Single-residue linear and conformational B cell epitopes prediction using random and ESM-2 based projections.

ABSTRACT: B cell epitope prediction methods are separated into linear sequence-based predictors and conformational epitope predictions that typically use the measured or predicted protein structure. Most linear predictions rely on the translation of the sequence to biologically based representations and the applications of machine learning on these representations. We here present CALIBER 'Conformational And LInear B cell Epitopes pRediction', and show that a bidirectional long short-term memory with random projection produces a more accurate prediction (test set AUC=0.789) than all current linear methods. The same predictor when combined with an Evolutionary Scale Modeling-2 projection also improves on the state of the art in conformational epitopes (AUC = 0.776). The inclusion of the graph of the

SUBMITTER: Israeli S 

PROVIDER: S-EPMC10940830 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature