Function-based classification of carbohydrate-active enzymes by recognition of short, conserved peptide motifs.

ABSTRACT: Functional prediction of carbohydrate-active enzymes is difficult due to low sequence identity. However, similar enzymes often share a few short motifs, e.g., around the active site, even when the overall sequences are very different. To exploit this notion for functional prediction of carbohydrate-active enzymes, we developed a simple algorithm, peptide pattern recognition (PPR), that can divide proteins into groups of sequences that share a set of short conserved sequences. When this method was used on 118 glycoside hydrolase 5 proteins with 9% average pairwise identity and representing four characterized enzymatic functions, 97% of the proteins were sorted into groups correlating with their enzymatic activity. Furthermore, we analyzed 8,138 glycoside hydrolase 13 proteins including 204

SUBMITTER: Busk PK 

PROVIDER: S-EPMC3648057 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature