Explore the vast range of titles available.

Fluorinated graphene, a two-dimensional nanomaterial composed of three atomic layers, a central carbon layer sandwiched between two layers of fluorine atoms, has attracted considerable attention across various fields, particularly for its potential use in biomedical applications. Nonetheless, scant effort has been devoted to assessing the potential toxicological implications of this nanomaterial. In this study, we scrutinize the potential impact of fluorinated graphene on a protein model, HP35 by utilizing extensive molecular dynamics (MD) simulation methods. Our MD results elucidate that upon adsorption to the nanomaterial, HP35 undergoes a denaturation process initiated by the unraveling of the second helix of the protein and the loss of the proteins hydrophobic core. In detail, substantial alterations in various structural features of HP35 ensue, including alterations in hydrogen bonding, Q value, and RMSD. Subsequent analyses underscore that hydrophobic and van der Waals interactions (predominant), alongside electrostatic energy (subordinate), exert influence over the adsorption of HP35 on the fluorinated graphene surface. Mechanistic scrutiny attests that the unrestrained lateral mobility of HP35 on the fluorinated graphene nanomaterial primarily causes the exposure of HP35's hydrophobic core, resulting in the eventual structural denaturation of HP35. A trend in the features of 2D nanostructures is proposed that may facilitate the denaturation process. Our findings not only substantiate the potential toxicity of fluorinated graphene but also unveil the underlying molecular mechanism, which thereby holds significance for the prospective utilization of such nanomaterials in the field of biomedicine.

All-atom molecular dynamics simulations now allow us to create movies of proteins folding and unfolding. However, it is difficult to assess the accuracy of the folding mechanisms observed because experiments cannot yet directly resolve events occurring along the transition paths between unfolded and folded states. Protein folding ϕ-values provide residue-resolved information about folding mechanisms by comparing the effects of mutations on folding rates and stability, but determining ϕ-values by separately simulating mutant proteins would be computationally demanding and prone to large statistical errors. Here we use transition path theory to develop a method for computing ϕ-values directly from the transition path ensemble, without the need for additional simulations. This path-based approach uses the full transition path information available from equilibrium folding and unfolding trajectories, or from transition path sampling, and does not require identification of folding transition states. Applying our approach to a set of simulations of 10 small proteins by Shaw and coworkers [Lindorff-Larsen K, Piana S, Dror RO, Shaw DE (2011) Science 334(6055):517–520; Piana S, Lindorff-Larsen K, Shaw DE (2011) Biophys J 100(9):L47–L49; and Piana S, Lindorff-Larsen K, Shaw DE (2013) Proc Natl Acad Sci USA 110(15):5915–5920], we find good agreement with experiments in most cases where data are available. We can further resolve the contributions to fractional ϕ-values coming from partial contact formation versus transition path heterogeneity. Although in some cases, there is substantial heterogeneity of folding mechanism, in others, such as Ubiquitin, the mechanism is strongly conserved.