RESUMO
Classical Coulombic interaction, characterized by electrostatic interactions mediated through surface charges, is often regarded as the primary determinant in nanoparticles' (NPs) cellular association and internalization. However, the intricate physicochemical properties of particle surfaces, biomolecular coronas, and cell surfaces defy this oversimplified perspective. Moreover, the nanometrological techniques employed to characterize NPs in complex physiological fluids often exhibit limited accuracy and reproducibility. A more comprehensive understanding of nanoparticle-cell membrane interactions, extending beyond attractive forces between oppositely charged surfaces, necessitates the establishment of databases through rigorous physical, chemical, and biological characterization supported by nanoscale analytics. Additionally, computational approaches, such as in silico modeling and machine learning, play a crucial role in unraveling the complexities of these interactions.
