Graphene oxide: multiscale computational approaches at nanobioeco interfaces

Abstract

When released into the environment, nanomaterials engage in interactions with the present organic and metals pollutants altering their bioavailability and resulting in complicated mixture toxicity effects. Biomolecular coronas formed upon the release significantly affect this process, competing with pollutants for surface interaction sites or multiplying the possibilities of interactions. Understanding nanomaterials' environmental transformations are essential to their risk assessment, and there is still plenty to explore regarding the processes at the interface between nanomaterials, biomolecules, and pollutants. Computational approaches have provided valuable advances in understanding mechanistic aspects of nano-bio interactions; however, due to the increased size and complexity inherent in biological systems, it is necessary to address multiple size scales (extrapolating from atomic-meso-macro) in simulations to understand the relevant processes. Regarding the biocorona formation, all-atom simulations alone cannot reach the relevant system sizes and multi-scale theory methods are required to model the corona, reflect the multitude of molecules and explore their orientation on nanomaterials surfaces in a feasible time. In this project, we propose to adapt the coarse-grained United Atom method to characterize the interaction of different types of environmental biomolecules (e.g., proteins, humic acids, and lipids) with graphene oxide surface, evaluating the binding energy and orientations of adsorbed molecules, then, to compare the interaction of the resulting biocoronas with common contaminants. Thiswork will contribute to the mechanistic understanding of the formation of biocoronas on graphene oxide in the environment and how they modulate the adsorption of pollutants by the nanomaterial. The learned methodologies will contribute to scaling up the models of graphene oxide interactions with organic matter and organic pollutants, which are the subject of the ongoing project of the PhD student in Brazil. (AU)