspase substrates involved in apoptosis and inflammation. The CaspDB database offers insights into cleavage motif conservation and disease-associated genetic variations.
Area of Science:
- Biochemistry
- Molecular Biology
- Proteomics
Background:
- Caspases are critical cysteine proteases regulating apoptosis and inflammation.
- Identifying caspase substrates is essential for understanding cellular processes but remains challenging.
- Over 1500 human caspase substrates are known, with ongoing discoveries.
Purpose of the Study:
- To develop an accurate computational method for predicting caspase cleavage sites.
- To create a comprehensive database of predicted caspase cleavage positions in human proteins.
Main Methods:
- Utilized the MerCASBA database of experimentally validated caspase substrates.
- Employed a Random Forest classification algorithm for prediction.
- Integrated predictions with Uniprot human proteome and orthologs.
Main Results:
- The developed prediction method demonstrated superior ranking of cleavage positions compared to existing approaches.
- Generated CaspDB, a relational database of in silico predicted caspase cleavage sites.
- CaspDB includes data on cleavage motif conservation, disease-associated SNPs, and PTMs.
Conclusions:
- The novel prediction method and CaspDB database significantly advance the identification of caspase substrates.
- CaspDB facilitates research into caspase function, disease mechanisms, and substrate regulation.
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