The identification efficient enzymes and the development of effective enzyme cocktails are two of the key R&D elements of the emerging lignocellulose industry. Fungal enzymes are expected to be widely used in this industry. To take stock of the available data with a plan to translating them into knowledge to guide future R&D, we have manually curated fungal genes encoding biochemically characterized glycoside hydrolases. To facilitate comparative studies, we have standardized enzyme abbreviations and kinetic definitions, assigned Gene Ontology terms, and provided references to supporting evidence. Analysis of the curated information has already led to development of new tools for refining the classification of glycoside hydrolases.

Numerous fungal genes predicted to encode lignocellulolytic enzymes have been identified. But few of their encoding enzymes have been characterized biochemically. Although searches in databases such as NCBI are useful in identifying leads, results are not ranked based on the closest biochemically-characterized homologues. We have therefore constructed a searchable database that contains sequences with corresponding characterized enzymes.

Tables were created to display features such as enzyme names, species, gene ontology, specific activity, substrate specificity and optimal temperature and pH conditions. For each sequence/enzyme, links to other resources including PubMed, UniProt and GenBank are provided. Currently, over 400 individual enzymes have been collected. The database, mycoCLAP, will be used as a web-based tool for the identification and preliminary functional analysis of novel glycoside hydrolases.