Confronting the catalytic dark matter encoded by sequenced genomes.

Area of Science:

• Proteomics
• Enzymology
• Bioinformatics

Background:

• The post-genomic era yields vast protein sequence data.
• A substantial portion of these proteins have unknown functions.
• Identifying enzyme functions is crucial for biological understanding.

Purpose of the Study:

• To quantify enzymes with uncertain or unknown functions in yeast and human proteomes.
• To review methods for enzyme function discovery.
• To discuss the implications of the 'unknown enzyme problem'.

Main Methods:

• Utilized Swiss-Prot, BRENDA, and KEGG databases.
• Employed a Hidden Markov Model-based computational approach.
• Reviewed existing experimental and computational discovery strategies.

Main Results:

• Estimated over 600 yeast and 2000 human proteins are enzymes with undetermined functions.
• This represents over 30% of proteins with unknown functions.
• Highlighted the 'unknown enzyme problem' scale.

Conclusions:

• A significant number of enzymes in yeast and humans have unknown functions.
• Various approaches exist to aid enzyme function discovery.
• Understanding these enzymes is vital for metabolic modeling, engineering, and rare disease research.