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arxiv: 2308.05027 · v2 · pith:KRR6YBIDnew · submitted 2023-07-28 · 🧬 q-bio.BM · cs.LG· stat.ML

AbDiffuser: Full-Atom Generation of in vitro Functioning Antibodies

classification 🧬 q-bio.BM cs.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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Cited by 1 Pith paper

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  1. ADIOS: Antibody Development via Opponent Shaping

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    ADIOS applies opponent shaping in a meta-learning setup to create antibodies that target current and future viral variants while biasing evolution toward weaker strains, demonstrated in Absolut! simulations.