[Research progress on B-cell epitope prediction methods]

Area of Science:

• Immunology
• Bioinformatics
• Computational Biology

Background:

• B-cell epitopes are crucial for adaptive immunity, recognized by B-cell receptors and antibodies.
• Accurate identification of B-cell epitopes accelerates the development of therapeutic antibodies and vaccines.
• Predicting epitopes computationally is essential for efficient drug discovery.

Purpose of the Study:

• To systematically review recent computational methods for predicting B-cell conformational and linear epitopes.
• To provide a comprehensive overview of prediction tools, including their architectures, performance, and applications.
• To serve as a reference for researchers in immunology, bioinformatics, and drug development.

Main Methods:

• Systematic literature review of B-cell epitope prediction methods.
• Analysis of representative tools for conformational epitopes (e.g., SEPPA 3.0, DiscoTope-3.0, BepiPred-3.0).
• Analysis of representative tools for linear epitopes (e.g., DLBEpitope, EpiDope, EpitopeVec).

Main Results:

• Detailed introduction to various epitope prediction methods.
• Comparison of prediction performance, model architectures, and application scopes.
• Illustrative examples demonstrating the utility of the reviewed methods.

Conclusions:

• The reviewed methods offer valuable insights into B-cell epitope prediction.
• This systematic review provides essential reference information for researchers.
• Advancements in epitope prediction accelerate the design of novel therapeutics and vaccines.