FuzPred

FuzPred predicts context-dependent protein binding modes from amino acid sequence to determine whether interactions produce ordered (disorder-to-order) or disordered (disorder-to-disorder) assemblies.

Key Features:

• Sequence-Based Prediction: Uses amino acid sequence information to forecast protein binding modes and distinguish disorder-to-order versus disorder-to-disorder transitions.
• Context-Dependent Binding Modes: Estimates the multiplicity of possible binding modes for each protein region, identifying regions likely to adopt multiple conformations.
• Visualization on Protein Structures: Maps prediction results onto AlphaFold-generated protein structures to localize different interaction behaviors on 3D models.

Scientific Applications:

• Understanding Protein Functionality: Provides insights into how proteins transition between states upon interaction to inform studies of protein function and regulation.
• Identifying Regulatory Sites: Highlights regions with high multiplicity of binding modes that may serve as regulatory sites or interaction hot-spots.
• Structural Biology Research: Supports mapping of predicted interaction behaviors onto structures to aid studies of protein dynamics and assembly processes.

Methodology:

Predicts binding modes directly from sequence without requiring predefined binding partners, estimates the multiplicity of binding modes for protein regions, distinguishes disorder-to-order and disorder-to-disorder transitions, and maps predictions onto AlphaFold-generated structures.