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Tuning gold-based surface functionalization for streptavidin detection: A combined simulative and experimental study.

Sutapa Dutta^1,2, Mariacristina Gagliardi³, Luca Bellucci³

¹Dipartimento di Scienze Chimiche, Università di Padova, Padova, Italy.

Frontiers in Molecular Biosciences

|December 15, 2022

Summary

This study demonstrates a gold biosensor surface that captures proteins using biotin and streptavidin. Simulations and experiments confirm its ability to specifically bind target proteins, guiding future biosensor design.

Keywords:

Brownian dynamics acoustic wave biosensor binding affinity molecular dynamics streptadivin-biotin assemblies surface functionalization

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Area of Science:

Biomaterials Science
Surface Chemistry
Computational Biophysics

Background:

Development of sensitive biosensors is crucial for detecting target proteins.
Protein-ligand interactions are key for biosensor functionality.
Understanding binding mechanisms at the nanoscale is essential for optimizing sensor design.

Purpose of the Study:

To design and validate a gold-functionalized surface for specific protein capture.
To elucidate the binding mechanism of streptavidin on biotinylated surfaces using multiscale simulations.
To correlate simulation findings with experimental data for enhanced biosensor development.

Main Methods:

Multiscale simulations: Brownian Dynamics (BD) and classical Molecular Dynamics (MD).
Surface functionalization: Biotinylated polyethylene glycol (PEG) chains on gold via thiol-Au chemistry.
Experimental validation: Quartz Crystal Microbalance with Dissipation monitoring (QCM-D).

Main Results:

Identified preferred initial orientation of streptavidin using BD simulations.
Refined binding poses and analyzed forces/kinetics using MD simulations.
Confirmed specific streptavidin capture and stable attachment using QCM-D experiments.

Conclusions:

Confined biotin moieties effectively capture streptavidin from solution.
Simulation parameters can guide the rational design of highly sensitive biosensors.
The study provides a framework for optimizing protein-capture surfaces.