Identification and prioritization of novel uncharacterized peptidases for biochemical characterization

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

Phylogenetic survey of the subtilase family and a data-mining-based search for new subtilisins from Bacillaceae

“…Due to the increasing number of genome sequencing projects, the amount of data on uncharacterised proteins is growing exponentially ( Rawlings, 2013 ). Many genomes encode multiple secreted proteases and many proteases can be found in different species ( Takimura et al, 2007 ).…”

“…Due to the increasing number of genome sequencing projects, the amount of data on uncharacterised proteins is growing exponentially ( Rawlings, 2013 ). This rapidly increasing online database provides an excellent resource for broadening the sequence space of subtilisins.…”

MEROPS: the database of proteolytic enzymes, their substrates and inhibitors

“…Table 1 shows that the number of peptidases that can be distinguished now exceeds 4000, each of which has been assigned a unique MEROPS identifier. Some of these identifiers have been set up for particular model organisms that have been the subject of genome sequencing projects, and the peptidase homologues have not yet been biochemically characterized ( 16 ). If these putative proteins are excluded, then the number of distinct biochemically characterized peptidases in release 9.9 is 2646.…”

Biochemical characterisation of a novel broad pH spectrum subtilisin from Fictibacillus arsenicusDSM 15822T

“…However, the classical approach of isolation and cultivation of microorganisms from a specific environment with the extraction of genomic DNA or the purification of proteins and gene identification is a time and labour‐intensive procedure [ 18 ]. The increasing number of genomic or metagenomic sequencing projects, which provide an exponentially growing amount of data on uncharacterised proteins due to automatic annotation, offers an alternative source for finding new protease genes for industrial applications [ 19 ]. We recently analysed this unused information and conducted a search for new uncharacterised subtilisins from the Bacillaceae family [ 6 ].…”