DICED (Database of Identified Cleavage Sites Endemic to Diseases States): A Searchable Web Interface for Terminomics/Degradomics.

Abstract

Proteolysis is an irreversible posttranslational modification with immense biological impact. Owing to its high disease significance, there is growing interest in investigating proteolysis on the proteome scale, termed degradomics. We developed 'Database of Identified Cleavage sites Endemic to Disease states' (DICED; https://diced.lerner.ccf.org/), as a searchable knowledgebase to promote collaboration and knowledge sharing in degradomics. DICED was designed and constructed using Python, JavaScript, HTML, and PostgreSQL. Django (https://www.djangoproject.com) was chosen as the primary framework for its security features and support for agile development. DICED can be utilized on major web browsers and operating systems for easy access to high-throughput mass spectrometry-identified cleaved protein termini. The data was obtained using N-terminomics, comprising N-terminal protein labeling, labeled peptide enrichment, mass spectrometry and positional peptide annotation. The DICED database contains experimentally derived N-terminomics peptide datasets from tissues, diseases, or digests of tissue protein libraries using individual proteases and is searchable using UniProt ID, protein name, gene symbol or up to 100 peptide sequences. The tabular output format can be exported as a CSV file. Although DICED presently accesses data from a single laboratory, it is freely available as a Galaxy tool and the underlying database is scalable, permitting addition of new datasets and features.