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Arc Institute announces Germinal, a generative AI system for de novo antibody design published in Nature Biotechnology. It designs epitope-targeted antibodies with nanomolar affinity testing only tens of designs per target, making custom antibody design more accessible.
Nabla Bio unveils JAM-2, a model for zero-shot drug design achieving atomic-precision, computationally designed multispecific antibodies and dual-variant KRAS multispecifics with high potency and selectivity, validated with Cryo-EM and wet-lab experiments.
This paper identifies three failure modes in existing antibody design methods (antigen blindness, vocabulary collapse, convergence to marginal distribution) and proposes AgForce, a novel encoder-decoder architecture using graph neural networks and mixture density networks, achieving state-of-the-art binding quality and sequence recovery on the Chimera-Bench benchmark.
ConTact introduces a contact-then-act architecture for antibody CDR design that explicitly decomposes the task into interface reasoning, contact prediction, and contact-gated sequence generation, achieving state-of-the-art structural quality and epitope awareness on the Chimera-Bench benchmark.
This paper introduces a discrete diffusion model with a novel 'germline absorbing' modification to improve conditional antibody sequence generation. It addresses germline bias in protein language models and demonstrates superior performance in optimizing antibody binding affinity and developability compared to existing methods like EvoProtGrad.