CUPP

CUPP performs peptide-pattern-based clustering to annotate and subgroup carbohydrate-active enzymes (CAZymes) for functional classification.

Key Features:

• Peptide-based similarity assessment: Uses a peptide-based similarity algorithm to detect conserved unique peptide patterns and cluster proteins.
• Unsupervised grouping: Produces unsupervised groups of proteins based on conserved unique peptide patterns.
• CAZyme classification: Assigns proteins to CAZy families and subfamilies for functional classification.
• EC number assignment: Assigns Enzyme Commission (EC) numbers to denote specific enzymatic functions.
• Input types and sizes: Accepts genomic DNA (up to 30MB compressed) and amino acid sequences (up to 10MB compressed) as query inputs.
• Cross-domain applicability: Applicable to genomic studies of both prokaryotic and eukaryotic organisms.
• Experimental evidence mapping: Provides information linking group members to experimentally characterized enzymes.

Scientific Applications:

• CAZyme annotation and subfamily classification: Classifying carbohydrate-active enzymes into CAZy families and subfamilies.
• Enzymatic function prediction: Predicting enzymatic activities by assigning Enzyme Commission (EC) numbers.
• Comparative genomics of CAZymes: Analyzing CAZyme repertoires across prokaryotic and eukaryotic genomes.
• Selection of experimental candidates: Identifying group members and experimentally characterized homologs to support experimental validation of predicted functions.

Methodology:

Uses a peptide-based similarity assessment algorithm to identify conserved unique peptide patterns and cluster proteins into unsupervised groups for CAZy family/subfamily classification and EC number assignment.