Neoantigen × AI
Daily research signal
35Brief

AlphaFold3 improves but struggles with antibody-peptide complexes

A new benchmark reveals that while AlphaFold3 and enhanced sampling protocols improve the modeling of antibody and TCR antigen recognition compared to AlphaFold2, accuracy remains inconsistent across interface classes.bioRxiv

The study highlights significant challenges in predicting antibody-peptide complexes and suggests that model pooling strategies may be necessary to achieve reliable predictive performance for neoantigen vaccine design.bioRxiv

1new story
AI / Methods3 days agoNew

Benchmarking AlphaFold and related deep learning approaches for modeling antibody and TCR antigen recognition

Researchers benchmarked AlphaFold2, AlphaFold3, and related deep learning methods for modeling antibody-protein, antibody-peptide, and TCR-pMHC recognition. Results indicate that increased sampling and AlphaFold3 generally outperform default AlphaFold2 settings, though predictive accuracy varies significantly by interface class. The authors note that antibody-peptide complexes remain particularly difficult to model accurately and propose model pooling as a potential solution to leverage method complementarity.

biorxiv · 3 days ago · Yin, R.; Saravanakumar, S.; Shi, S. Y.; Park, M.; Lin, V.; Lee, J.; Cheung, M.; Felbinger,