Evidence map›Paper›PMID 42552660›Full record

ReviewSmall methods2026

Multidimensional Protein Corona Analysis Toward Predictive Nano-Bio Interface Design.

Mingxuan Hou, Minglong Chen, Shiyong Liu

Abstract readReview
In one paragraph

Review in Small methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mingxuan HouState Key Laboratory of Precision and Intelligent Chemistry, Department of Polymer Science and Engineering, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui, China.
Minglong ChenState Key Laboratory of Precision and Intelligent Chemistry, Department of Polymer Science and Engineering, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui, China.
Shiyong LiuState Key Laboratory of Precision and Intelligent Chemistry, Department of Polymer Science and Engineering, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui, China.ORCID https://orcid.org/0000-0002-9789-6282

Funding

Fundamental Research Funds for the Central Universities WK2060000073Fundamental Research Funds for the Central Universities WK2060250100Fundamental Research Funds for the Central Universities WK3450000009National Natural Science Foundation of China 52021002National Natural Science Foundation of China 52233009National Natural Science Foundation of China 52350348National Natural Science Foundation of China 52425306National Natural Science Foundation of China 524B2034National Natural Science Foundation of China 92356302USTC Research Funds of the Double First-Class Initiative YD2060006006
6 · The paper itself

Abstract

Nanoparticles entering biological fluids are rapidly coated by proteins and other biomolecules, converting their synthetic surfaces into biologically active nano-bio interfaces. These coronas regulate colloidal stability, immune recognition, cellular uptake, biodistribution, pharmacokinetics, cargo delivery, and toxicity. Yet a protein list obtained by mass spectrometry captures only part of this interface. Corona identity and function are also shaped by protein organization, binding stability, exchange dynamics, conformational changes, and molecular accessibility. Here, we discuss recent progress in protein corona isolation and analysis from a question-oriented analytical perspective, with emphasis on how centrifugation, magnetic recovery, affinity- or chemistry-enabled capture, chromatography, filtration, and field-flow fractionation (FFF) influence the fidelity, integrity, and comparability of recovered coronas. We then examine how proteomic profiling can be integrated with binding measurements, interfacial structural analysis and functional validation to distinguish descriptive corona signatures from biologically meaningful mechanisms. We further consider how biofluid composition, disease state, tissue interfaces and cellular environments remodel corona identity, presentation, and bioactivity. Finally, we argue that standardized reporting, computational modeling, and AI-enabled approaches are essential for converting protein corona datasets into reproducible and predictive knowledge that can guide the design of drug delivery systems and precision nanomedicines.

Indexed as

NanoparticlesProtein CoronaAnimalsHumansMass SpectrometryProteomicsProtein CoronaAI‐enabled predictive modelingcorona isolationinterfacial characterizationmultidimensional decodingnano‐bio interfaceprotein corona

Identifiers

PMID42552660
PMCPMC13555681

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.