From protein corona characterization to computational and AI-enabled approaches: Mapping the evolution of nano–bio interface research

Protein corona formation critically shapes nano-bio interactions by influencing nanoparticle biological identity, cellular uptake, biodistribution, toxicity, and performance in nanomedicine. To characterize the evolution of protein corona research and the emergence of computational approaches, we conducted a comparative bibliometric analysis of records retrieved on July 25, 2026, using the Web of Science Core Collection as the primary database and Scopus and PubMed for external validation. Two complementary corpora were constructed: a general protein corona corpus comprising 1212 documents published between 2000 and 2025 and an AI-enabled computational protein corona corpus comprising 310 documents published between 2011 and 2025. Bibliometric analyses included global collaboration, publication sources, keyword co-occurrence, thematic evolution, co-citation, bibliographic coupling, citation bursts, and cross-database consistency. The general corpus showed that protein corona research has evolved from physicochemical characterization and protein adsorption toward biological identity, nanomedicine, drug delivery, and functional interpretation. The computational corpus retained the central concepts, publication sources, and citation foundations of the established field, while machine learning, molecular dynamics, and artificial intelligence emerged as prominent methodological themes. These patterns indicate that computational development combines data-driven prediction with mechanistic simulation rather than forming an isolated AI subfield. Scopus and PubMed validation reproduced the major thematic direction identified in Web of Science, although individual frequencies and network indicators differed across databases. Overall, protein corona research exhibits a two-layer structure consisting of an established biomedical nano-bio interface field and an emerging AI-enabled computational extension, reflecting a gradual transition from descriptive characterization toward computationally assisted and prediction-oriented investigation.