Despite the innovations in nanotechnology in the past few decades, biological fate and toxicity of engineered nanomaterials (ENMs) is poorly understood with respect to molecular level interactions with biological systems. In living systems, ENMs undergo chemical and physical changes, including adsorption of biological macromolecules like proteins. This protein corona leaves the particle surface with little resemblance to the original ENM, altering the bioavailability, reactivity, and biological response. The central hypothesis of this project is that peptides can serve as structural mimics of physiologically relevant proteins to probe physiochemical characteristics mediating ENM protein corona formation, dynamics and biological response. The biophysical attributes of ENMs and proteins that facilitate interaction will be discovered by studying a library of structurally diverse peptides upon interaction with a small collection of noble metal ENMs, varied in material and surface chemistries. The proposed experiments provide novel probes of molecular level protein-ENM reactivity that span various levels of complexity.
The specific aims of the research are: (1) evaluate biophysical characteristics that facilitate protein-ENM interactions and stability, (2) to characterize individal peptides dynamics within a complex, dynamic ENM protein corona, and (3) to assay the role of the changing protein corona in mammalian cell response to ENMs. The tools developed will be broadly applicable to the major challenge of characterizing coronal protein dynamics within complex systems. Long term implications of this work include prioritization of engineered and biological properties that mediate ENM physiological reactivity, with applications in ENM design and safe use in nanomedicine.
Engineered nanomaterials (ENMs) are designed for a variety of applications, including medical devices and drugs, but biological response to ENMs is complicated by interactions with biomolecules that alter reactivity. This project provides new approaches to investigate formation and dynamics of the proteins interacting with ENMs. Developments will be applied to predictive models of behavior and controlled design of safer ENMs.
| Findlay, Matthew R; Freitas, Daniel N; Mobed-Miremadi, Maryam et al. (2018) Machine learning provides predictive analysis into silver nanoparticle protein corona formation from physicochemical properties. Environ Sci Nano 5:64-71 |
