TL;DR
This study uses electrostatic modeling to predict protein orientations near charged nanosurfaces, providing insights for biosensor design and improving immunoassay sensitivity through simulation-guided surface and protein modifications.
Contribution
Introduces a novel electrostatic modeling approach to predict protein orientations near charged surfaces, validated with experimental and simulation data, aiding biosensor development.
Findings
Protein GB1D4' shows dipolar orientation behavior near charged surfaces.
IgG2a antibodies can have favorable orientations at certain surface charges and salt levels.
Local interactions can outweigh dipole effects in protein orientation near surfaces.
Abstract
Protein-surface interactions are ubiquitous in biological processes and bioengineering, yet are not fully understood. In biosensors, a key factor determining the sensitivity and thus the performance of the device is the orientation of the ligand molecules on the bioactive device surface. Adsorption studies thus seek to determine how orientation can be influenced by surface preparation. In this work, protein orientation near charged nanosurfaces is obtained under electrostatic effects using the Poisson-Boltzmann equation, in an implicit-solvent model. Sampling the free energy for protein GB1D4' at a range of tilt and rotation angles with respect to the charged surface, we calculated the probability of the protein orientations and observed a dipolar behavior. This result is consistent with published experimental studies and combined Monte Carlo and molecular dynamics simulations using…
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