A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding
Rahmad Akbar(University of Oslo), Philippe A. Robert(University of Oslo), Milena Pavlović(University of Oslo), Jeliazko R. Jeliazkov(University of Zurich), Igor Snapkov(University of Oslo), Andrei Slabodkin(University of Oslo), Cédric R. Weber(ETH Zurich), Lonneke Scheffer(University of Oslo), Enkelejda Miho(FHNW University of Applied Sciences and Arts Northwestern Switzerland), Ingrid Hobæk Haff(University of Oslo), Dag Trygve Tryslew Haug(Integrated Detector Electronics AS (Norway)), Fridtjof Lund‐Johansen(University of Oslo), Yana Safonova(University of California San Diego), Geir Kjetil Sandve(University of Oslo), Victor Greiff(University of Oslo)
Cited by 187Open Access
Abstract
motifs; (2) distinct from non-immune protein-protein interactions; and (3) mediates specific oligo- and polyreactive interactions between paratope-epitope pairs. Our work leverages combined structure- and sequence-based learning to demonstrate that machine-learning-driven predictive paratope and epitope engineering is feasible.
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