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Quantitative Cooperative Binding Model for Intrinsically Disordered Proteins Interacting with Nanomaterials.

Da-Wei Li¹, Mouzhe Xie², Rafael Brüschweiler^1,2,3

¹Campus Chemical Instrument Center, The Ohio State University, Columbus, Ohio 43210, United States.

Journal of the American Chemical Society

|May 20, 2020

Summary

A new model, SILC, quantitatively predicts how intrinsically disordered proteins (IDPs) bind to nanoparticles. This helps understand IDP behavior and design nanomaterials for biological applications.

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Fluorescence Anisotropy as a Tool to Study Protein-protein Interactions

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Published on: October 21, 2016

Area of Science:

Biophysics
Materials Science
Protein Science

Background:

Intrinsically disordered proteins (IDPs) exhibit diverse binding behaviors with variable affinities.
Understanding IDP interactions with nanomaterials is crucial for controlling their biological functions.
Residue-level variations in IDPs influence their binding properties.

Purpose of the Study:

To develop a quantitative model for predicting residue-specific binding affinities of IDPs to nanoparticles.
To explain the binding cooperativity and behavior of IDP-nanoparticle complexes.
To provide a framework for understanding nanotoxicity and targeted delivery using IDPs and nanomaterials.

Main Methods:

Solution NMR relaxation experiments to measure binding affinities.
Development of a first-principle analytical statistical mechanical model (SILC).
Parametrization of SILC for anionic synthetic silica nanoparticles (SNPs).

Main Results:

SILC accurately predicts residue-specific binding affinities for IDPs interacting with SNPs.
The model captures differences in overall binding affinities and fine affinity profile details.
SILC successfully predicts the effects of site-directed mutagenesis at the residue level.

Conclusions:

The SILC model provides an analytical description of intrinsically disordered protein-nanoparticle complexes.
This model advances the understanding of IDP-nanomaterial interactions.
It offers potential for designing targeted nanomaterials for biomedical applications.