DbStRiPs

DbStRiPs catalogs and annotates tandem structural repeats in protein structures to enable classification and functional interpretation of repeat proteins.

Key Features:

• Structural Repeat Identification: Employs a network-based pipeline combined with manual curation and Kajava's structure-based classification schema to identify and classify tandem structural repeats in protein structures.
• Integration of Sequence and Structure-Based Classifications: Maps the Pfam classification scheme onto structural classifications to integrate sequence repeat family knowledge with structural subclasses.
• Comprehensive Annotations: Provides repeat start and end boundaries, copy number, secondary and tertiary structure views, repeat class/subclass, disease associations, multiple sequence alignments (MSA) of repeating units, and cross-references to protein pattern databases, the Human Protein Atlas, and interaction resources.
• Novel Discoveries: Analysis of the complete Protein Data Bank yielded 16,472 repeat annotations across 15,141 protein chains, including a novel repeat family named "left-handed beta helix" and 33 protein repeat clusters (PRCs).
• Classification Efficiency: Approximately 79% of identified repeat proteins are classified into one of 14 established Protein Repeat Families (PRFs) or among the 33 PRCs, with the remainder unclassified.

Scientific Applications:

• Structure–Function Analysis: Supports analysis of protein structure–function relationships by providing structural repeat annotations and views.
• Evolutionary Biology: Enables investigation of evolutionary conservation and variation among repeating units across protein families.
• Disease Mechanism Investigation: Facilitates study of molecular bases of diseases linked to repeat proteins via disease association annotations.
• Function Prediction Refinement: Enhances protein function prediction by combining structural subclassification with Pfam sequence-family mappings.

Methodology:

Uses a network-based pipeline with manual curation, applies Kajava's structure-based classification schema, maps the Pfam classification scheme onto structural classifications, and was applied to the complete Protein Data Bank.