SurfBind applies a Transformer with patch-level surface modeling and binder-aware cross-attention to 3D molecular surfaces, reporting state-of-the-art epitope prediction on SAbDab and DB5.5 with generalization to unseen antibodies.
Predicting mutational effects on protein binding from folding energy
2 Pith papers cite this work. Polarity classification is still indexing.
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D-Flow applies multi-modality flow matching and a mirror-image data augmentation to generate D-peptides with 10.2% higher sequence identity and 24.31% top affinity on the PepMerge benchmark.
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Deciphering Fingerprints of 3D Molecular Surfaces for Accurate Epitope Prediction
SurfBind applies a Transformer with patch-level surface modeling and binder-aware cross-attention to 3D molecular surfaces, reporting state-of-the-art epitope prediction on SAbDab and DB5.5 with generalization to unseen antibodies.
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D-Flow: Multi-modality Flow Matching for D-peptide Design
D-Flow applies multi-modality flow matching and a mirror-image data augmentation to generate D-peptides with 10.2% higher sequence identity and 24.31% top affinity on the PepMerge benchmark.