Measuring the zeta potential of protein-coated nanoparticles presents unique challenges due to the dynamic nature of protein-nanoparticle interactions. The formation of a protein corona, variations in isoelectric points, and protein conformational changes significantly influence the electrophoretic mobility of nanoparticles, complicating data interpretation. Accurate measurement requires careful consideration of these factors, as well as strategies to differentiate between signals from bare and coated nanoparticles.

Protein corona formation is a primary challenge in zeta potential measurements. When nanoparticles are introduced into biological fluids or protein-rich environments, proteins adsorb onto their surfaces, forming a soft, dynamic layer. This corona alters the effective surface charge and hydrodynamic diameter of the nanoparticles, directly impacting their electrophoretic mobility. The composition and density of the corona depend on factors such as protein concentration, incubation time, and nanoparticle surface chemistry. For example, nanoparticles with hydrophobic surfaces tend to adsorb more proteins than hydrophilic ones, leading to greater shifts in zeta potential. The corona is also time-dependent, as proteins may undergo exchange processes (Vroman effect), where high-affinity proteins displace initially adsorbed lower-affinity proteins over time. This dynamic behavior means that zeta potential measurements must account for temporal changes to avoid misinterpretation.

The isoelectric point (pI) of both the nanoparticle and the adsorbed proteins plays a critical role in zeta potential measurements. The pI is the pH at which a molecule carries no net charge, and it determines the surface charge characteristics under different pH conditions. If the measurement pH is close to the pI of the adsorbed proteins, their contribution to the overall zeta potential diminishes, potentially leading to aggregation due to reduced electrostatic repulsion. For instance, albumin-coated nanoparticles may exhibit a zeta potential near zero at pH 4.7–5.0, the pI range of albumin, even if the bare nanoparticle has a different intrinsic charge. Conversely, at pH values far from the pI, the proteins contribute more significantly to the measured zeta potential. Therefore, buffer selection and pH control are crucial to ensure reproducible measurements and avoid misleading results due to protein charge neutralization.

Protein conformational changes upon adsorption further complicate zeta potential analysis. Proteins can denature or reorient on nanoparticle surfaces, exposing previously buried charged residues. This structural rearrangement modifies the effective surface charge density and distribution, altering the measured zeta potential. For example, fibrinogen may undergo unfolding upon adsorption, increasing its negative charge contribution. Such changes are difficult to predict and require complementary techniques, such as circular dichroism or fluorescence spectroscopy, to correlate conformational states with zeta potential shifts. Additionally, multilayer protein adsorption or incomplete coating can create heterogeneous charge distributions, leading to broad or multimodal peaks in electrophoretic mobility distributions.

Distinguishing between signals from bare and protein-coated nanoparticles is essential for accurate interpretation. In mixed systems where uncoated and coated nanoparticles coexist, the measured zeta potential represents an average value, obscuring the distinct contributions of each population. To address this, size-based separation techniques such as asymmetric flow field-flow fractionation (AF4) can be coupled with zeta potential measurements to isolate and analyze individual fractions. Alternatively, differential centrifugation or filtration may help separate free proteins from protein-nanoparticle complexes before measurement. Labeling strategies, such as fluorescent tagging of proteins, can also assist in verifying coating completeness and correlating coating density with zeta potential changes.

Sample preparation and measurement conditions must be optimized to minimize artifacts. High ionic strength buffers can compress the electrical double layer, reducing the sensitivity of zeta potential measurements, while excessively low ionic strength may induce aggregation due to insufficient electrostatic stabilization. A balance must be struck to maintain colloidal stability without masking the protein corona's influence. Temperature control is equally important, as protein adsorption kinetics and conformation are temperature-dependent. Measurements should be performed at physiologically relevant temperatures (e.g., 37°C for biomedical applications) to reflect realistic conditions.

The choice of measurement technique also affects outcomes. Phase analysis light scattering (PALS) is often preferred over traditional electrophoretic light scattering for protein-coated nanoparticles due to its higher sensitivity in low-mobility regimes. However, PALS may still struggle with highly polydisperse samples or those with weak scattering signals. Cross-validation with other techniques, such as tunable resistive pulse sensing or nanoparticle tracking analysis, can provide additional insights into the relationship between size, charge, and coating uniformity.

Data interpretation must account for the limitations of theoretical models used to calculate zeta potential from electrophoretic mobility. The Smoluchowski equation, commonly applied for large particles with thin double layers, may not hold for protein-coated nanoparticles, where the softness and permeability of the corona require more complex models like the Ohshima soft particle theory. Neglecting these corrections can lead to underestimation or overestimation of the true zeta potential.

In summary, zeta potential measurements of protein-coated nanoparticles require meticulous experimental design and data analysis to address challenges posed by corona formation, isoelectric points, and protein conformational changes. Strategies such as sample fractionation, complementary characterization techniques, and appropriate theoretical models are necessary to obtain reliable and meaningful results. By carefully controlling measurement conditions and interpreting data within the context of these complexities, researchers can better understand the surface charge behavior of protein-nanoparticle systems.