FunFOLD2

FunFOLD2 predicts protein function from sequence by identifying ligand-binding sites and assessing structural model quality through tertiary-structure-based analysis.

Key Features:

• Integrated protocols: Predicts protein-ligand binding sites and evaluates prediction quality using structure-based analyses.
• Tertiary-structure prediction: Generates predicted 3D models from sequence to support functional and binding-site inference.
• Annotated structural output: Produces annotated images of top predicted tertiary structures highlighting putative ligand-binding residues.
• Residue and ligand predictions: Reports likely binding-site residues and predicted ligand types with frequencies derived from similar structures.
• Machine-readable data: Exports raw, machine-readable results that adhere to Critical Assessment of Techniques for Protein Structure Prediction (CASP) standards for function prediction.

Scientific Applications:

• Drug discovery: Identifies potential small-molecule binding sites on protein targets to inform target selection and ligand design.
• Protein engineering: Guides design of proteins with altered or improved functions by identifying structurally informed functional residues.
• Functional genomics: Assists annotation of protein functions in newly sequenced genomes by predicting structural features and binding sites.

Methodology:

Uses sequence data to predict tertiary structures and to identify potential ligand-binding sites, integrating structural modeling with functional annotation and applying protocols for binding-site prediction and quality assessment; outputs include machine-readable data conforming to CASP function-prediction standards.