PEASE

PEASE predicts antibody-specific epitopes by integrating antibody sequence into a predictive model to identify epitope residues and surface patches on antigen 3D structures.

Key Features:

• Antibody-sequence integration: Incorporates the sequence of the antibody into the predictive model rather than relying solely on antigen sequence or structure.
• Antibody-specific epitope prediction: Produces predictions that are specific to the input antibody, enabling differentiation between epitopes targeted by different antibodies.
• Residue-level predictions: Reports epitope predictions at the individual residue level on the antigen.
• Surface-patch (3D) predictions: Aggregates residue predictions into patches mapped onto the antigen's 3D structure to indicate potential binding sites.
• Adjustable recall–precision trade-off: Allows tuning of prediction parameters to balance recall and precision according to analysis requirements.

Scientific Applications:

• Drug development: Identifies antibody-specific binding sites on antigens to inform therapeutic antibody design and optimization.
• Diagnostics: Maps epitopes targeted by antibodies to support development and interpretation of antibody-based diagnostic assays.
• Vaccine design: Highlights antigen regions bound by specific antibodies to guide immunogen selection and epitope-focused vaccine strategies.
• Antibody–antigen recognition studies: Enables comparative analysis of how different antibodies recognize the same antigen at residue and surface-patch levels.

Methodology:

Integrates antibody sequence into a predictive model to generate residue-level and antigen surface-patch epitope predictions mapped onto antigen 3D structures, with adjustable parameters to trade recall and precision.