Protein–protein interactions (PPIs) are involved in nearly all biological processes. Understanding and analysis of PPI is key to revealing biological networks and identifying new therapeutic targets. Various computational approaches have been proposed as an alternative to the experimental investigation of PPIs. More recently, with the advent of Large Language Models (LLMs), a plethora of approaches using LLMs have been developed, enabling efficient analysis of interaction networks and binding sites directly from protein sequences. These models capture intricate biological patterns, offering scalability and adaptability across diverse datasets. However, challenges remain, including computational costs, data imbalance, and the integration of multimodal information. Advancements in addressing these limitations are set to further enhance the potential of LLMs in protein–protein interaction analysis, driving deeper insights and broader applications in biological research.