RONN

RONN predicts natively disordered regions in protein sequences to identify segments that lack stable tertiary structure and can influence protein function and experimental outcomes.

Key Features:

• Bio-Basis Function Neural Network Algorithm: Implements a bio-basis function neural network pattern-recognition algorithm to detect disordered regions from primary sequence information.
• Blind-Testing Performance: In blind tests against nine disorder prediction tools using 80 Protein Data Bank (PDB) sequences, RONN achieved the highest scores according to the probability excess measure.

Scientific Applications:

• Understanding Protein Function: Identification of disordered regions informs analyses of protein-protein interactions and regulatory functions.
• Facilitating Structural Analysis: Prediction of disordered segments aids experimental design by indicating regions that affect solubility and crystallization.

Methodology:

Employs a neural network-based approach using a bio-basis function neural network and pattern-recognition methods to analyze protein sequences and distinguish ordered from natively disordered segments.