The growing field of protein corona research

When a nanoparticle enters a biological fluid, proteins attach to its surface and form a corona, which can influence how the particle is recognized by cells and how it behaves in the body.

The field of protein corona study has blossomed in the past two decades, so Hao et al. conducted bibliometric analyses to understand the evolution of the field.

The researchers analyzed two related bodies of literature: a general protein corona corpus comprising 1,212 publications from 2000 to 2025 and an AI-enabled computational corpus comprising 310 publications from 2011 to 2025.

“We wanted to compare the established protein corona field with the newer literature involving simulation, machine learning, and artificial intelligence,” said author Hongdong Hao. “If all publications were examined as a single group, this smaller and younger area could easily be hidden by the much larger traditional literature.”

For students and researchers entering the field, there can be a disconnect between traditional and computational research of protein coronas.

The bibliometric analyses of the two batches of publications revealed that computational protein corona research is still aligned with the established protein corona field, often appearing in the same journals and referencing the same foundational research.

The traditional research has evolved from characterization to nanomedicine, drug delivery, and functional interpretation, while computational research points to new methodologies using machine learning, molecular dynamics, and artificial intelligence.

“I hope the paper gives readers an accessible starting point for understanding where protein corona research has come from and where it may be going,” said Hao. “The growing use of computation and AI is promising, but reliable prediction will still depend on good experimental data, consistent reporting, external validation, and close cooperation between computational and laboratory researchers.”

Source: “From protein corona characterization to computational and AI-enabled approaches: Mapping the evolution of nano–bio interface research,” by Hongdong Hao, Huixi Bo, Dian Chen, Xuanyi Zhou, Cheng Qian, and Guanlin Wang, Biointerphases (2026). The article can be accessed at https://doi.org/10.1116/6.0005557 .