SEMA 2.0: web-platform for B-cell conformational epitopes prediction using artificial intelligence

Nikita V Ivanisenko; Tatiana I Shashkova; Andrey Shevtsov; Maria Sindeeva; Dmitriy Umerenkov; Olga Kardymon

doi:10.1093/nar/gkae386

SEMA 2.0: web-platform for B-cell conformational epitopes prediction using artificial intelligence

Nucleic Acids Res. 2024 May 14:gkae386. doi: 10.1093/nar/gkae386. Online ahead of print.

Authors

Nikita V Ivanisenko^{1

2}, Tatiana I Shashkova¹, Andrey Shevtsov^{1

3}, Maria Sindeeva¹, Dmitriy Umerenkov¹, Olga Kardymon¹

Affiliations

¹ Bioinformatics Group, AIRI, Moscow, Russia.
² Laboratory of Computational Proteomics, Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia.
³ Regulatory Transcriptomics and Epigenomics Group, Research Center of Biotechnology RAS, Moscow, Russia.

PMID: 38742639
DOI: 10.1093/nar/gkae386

Abstract

Prediction of conformational B-cell epitopes is a crucial task in vaccine design and development. In this work, we have developed SEMA 2.0, a user-friendly web platform that enables the research community to tackle the B-cell epitopes prediction problem using state-of-the-art protein language models. SEMA 2.0 offers comprehensive research tools for sequence- and structure-based conformational B-cell epitopes prediction, accurate identification of N-glycosylation sites, and a distinctive module for comparing the structures of antigen B-cell epitopes enhancing our ability to analyze and understand its immunogenic properties. SEMA 2.0 website https://sema.airi.net is free and open to all users and there is no login requirement. Source code is available at https://github.com/AIRI-Institute/SEMAi.