Predicting Cytotoxicity of Metal Oxide Nanoparticles using Isalos Analytics Platform.

A literature curated dataset containing 24 distinct metal oxide (MexOy) nanoparticles (NPs), including 15 physicochemical, structural and assay-related descriptors, was enriched with 62 atomistic computational descriptors and exploited to produce a robust and validated in silico model for prediction of NP cytotoxicity. The model can be used to predict the cytotoxicity (cell viability) of MexOy NPs based on the colorimetric lactate dehydrogenase (LDH) assay and the luminometric adenosine triphosphate (ATP) assay, both of which quantify irreversible cell membrane damage. Out of the 77 total descriptors used, 7 were identified as being significant for induction of cytotoxicity by MexOy NPs. These were NP core size, hydrodynamic size, assay type, exposure dose, the energy of the MexOy conduction band (EC), the coordination number of the metal atoms on the NP surface (Avg. C.N. Me atoms surface) and the average force vector surface normal component of all metal atoms (v⟂ Me atoms surface). The significance and effect of these descriptors is discussed to demonstrate their direct correlation with cytotoxicity. The produced model has been made publicly available by the Horizon 2020 (H2020) NanoSolveIT project and will be added to the project's Integrated Approach to Testing and Assessment (IATA).

NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment.

Nanotechnology has enabled the discovery of a multitude of novel materials exhibiting unique physicochemical (PChem) properties compared to their bulk analogues. These properties have led to a rapidly increasing range of commercial applications; this, however, may come at a cost, if an association to long-term health and environmental risks is discovered or even just perceived. Many nanomaterials (NMs) have not yet had their potential adverse biological effects fully assessed, due to costs and time constraints associated with the experimental assessment, frequently involving animals. Here, the available NM libraries are analyzed for their suitability for integration with novel nanoinformatics approaches and for the development of NM specific Integrated Approaches to Testing and Assessment (IATA) for human and environmental risk assessment, all within the NanoSolveIT cloud-platform. These established and well-characterized NM libraries (e.g. NanoMILE, NanoSolutions, NANoREG, NanoFASE, caLIBRAte, NanoTEST and the Nanomaterial Registry (>2000 NMs)) contain physicochemical characterization data as well as data for several relevant biological endpoints, assessed in part using harmonized Organisation for Economic Co-operation and Development (OECD) methods and test guidelines. Integration of such extensive NM information sources with the latest nanoinformatics methods will allow NanoSolveIT to model the relationships between NM structure (morphology), properties and their adverse effects and to predict the effects of other NMs for which less data is available. The project specifically addresses the needs of regulatory agencies and industry to effectively and rapidly evaluate the exposure, NM hazard and risk from nanomaterials and nano-enabled products, enabling implementation of computational 'safe-by-design' approaches to facilitate NM commercialization.

Fe-Doped ZnO nanoparticle toxicity: assessment by a new generation of nanodescriptors.

In the search for novel tools to combat cancer, nanoparticles (NPs) have attracted a lot of attention. Recently, the controlled release of cancer-cell-killing metal ions from doped NPs has shown promise, but fine tuning of dissolution kinetics is required to ensure specificity and minimize undesirable toxic side-effects. Theoretical tools to help in reaching a proper understanding and finally be able to control the dissolution kinetics by NP design have not been available until now. Here, we present a novel set of true nanodescriptors to analyze the charge distribution, the effect of doping and surface coating of whole metal oxide NP structures. The polarizable model of oxygen atoms enables light to be shed on the charge distribution on the NP surface, allowing the in detail study of the factors influencing the release of metal ions from NPs. The descriptors and their capabilities are demonstrated on a Fe-doped ZnO nanoparticle system, a system with practical outlook and available experimental data.

In Silico Design of Optimal Dissolution Kinetics of Fe-Doped ZnO Nanoparticles Results in Cancer-Specific Toxicity in a Preclinical Rodent Model.

Cancer cells have unique but widely varying characteristics that have proven them difficult to be treated by classical therapeutics and calls for novel and selective treatment options. Nanomaterials (NMs) have been shown to display biological effects as a function of their chemical composition, and the extent and exact nature of these effects can vary between different biological environments. Here, ZnO NMs are doped with increasing levels of Fe, which allows to finely tune their dissolution rate resulting in significant differences in their biological behavior on cancer or normal cells. Based on in silico analysis, 2% Fe-doped ZnO NMs are found to be optimal to cause selective cancer cell death, which is confirmed in both cultured cells and syngeneic tumor models, where they also reduce metastasis formation. These results show that upon tuning NM chemical composition, NMs can be designed as a targeted selective anticancer therapy.

An Integrated Data-Driven Strategy for Safe-by-Design Nanoparticles: The FP7 MODERN Project.

The development and implementation of safe-by-design strategies is key for the safe development of future generations of nanotechnology enabled products. The safety testing of the huge variety of nanomaterials that can be synthetized is unfeasible due to time and cost constraints. Computational modeling facilitates the implementation of alternative testing strategies in a time and cost effective way. The development of predictive nanotoxicology models requires the use of high quality experimental data on the structure, physicochemical properties and bioactivity of nanomaterials. The FP7 Project MODERN has developed and evaluated the main components of a computational framework for the evaluation of the environmental and health impacts of nanoparticles. This chapter describes each of the elements of the framework including aspects related to data generation, management and integration; development of nanodescriptors; establishment of nanostructure-activity relationships; identification of nanoparticle categories; hazard ranking and risk assessment.

Bond Strength and Reactivity Scales for Lewis Superacid Adducts: A Comparative Study with In(OTf)3 and Al(OTf)3.

Metal triflates, often called Lewis superacids, are potent catalysts for organic synthesis. However, the reactivity of a given Lewis superacid toward a given base is difficult to anticipate. A systematic screening of catalysts is often necessary when developing synthetic methodologies. Presented herein is the development of quantitative reactivity and bond strength scales by using mass spectrometry (MS). By applying a collision-induced dissociation (CID) technique to the adducts formed between Lewis superacids Al(OTf)3 or In(OTf)3 with a series of amides bases, including monodentate and bidentate ligands, different dissociation pathways were observed. Quantitative relative energy scales were established by performing energy-resolved mass spectrometry (ERMS) analysis on the adducts. ERMS of the adducts affords a bond strength scale when the fragmentation leads to the loss of a ligand, and reactivity scales when the dissociation leads to the C-F bond activation of one triflate anion or the deprotonation of the ligand. Al(OTf)3 was found to bind stronger to amides than In(OTf)3 and to provide the most reactive adducts.

Theoretical modeling of HPV: QSAR and novodesign with fragment approach.

Structure-activity relationships in a data set of HPV6-E1 helicase ATPase inhibitors were investigated based on two different sets of descriptors. Statistically significant four parameter Quantitative Structure-Activity Relationships (QSAR) models were constructed and validated in both cases (R(2)=0.849; R(2) cv=0.811; F=52.20; s(2)=0.25; N=42). A Fragment based QSAR (FQSAR) approach was applied for developing a fragment-QSAR equation, which enabled the construction of virtual structures for novel ATPase inhibitors with desired or pre-defined activity.

Gas-phase lithium cation basicity: revisiting the high basicity range by experiment and theory.

According to high level calculations, the upper part of the previously published FT-ICR lithium cation basicity (LiCB at 373 K) scale appeared to be biased by a systematic downward shift. The purpose of this work was to determine the source of this systematic difference. New experimental LiCB values at 373 K have been measured for 31 ligands by proton-transfer equilibrium techniques, ranging from tetrahydrofuran (137.2 kJ mol(-1)) to 1,2-dimethoxyethane (202.7 kJ mol(-1)). The relative basicities (ΔLiCB) were included in a single self-consistent ladder anchored to the absolute LiCB value of pyridine (146.7 kJ mol(-1)). This new LiCB scale exhibits a good agreement with theoretical values obtained at G2(MP2) level. By means of kinetic modeling, it was also shown that equilibrium measurements can be performed in spite of the formation of Li(+) bound dimers. The key feature for achieving accurate equilibrium measurements is the ion trapping time. The potential causes of discrepancies between the new data and previous experimental measurements were analyzed. It was concluded that the disagreement essentially finds its origin in the estimation of temperature and the calibration of Cook's kinetic method.

Computational study of the Sonogashira cross-coupling reaction in the gas phase and in dichloromethane solution.

The Sonogashira cross-couplig reaction, consisting of oxidative addition, cis-trans isomerization, transmetalation, and reductive elimination, was computationally modeled using the DFT B3LYP/cc-pVDZ method for reaction between bromobenzene and phenylacetylene. Palladium diphosphane was used as a catalyst, copper(I) bromide as a co-catalyst and trimethylamine as a base. The reaction mechanism was studied both in the gas phase and in dichloromethane solution using PCM method. The complete catalytic cycle is thermodynamically strongly shifted toward products (diphenylacetylene and regenerated palladium catalyst) and is exothermic being in accordance with experimental data. The rate-determining step is the oxidative addition, since the highest point on the Gibbs energy graph of the complete reaction is the transition state of this step. This conclusion is also supported by recent experimental data. The computed energy profile suggests that the transmetalation step is initiated by the dissociation of neutral ligand, while the activation Gibbs energy of this step is 0.1 kcal mol(-1) in the gas phase.

Computational study on the reactivity of tetrazines toward organometallic reagents.

The possible reaction pathways between methyllithium and disubstituted 1,2,4,5-tetrazines (bearing methyl, methylthio, phenyl, and 3,5-dimethylpyrazolyl groups) were investigated by means of the density functional theory B3LYP/6-31G* method. Solvation was modeled using the supermolecule approach, adding one tetrahydrofuran molecule to the complexes. Comparison of the calculated energies and structures for the alternate azaphilic and nucleophilic addition pathways showed that the azaphilic addition is kinetically favored over nucleophilic addition, while thermodynamically the nucleophilic addition is usually preferred. The coordination of the tetrazine molecule with methyllithium was found to play a crucial role in the process. These findings provide the first rationale for the experimentally observed unique reactivity of tetrazines toward polar organometallic reagents, suggesting the presence of a kinetically controlled process.

Computational study of cesium cation interactions with neutral and anionic compounds related to soil organic matter.

The gas-phase cesium cation affinities (CsCAs) and basicities (CsCBs) for 56 simple neutral compounds (mostly aromatic molecules) and 41 anions (carboxylates and phenolates) were calculated using density functional theory (DFT), in the context of the interaction of Cs(+) with soil organic matter (SOM). The B3LYP/def2-TZVP method gives in general CsCAs and CsCBs in a good agreement with experimental data. The strong deviations in case of NO(3)(-) and CsSO(4)(-) anions need further experimental investigations as the high-level CCSD(T) calculations support B3LYP results. Different cesium cation complexation patterns between Cs(+) and the neutral and anionic systems are discussed. As expected, the strongest CsCAs are observed for anions. The corresponding quantities are approximately by 4-5 times higher than for the neutral counterparts, being in the range 90-118 kcal/mol. The weakest cesium cation bonding is observed in the case of unsubstituted aromatic systems (11-15 kcal/mol).