BoRam Lee

Boltz-Perturb: Improving Diversity and Accuracy in Protein-Ligand Co-Folding through Training-Free Conditioning Perturbation

Boltz-Perturb is presented, a framework for addressing small molecule binding poses through perturbing model conditioning signals during model inference, and it is demonstrated that inference-time perturbations can unlock latent structural diversity in generative co-folding models and improve protein-ligand predictions without costly retraining.