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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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BepiPred-3.0: Improved B-cell epitope prediction using protein language models.

Joakim Nøddeskov Clifford¹, Magnus Haraldson Høie¹, Sebastian Deleuran¹

¹Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark.

Protein Science : a Publication of the Protein Society

|November 11, 2022

Summary

BepiPred-3.0 leverages advanced protein language models to significantly enhance B-cell epitope prediction accuracy for vaccine development and diagnostics. This new tool offers rapid, precise identification of epitopes from amino acid sequences alone.

Keywords:

B-cell epitope prediction B-cell epitopes BepiPred BepiPred-3.0 bioinformatics deep learning immunoinformatics immunology machine learning protein language model

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A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes

Published on: March 25, 2014

Area of Science:

Computational biology
Immunoinformatics

Background:

B-cell epitope prediction is crucial for vaccine design and diagnostics.
Protein language models (LMs) offer powerful sequence-based representations.

Purpose of the Study:

To develop an improved B-cell epitope prediction tool using LM embeddings.
To enhance prediction accuracy for both linear and conformational epitopes.

Main Methods:

Utilized LM embeddings for sequence-based epitope prediction.
Incorporated additional input variables and refined residue annotation strategies.
Developed BepiPred-3.0 as a web server and standalone package.

Main Results:

Achieved significantly improved prediction accuracy on multiple test sets.
Demonstrated unprecedented predictive power for B-cell epitopes.
Enabled rapid prediction across hundreds of sequences.

Conclusions:

BepiPred-3.0 represents a substantial advancement in sequence-based B-cell epitope prediction.
The tool's performance and speed facilitate practical applications in research and development.
Freely available web server and package promote accessibility and adoption.