Highlights
Key features of our prediction model.
Integrates residue-level ESM-2 embeddings with interpretable biochemical descriptors.
Cross-attention + Transformer aligns property cues to salient sequence positions.
Returns calibrated probabilities with ACC, Sn, Sp, MCC, and AUC.
Benchmark-validated on ACP135 and ACP99 with consistent gains over strong baselines.
Supports saliency visualizations for mechanism-aware interpretation.
Efficient, GPU-ready inference for large-scale peptide screening.