Protein-Protein Interaction Prediction

The field predicts whether proteins interact, where they bind, and how their interfaces or docking poses are arranged—useful for understanding cell biology and guiding therapeutic design. Methods range from sequence language models and multimodal embeddings to geometric or equivariant graph networks, knowledge graphs, and docking-based pose scoring. Evaluation spans interaction classification, residue-level site prediction, and pose ranking, with protein-disjoint and cold-start tests used to probe generalization beyond familiar proteins. A central challenge is separating biological signal from dataset shortcuts while extending static predictions to flexible, dynamic binding processes.