ProtFun

ProtFun predicts the cellular role, enzyme class, and Gene Ontology (GO) category of proteins from amino acid sequences by analyzing sequence-derived functional attributes.

Key Features:

• Sequence-Based Methodology: Predicts protein function solely from amino acid sequences without relying on three-dimensional structural data.
• Functional Attribute Integration: Integrates sequence-derived attributes including post-translational modifications (PTMs), protein sorting signals, and polypeptide chain characteristics such as length, isoelectric point, and amino acid composition.
• Enzyme Class Prediction: Categorizes enzymes by correlating sequence-derived features with enzymatic function to assign enzyme classes.

Scientific Applications:

• Functional Genomics: Facilitates annotation and classification of newly discovered or poorly characterized proteins based on sequence information.
• Enzymology: Provides sequence-based assignments of enzyme classes to support studies of enzymatic roles and classification.
• Systems Biology: Contributes functional role assignments that can be integrated into protein network and pathway analyses.

Methodology:

Applies an entirely sequence-based approach that identifies and integrates sequence-derived functional attributes (PTMs, protein sorting signals, polypeptide chain characteristics) to predict cellular roles, enzyme classes, and Gene Ontology categories from amino acid sequences.