Site-Aware Receptor-Sequence-Conditioned Peptide Binder Generation

Sequence-based peptide binder generation enables efficient design from readily  available receptor sequences. However, binding alone is insufficient for functional  peptides, whose biological activity often depends on engaging specific receptor  regions. Existing sequence-based methods either offer no direct control over which  receptor site is engaged or require the target region to be specified in advance,  limiting their use when the functionally relevant region is unknown. To address  this gap, we introduce **SitePepGen**, a **Site**-aware, receptor-sequence-conditioned  masked language model for **Pep**tide **Gen**eration that requires neither receptor  structures nor predefined functional binding sites. SitePepGen combines two  components: (1) a residue-level receptor binding-site prediction head, jointly  trained with peptide generation using shared ESM-2 representations to identify  putative peptide-binding regions; and (2) a site-aware candidate selection module  that ranks generated peptides by their physicochemical compatibility score with the  predicted receptor sites and the model’s generation confidence. In the evaluation  of receptor binding-site recovery using predicted receptor–peptide complexes,  SitePepGen improves macro-averaged Jaccard and F1 over the strongest baseline  by 3.62 and 3.56 percentage points, respectively, while maintaining comparable  sequence-plausibility diagnostics. For receptor binding-site prediction, SitePepGen  further improves AUROC and AUPRC over the strongest baseline by 0.95 and  1.69 percentage points, respectively. The code will be released at https\://  anonymous.4open.science/r/SitePepGen/.