ReUPRed

ReUPred predicts and classifies tandem repeat (TR) units in protein structures by performing iterative structural searches against a Structure Repeat Unit Library (SRUL) derived from RepeatsDB to identify and categorize repeat units.

Key Features:

• Automatic Prediction: Provides fast automatic identification and categorization of tandem repeat units in protein structures.
• Iterative Structural Search: Employs an iterative structural search mechanism against the SRUL to enhance detection of repetitive units within protein structures.
• High Accuracy: On a test set of solenoid proteins, correctly identifies 92% of repeat-containing proteins and classifies solenoid repeats with 89% accuracy.
• Superior Performance: Outperforms existing state-of-the-art methods for the identification of repeat units.
• Extensive Annotation: Increases the number of annotated repeat units by an order of magnitude compared to sequence-based classifications such as Pfam.
• Implementation: Implemented in Python and compatible with Linux.

Scientific Applications:

• Structural characterization of TR proteins: Enables identification and classification of repeat units to support structural biology investigations of tandem repeat proteins.
• Annotation expansion and comparative analysis: Facilitates expansion of repeat annotations beyond sequence-based resources (e.g., Pfam) for comparative and evolutionary analyses.
• Structure–function and disease studies: Supports studies of structure–function relationships of TR proteins implicated in biological functions and diseases.

Methodology:

Performs an iterative structural search against a curated Structure Repeat Unit Library (SRUL) derived from RepeatsDB to identify and classify structural repeat units.