  Current protein language models (pLMs) predominantly focus on single-chain
protein sequences and often have not accounted for constraints on generative
design imposed by protein-protein interactions. To address this gap, we present
paired Antibody T5 (pAbT5), an encoder-decoder model to generate complementary
heavy or light chain from its pairing partner. We show that our model respects
conservation in framework regions and variability in hypervariable domains,
demonstrated by agreement with sequence alignment and variable-length CDR
loops. We also show that our model captures chain pairing preferences through
the recovery of ground-truth chain type and gene families. Our results showcase
the potential of pAbT5 in generative antibody design, incorporating biological
constraints from chain pairing preferences.
