Biophysical Descriptors of Nanoparticle Protein Coronas

Area of Science:

• Nanomaterial science
• Biophysics
• Computational toxicology

Background:

• Nanoparticle (NP) interactions with biological systems lead to the formation of a nanoparticle-protein corona (NP-PC).
• Characterizing NP-PC biophysical properties and molecular interactions at an atomic level is challenging.
• Existing methods for NP-PC modeling are limited in detail and scope.

Purpose of the Study:

• To develop and apply atomistic molecular dynamics (MD) simulations to study NP-PC formation.
• To analyze the biophysical properties of NP-PC models, including surface hydrophobicity and charge.
• To characterize the transition from the hard (NP-proximal) to the soft (NP-distal) corona regions.

Main Methods:

• Atomistic molecular dynamics (MD) simulations of proteins interacting with TiO2 and SiO2 nanoparticles.
• Molecular docking to generate homo- and hetero-oligomers within NP-PCs.
• Analysis of surface biophysical properties, such as hydrophobic fraction of solvent-accessible surface area (SASA_H) and surface charge distribution.

Main Results:

• Established scaling relationships between NP-PC protein composition and SASA_H values.
• Developed a systematic method to characterize the hard-to-soft corona transition.
• Generated atomistic NP-PC models for efficient biophysical descriptor calculation.

Conclusions:

• Atomistic NP-PC modeling provides detailed insights into NP-biomolecule interactions.
• This approach can guide future nanotoxicity risk assessments.
• The developed methodology facilitates the study of NP-PC formation in diverse biological systems.