Paraplume Predicts Antibody Paratopes At Scale
Researchers Athènes, Woolfe, Mora, and Walczak publish Feb. 18, 2026 in PLoS Computational Biology a sequence-based paratope predictor, Paraplume, that uses protein language model embeddings to identify antibody binding residues without structural input. Paraplume outperforms existing methods on multiple benchmarks, is available as a PyPI package and GitHub repository, and shows antigen-driven somatic hypermutation correlates with increased paratope size across repertoires.
Scoring Rationale
High methodological novelty and peer-reviewed validation; impact focused on antibody paratope prediction rather than broad AI infrastructure.
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