Systeme und Verfahren zur Vorhersage Immunogener Epitope aus Antigenproteinsequenzen

Details

Veröffentlichungs-Nr.

EP4814971

Anmeldetag

9. März 2026

Veröffentlichung

30. September 2026

Rechtsraum

EP

IPC

G16B20/30, G16B40/20

Abstract

Epitopes identification is a very important problem and has implications in designing vaccines for emerging viruses, bacteria and fight antimicrobial resistance. Traditional methods of epitope mapping are costly, and time consuming. Present disclosure provides a system and a method that processes structural features along with the features from protein language models and apply deep concatenation techniques to combine the features for obtaining a concatenated feature set. A weight for each feature amongst the concatenated features set and a bias for the concatenated features set are learnt to obtain an optimal combination of features set based on which amino acid residues are predicted as one of an epitope or a non-epitope. Further, epitopes are prioritized using a plurality of attention scores capturing a T-B association by using a protein language model, to obtain a set of immunogenic B-cell epitopes.

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien

Fachgebiete