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In this paper we propose a theoretical model that predicts the oxidative stress potential of oxide nanoparticles by looking at the ability of these materials to perturb the intracellular redox state. The model uses reactivity descriptors to build the energy band structure of oxide nanoparticles, assuming a particle diameter larger than 20--30 nm and no surface states in the band gap, and predicts their ability to induce an oxidative stress by comparing the redox potentials of relevant intracellular reactions with the oxides' energy structure. Nanoparticles displaying band energy values comparable with redox potentials of antioxidants or radical formation reactions have the ability to cause an oxidative stress and a cytotoxic response in vitro. We discuss the model's predictions for six relevant oxide nanoparticles (TiO2, CuO, ZnO, FeO, Fe2O3, Fe3O4) with literature in vitro studies and calculate the energy structure for 64 additional oxide nanomaterials. Such a framework would guide the development of more rational and efficient screening strategies avoiding random or exhaustive testing of new nanomaterials. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article “A rule for designing safer nanomaterials: do not interfere with the cellular redox equilibrium" by Enrico Burello, and Andrew P. Worth in the September 10, 2013 issue.

The article presents the results of a study by Jerzy Leszczynski and colleagues at Jackson State University on the development of a statistical model to assess the toxicity of metal oxide nanoparticles in cells. According to the authors, the researchers used the quantitative structure-activity relationship (QSAR) to predict the cytotoxicity of nanoparticles towards Escherichia coli and compute the structural descriptors. They add that Leszczynski defined cytotoxicy as the effective concentration of compounds that can reduce bacterial viability.

A thorough understanding of the relationships between the physicochemical properties and the behavior of nanomaterials in biological systems is mandatory for designing safe and efficacious nanomedicines. Quantitative structure-activity relationship (QSAR) methods help to establish such relationships, although their application to model the behavior of nanomaterials requires new ideas and applications to account for the novel properties of this class of compounds. This review presents and discusses a number of recent inspiring applications of QSAR modeling and descriptors for nanomaterials with a focus on approaches that attempt to describe the interactions that take place at the nano/bio-interface. The paradigm shift from classic to nano-QSAR currently relies on both theoretically and experimentally derived descriptors, and the solutions adopted for modeling are diverse, mirroring the structural and behavioral heterogeneity of nanomaterials. Research should focus on both aspects of a QSAR study: the generation of nanospecific theoretical descriptors and experimental test data., (Copyright © 2011 John Wiley & Sons, Inc.)

A method is presented for the high-throughput monitoring of reaction kinetics in homogeneous catalysis, running up to 25 coupling reactions in a single reaction vessel. This method is demonstrated and validated on the Sonogashira reaction, analyzing the kinetics for almost 500 coupling reactions. First, one-pot reactions of phenylacetylene with a set of 20 different meta- and para-substituted aryl bromides were analyzed in the presence of 17 different Pd-phosphine complexes. In addition, the temperature-dependent Sonogashira reactions were examined for 21 different ArX (X=Cl, Br, I) substrates, and the corresponding activation enthalpies and entropies were determined by means of Eyring plots: ArI (DeltaH(not equal)=48-62 kJ mol(-1); DeltaS(not equal)=-71--39 J mol(-1) K; NO(2)-->OMe), ArBr (DeltaH(not equal)=54-82 kJ mol(-1), DeltaS(not equal)=-55-11 J mol(-1) K), and ArCl (DeltaH(not equal)=95-144 kJ mol(-1), DeltaS(not equal)=-6-100 J mol(-1) K). DFT calculations established a linear correlation of DeltaH( not equal) and the Kohn-Sham HOMO energies of ArX (X=Cl, Br, I) and confirmed their involvement in the rate-limiting step. However, despite different C--X bond energies, aryl iodides and electron-deficient aryl bromides showed similar activation parameters.