In silico identification of protein targets for chemical neurotoxins using ToxCast in vitro data and read-across within the QSAR toolbox.

There are many mechanisms of neurotoxicity that are initiated by the interaction of chemicals with different neurological targets. Under the U.S. Environmental Protection Agency's ToxCast program, the biological activity of thousands of chemicals was screened in biochemical and cell-based assays in a high-throughput manner. Two hundred sixteen assays in the ToxCast screening database were identified as targeting a total of 123 proteins having neurological functions according to the Gene Ontology database. Data from these assays were imported into the Organization for Economic Co-operation and Development QSAR Toolbox and used to predict neurological targets for chemical neurotoxins. Two sets of data were generated: one set was used to classify compounds as active or inactive and another set, composed of AC50s for only active compounds, was used to predict AC50 values for unknown chemicals. Chemical grouping and read-across within the QSAR Toolbox were used to identify neurologic targets and predict interactions for pyrethroids, a class of compounds known to elicit neurotoxic effects in humans. The classification prediction results showed 79% accuracy while AC50 predictions demonstrated mixed accuracy compared with the ToxCast screening data.

Coarse-grained molecular-dynamics simulations of the self-assembly of pentablock copolymers into micelles.

Multiblock polymers in aqueous solution, where one or several blocks are hydrophobic, exhibit a rich variety of phases and states of aggregation. In this paper, we investigate a pentablock system ABCBA, where the B block is always hydrophilic and the A and C blocks have varying degrees of hydrophobicity depending on external conditions. We report coarse-grained molecular-dynamics simulations where the solvent is included explicitly and monomers interact via a 6-9 Lennard Jones potential function. The hydrophobic interaction is modeled by tuning the parameter controlling the strength of the interaction between the hydrophobic monomers and the solvent. We investigate the structure and morphology of the micelles for two concrete situations representing changes in temperature and the pH level. The simulated system is directly relevant to a recently synthesized pentablock system consisting of a triblock Pluronic with an added pH-sensitive end group [B. C. Anderson et al., Macromolecules 36, 1670 (2003)].

Viscoelastic model for the dynamic structure factors of binary systems.

This paper presents the viscoelastic model for the Ashcroft-Langreth dynamic structure factors of liquid binary mixtures. We also provide expressions for the Bhatia-Thornton dynamic structure factors and, within these expressions, show how the model reproduces both the dynamic and the self-dynamic structure factors corresponding to a one-component system in the appropriate limits (pseudobinary system or zero concentration of one component). In particular we analyze the behavior of the concentration-concentration dynamic structure factor and longitudinal current, and their corresponding counterparts in the one-component limit, namely, the self-dynamic structure factor and self-longitudinal current. The results for several lithium alloys with different ordering tendencies are compared with computer simulation data, leading to a good qualitative agreement, and showing the natural appearance in the model of the fast sound phenomenon.