eLife assessment
This study presents a useful deep learning-based inter-protein contact prediction method named PLMGraph-Inter which combines protein language models and geometric graphs. The evidence supporting the claims of the authors is solid, although it could have information leakage between training and test sets, and although more emphasis should be given to predictions starting from unbound monomer structures. The authors show that their approach may be useful in some cases where AlphaFold-Multimer performs poorly. This work will be of interest to researchers working on protein complex structure prediction, particularly when accurate experimental structures are available for one or both of the monomers in isolation.