Boltz2 co-folding representations match or exceed existing models on ADMET benchmarks, accelerate generative modeling, and improve sample efficiency in ligand optimization while being complementary to 3D, bioassay, and quantum-chemical supervision.
In this experiment, we use the official codebase of GruM
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A Systematic Evaluation of Co-folding Model Representations for Small-Molecule Learning
Boltz2 co-folding representations match or exceed existing models on ADMET benchmarks, accelerate generative modeling, and improve sample efficiency in ligand optimization while being complementary to 3D, bioassay, and quantum-chemical supervision.