Elucidating molecular regulatory rules of nanoparticle biological identity via standardized deep proteomics
4 affiliations
- 1Zhejiang Cancer Hospital, Zhejiang Provincial Key Laboratory of Protein Detection Technology and Diagnostic Equipment, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou 310022, Zhejiang, People’s Republic of China
- 2Cancer Center and Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macau 999078, China
- 3School of Life Sciences, Tianjin University, Tianjin 300072, China
- 4School of Molecular Medicine, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, Zhejiang, China
Abstract
The biological identity of nanoparticles is often redefined upon exposure to physiological fluids through the formation of a protein corona (PC), However, the molecular rules linking synthetic design to biological fate remain elusive owing to the fragmented and inconsistent proteomics data. Here, leveraging a standardized deep proteomic database of 42 diverse nanomaterials, we reveal the general molecular selection rules that govern the PC formation. We demonstrate that the PC is not a product of random adsorption but is shaped by strict property-dependent recruitment. First, surface charge regulates cellular uptake, with anionic nanoparticles specifically recruiting adhesion proteins to promote Itgav-mediated endocytosis, thus forming a causal charge-corona-receptor chain. Second, PEGylation engineers immune evasion by selectively depleting specific complement and coagulation factors, rather than merely preventing protein adsorption. Third, nanoparticle geometry imposes structural constraints and selects proteins based on specific physicochemical features such as lysine content. Beyond mechanistic insights, we show that material-specific PCs can rebalance the serum proteome and enable the detection of low-abundance disease biomarkers. This work shifts the paradigm from empirical description toward rule-based prediction and provides a foundational framework for rationally engineering nanomedicines with predictable and programmable biological identities.
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BibTeX
@article{jiang2026elucidating,
title = {{Elucidating molecular regulatory rules of nanoparticle biological identity via standardized deep proteomics}},
author = {Chao Jiang and Haozhe Huang and Rongzi Gao and Yuling Du and Baichuan Jin and Wenwei Li and Mengjie Wang and Yunlu Dai and Yuan Liu},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
year = {2026},
month = oct,
doi = {10.1073/pnas.2618716123},
url = {https://doi.org/10.1073/pnas.2618716123},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Elucidating molecular regulatory rules of nanoparticle biological identity via standardized deep proteomics
AU - Chao Jiang
AU - Haozhe Huang
AU - Rongzi Gao
AU - Yuling Du
AU - Baichuan Jin
AU - Wenwei Li
AU - Mengjie Wang
AU - Yunlu Dai
AU - Yuan Liu
PY - 2026
DA - 2026/10/29
JO - Proceedings of the National Academy of Sciences of the United States of America
DO - 10.1073/pnas.2618716123
UR - https://doi.org/10.1073/pnas.2618716123
AB - The biological identity of nanoparticles is often redefined upon exposure to physiological fluids through the formation of a protein corona (PC), However, the molecular rules linking synthetic design to biological fate remain elusive owing to the fragmented and inconsistent proteomics data. Here, leveraging a standardized deep proteomic database of 42 diverse nanomaterials, we reveal the general molecular selection rules that govern the PC formation. We demonstrate that the PC is not a product of random adsorption but is shaped by strict property-dependent recruitment. First, surface charge regulates cellular uptake, with anionic nanoparticles specifically recruiting adhesion proteins to promote Itgav-mediated endocytosis, thus forming a causal charge-corona-receptor chain. Second, PEGylation engineers immune evasion by selectively depleting specific complement and coagulation factors, rather than merely preventing protein adsorption. Third, nanoparticle geometry imposes structural constraints and selects proteins based on specific physicochemical features such as lysine content. Beyond mechanistic insights, we show that material-specific PCs can rebalance the serum proteome and enable the detection of low-abundance disease biomarkers. This work shifts the paradigm from empirical description toward rule-based prediction and provides a foundational framework for rationally engineering nanomedicines with predictable and programmable biological identities.
SN - 0027-8424
SN - 1091-6490
ER -