2026-04-11
Protenix-v2: Broadening the Reach of Structure Prediction and Biomolecular Design
ABSTRACT
Advances in biomolecular modeling have broadened the range of problems addressable by structure prediction and design models. Here, we present results from Protenix-v2, a system spanning high-accuracy structure prediction and biomolecular design. On the structure prediction side, Protenix-v2 achieves antibody-antigen success rates with up to 13-point gains over Protenix-v1, while 5-seed performance surpasses previous 1000-seed results. On the design side, Protenix-v2 demonstrates a 100% target-level success rate in novelty-controlled VHH-Fc campaigns, reaching hit rates up to 48%. Crucially, the model enables hit discovery on difficult GPCR targets with hit rates of 16%–88% (VHH-Fc) and up to 50% (mAb) under 16–30 testing budgets per target. Resulting hits show high developability and diversity. Beyond antibody tasks, we report improved ligand-related plausibility and successful cross-variant SARS-CoV-2 spike RBD mini-binder design. These results establish Protenix-v2 as a robust and powerful model for accelerated drug discovery.
AUTHORS
Yuxuan Zhang, Chengyue Gong, Jinyuan Sun, Jiaqi Guan, Milong Ren, Song Xue, Hanyu Zhang, Wenzhi Ma, Zhenyu Liu, Xinshi Chen, Wenzhi Xiao
VENUE
bioRxiv
