3M-SARS-CoV-2

3M-SARS-CoV-2 predicts potentially immunopathogenic, cross-reactive B- and T-cell epitopes of SARS-CoV-2 to identify molecular mimicry between viral and human proteins.

Key Features:

• Identification of Cross-Reactive Epitopes: Uses a hidden Markov model-based approach to detect distant viral homologs of human proteins that may yield cross-reactive epitopes.
• Structural Analysis: Leverages experimentally determined and modeled protein structures of SARS-CoV-2 and human proteins to identify homologous structural regions implicated in cross-reactivity.
• Binding Affinity Prediction: Predicts binding affinity (IC50) of candidate T-cell epitopes to 34 MHC allelic variants associated with autoimmune diseases using multiple prediction algorithms.
• Comprehensive Epitope Dataset: From analysis of 8,138 SARS-CoV-2 genomes, reports 3,238 potentially cross-reactive B-cell epitopes (associated with six human proteins) and 1,224 T-cell epitopes (associated with 285 human proteins).

Scientific Applications:

• Autoimmune Disease Research: Investigates the potential role of molecular mimicry in autoimmune disease pathogenesis following SARS-CoV-2 infection.
• Vaccine Antigen Evaluation: Informs selection and design of vaccine antigens by identifying epitopes that may contribute to cross-reactive or suboptimal immune responses, including in individuals with genetic predispositions to autoimmunity.

Methodology:

Sequence similarity search complemented by structural analysis to identify cross-reactive epitopes, with binding affinity (IC50) predictions to 34 MHC allelic variants performed using multiple algorithms.