ArticleDatabase : the journal of biological databases and curation2013
Identification and prioritization of novel uncharacterized peptidases for biochemical characterization.
Article in Database : the journal of biological databases and curation, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 8 citations in OpenAlex.
- In silico and experimental characterization of a new polyextremophilic subtilisin-like protease from3 Biotech · 2024Article
- Biochemical characterisation of a novel broad pH spectrum subtilisin from Fictibacillus arsenicus DSM 15822FEBS open bio · 2023Article
- New robust subtilisins from halotolerant and halophilic Bacillaceae.Applied microbiology and biotechnology · 2023Article
- Bioprospecting the microbiome of Red Sea Atlantis II brine pool for peptidases and biosynthetic genes with promising antibacterial activity.Microbial cell factories · 2022Article
- Phylogenetic survey of the subtilase family and a data-mining-based search for new subtilisins fromFrontiers in microbiology · 2022Article
- In Silico Analysis of Glutaminase from Different Species of Escherichia and Bacillus.Iranian journal of medical sciences · 2016Article
- MEROPS: the database of proteolytic enzymes, their substrates and inhibitors.Nucleic acids research · 2014Article
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Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Genome sequencing projects are generating enormous amounts of biological data that require analysis, which in turn identifies genes and proteins that require characterization. Enzymes that act on proteins are especially difficult to characterize because of the time required to distinguish one from another. This is particularly true of peptidases, the enzymes that activate, inactivate and degrade proteins. This article aims to identify clusters of sequences each of which represents the species variants of a single putative peptidase that is widely distributed and is thus merits biochemical characterization. The MEROPS database maintains large collections of sequences, references, substrate cleavage positions and inhibitor interactions of peptidases and their homologues. MEROPS also maintains a hierarchical classification of peptidase homologues, in which sequences are clustered as species variants of a single peptidase; homologous sequences are assembled into a family; and families are clustered into a clan. For each family, an alignment and a phylogenetic tree are generated. By assigning an identifier to a peptidase that has been biochemically characterized from a particular species (called a holotype), the identifier can be automatically extended to sequences from other species that cluster with the holotype. This permits transference of annotation from the holotype to other members of the cluster. By extending this concept to all peptidase homologues (including those of unknown function that have not been characterized) from model organisms representing all the major divisions of cellular life, clusters of sequences representing putative peptidases can also be identified. The 42 most widely distributed of these putative peptidases have been identified and discussed here and are prioritized as ideal candidates for biochemical characterization. Database URL: http://merops.sanger.ac.uk.
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