Identifying pseudoenzymes using functional annotation: pitfalls of common practice.

Area of Science:

• Biochemistry and Molecular Biology
• Evolutionary Biology
• Bioinformatics

Background:

• Pseudoenzymes are proteins evolutionarily related to enzymes but have lost catalytic activity.
• The evolutionary pathways leading to loss of catalytic function are not well understood, with pseudokinases being a notable exception.
• Existing literature often assumes pseudoenzymes are ubiquitous and mutations in catalytic sites signify loss of function.

Purpose of the Study:

• To analyze the current knowledge of pseudoenzymes across diverse enzyme families using biological database information.
• To investigate the prevalence of pseudoenzymes and the correlation between loss of catalytic function and catalytic residue mutations.
• To challenge prevailing assumptions about pseudoenzyme ubiquity and the interpretation of catalytic residue mutations.

Main Methods:

• Utilized UniProtKB for functional annotations of proteins.
• Employed the Mechanism and Catalytic Site Atlas (M-CSA) to gather information on enzyme catalytic residues.
• Developed and applied a protocol to identify pseudoenzymes based on catalytic site information, correcting for incomplete annotations.

Main Results:

• Found that explicit 'lack of activity' annotations in UniProtKB are not exhaustive, necessitating alternative identification methods.
• Identified pseudoenzymes within M-CSA and assessed their prevalence across various enzyme families.
• Observed that mutations in catalytic residues do not always correlate with a definitive lack of catalytic activity.

Conclusions:

• Pseudoenzymes are not as ubiquitous across all enzyme families as commonly suggested.
• Mutations in catalytic residues of enzyme homologues are not a foolproof indicator of lost catalytic function.
• Database analysis provides valuable insights into pseudoenzyme characteristics, complementing traditional literature reviews.