[Application of AlphaFold3 in screening nanobodies against Staphylococcus aureus enterotoxin C]

Objective: To evaluate the consistency between AlphaFold3 (AF3) predictions for epitope grouping of nanobodies (Nbs)-antigen complexes and experimental validation, and provide reference for structure-prediction-assisted efficient in vitro screening of Nbs. Methods: Staphylococcus aureus enterotoxin C (SEC) was used as the target antigen, specific Nbs were screened from a naive phage-displayed nanobodies library, and their specificity was verified by indirect ELISA and Western blot. Approximately 5 000 models were generated for each SEC-Nbs complex by using AF3, and the model with the highest ranking score was selected as the optimal model for epitope analysis. Results: After six rounds of solid-phase panning, six Nbs with distinct sequences were obtained, all of which achieved soluble expression. Indirect ELISA confirmed that all Nbs specifically bound to SEC. The optimal models for SEC-Nb1 to SEC-Nb6 had ranking scores of 0.932 4, 0.903 5, 0.837 5, 0.361 5, 0.932 1, and 0.678 3, respectively, dividing the Nbs into two epitope groups (Nb1-Nb2, Nb3-Nb6). Sandwich ELISA divided the Nbs into four epitope groups (Nb1-Nb3, Nb4, Nb5, Nb6), showing a 50% consistency with AF3 predictions. Conclusion: AF3 could serve as a valuable tool to facilitate epitope grouping-based in vitro screening of Nbs.