[Paper Review] Protein corona composition of PEGylated nanoparticles correlates strongly with amino acid composition of protein surface

Giovanni Settanni, Jiajia Zhou+5 more|arXiv (Cornell University)|Dec 28, 2016

Polymer Surface Interaction Studies11 references9 citations

TL;DR

This study reveals that the protein corona composition on PEGylated nanoparticles is strongly governed by the amino acid composition of protein surfaces, with PEG preferentially interacting with non-polar residues. Molecular dynamics simulations and a solvent-accessible surface area model accurately predict corona composition, matching experimental label-free proteomics data.

ABSTRACT

Extensive molecular dynamics simulations reveal that the interactions between proteins and poly(ethylene glycol)(PEG) can be described in terms of the surface composition of the proteins. PEG molecules accumulate around non-polar residues while avoiding polar ones. A solvent-accessible-surface-area model of protein adsorption on PEGylated nanoparticles accurately fits a large set of data on the composition of the protein corona recently obtained by label-free proteomic mass spectrometry.

Motivation & Objective

• To understand the molecular determinants governing protein corona formation on PEGylated nanoparticles.
• To investigate how protein surface composition influences interactions with PEG chains.
• To develop a predictive model for protein corona composition based on protein surface properties.
• To validate the model against experimental label-free proteomic data on nanoparticle corona composition.

Proposed method

• Conducting extensive molecular dynamics simulations of protein-PEG interactions in aqueous environments.
• Analyzing preferential accumulation of PEG molecules around specific amino acid residues based on surface hydrophobicity.
• Developing a solvent-accessible surface area (SASA)-based model to quantify protein-PEG interaction energy.
• Fitting the SASA model to a large dataset of experimentally measured protein corona compositions from label-free proteomics.
• Comparing simulation predictions with experimental corona compositions to assess model accuracy.
• Using the model to correlate protein surface amino acid composition with observed corona enrichment or depletion.

Experimental results

Research questions

• RQ1 How does the amino acid composition of a protein's surface influence its adsorption affinity to PEGylated nanoparticles?
• RQ2 What is the role of hydrophobic versus polar residues in determining protein-PEG interactions?
• RQ3 Can a solvent-accessible surface area model quantitatively predict the composition of the protein corona on PEGylated nanoparticles?
• RQ4 To what extent do simulation-based predictions of protein corona composition align with experimental label-free proteomic data?
• RQ5 Which specific amino acid residues show preferential interaction with PEG chains in the corona formation process?

Key findings

• PEG molecules selectively accumulate around non-polar amino acid residues on protein surfaces while avoiding polar ones.
• The solvent-accessible surface area (SASA) model accurately predicts the composition of the protein corona on PEGylated nanoparticles.
• The model fits a large dataset of experimental protein corona compositions obtained via label-free proteomic mass spectrometry.
• Proteins with higher surface content of non-polar residues show stronger enrichment in the protein corona on PEGylated nanoparticles.
• The correlation between protein surface composition and corona formation is robust and quantitatively predictable using the SASA model.
• The study establishes a direct link between intrinsic protein surface properties and nanoparticle corona composition, enabling predictive design of biocompatible nanoparticles.