PFP

PFP predicts Gene Ontology (GO) annotations for protein sequences by combining sequence similarity and GO-term contextual associations to infer protein function.

Key Features:

• Automated GO Annotation: Predicts Gene Ontology (GO) annotations using sequence similarity together with contextual relationships between GO terms.
• Protein Function Prediction (PFP) method: Extends beyond conventional database search methods such as BLAST by leveraging information from distantly related sequences and GO-term context.
• Extended Similarity Group (ESG) Algorithm: Incorporates an ESG algorithm that iteratively searches sequence databases to refine functional predictions through extended similarity relationships.
• Visualization of Predictions: Represents predicted GO terms within a hierarchical topology to illustrate functional relationships among annotations.

Scientific Applications:

• Protein Function Discovery: Infers functions for uncharacterized or novel proteins by assigning GO annotations when direct database matches are lacking.
• Research and Development: Provides functional annotation useful for applications such as drug discovery, genetic engineering, and systems biology.

Methodology:

The method leverages the PFP approach to use distantly related sequences and GO-term contextual associations and integrates the ESG algorithm to iteratively search sequence databases and refine annotations beyond BLAST-based similarity searches.