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AbDiffuser: Full-Atom Generation of in vitro Functioning Antibodies

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arxiv 2308.05027 v2 pith:KRR6YBID submitted 2023-07-28 q-bio.BM cs.LGstat.ML

classification q-bio.BMcs.LGstat.ML
keywords abdiffuserantibodiesdiffusiongenerationexperimentsproteinvitrowere
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We introduce AbDiffuser, an equivariant and physics-informed diffusion model for the joint generation of antibody 3D structures and sequences. AbDiffuser is built on top of a new representation of protein structure, relies on a novel architecture for aligned proteins, and utilizes strong diffusion priors to improve the denoising process. Our approach improves protein diffusion by taking advantage of domain knowledge and physics-based constraints; handles sequence-length changes; and reduces memory complexity by an order of magnitude, enabling backbone and side chain generation. We validate AbDiffuser in silico and in vitro. Numerical experiments showcase the ability of AbDiffuser to generate antibodies that closely track the sequence and structural properties of a reference set. Laboratory experiments confirm that all 16 HER2 antibodies discovered were expressed at high levels and that 57.1% of the selected designs were tight binders.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension

    q-bio.BM 2024-11 conditional novelty 6.0 of 10

    PepHAR generates peptide binders by first sampling hot-spot residues from a learned energy model, then autoregressively extending fragments via dihedral angles, then refining the full structure.

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