Novel approach for efficient predictions properties of large pool of nanomaterials based on limited set of species: nano-read-across

Creating suitable chemical categories and developing read-across methods, supported by quantum mechanical calculations, can be an effective solution to solving key problems related to current scarcity of data on the toxicity of various nanoparticles. This study has demonstrated that by applying a nano-read-across, the cytotoxicity of nano-sized metal oxides could be estimated with a similar level of accuracy as provided by quantitative structure-activity relationship for nanomaterials (nano-QSAR model(s)). The method presented is a suitable computational tool for the preliminary hazard assessment of nanomaterials. It also could be used for the identification of nanomaterials that may pose potential negative impact to human health and the environment. Such approaches are especially necessary when there is paucity of relevant and reliable data points to develop and validate nano-QSAR model

Preliminary studies of interaction between nanotubes and toll-like receptors

Toll-like receptors ( TLR s) are a group of proteins which play a crucial role in the innate immune system. The main function of TLR s is to recognize structurally conserved molecules, which are inserted to the organism of the host by microbes, and then to activate the immune response. Current development of drugs is often connected not only with the drug itself, but also with the way it is delivered into the human body to interact direc tly with the source of the problem. Carbon nanostructures, particularly nanotubes, are one of the car rier molecules of the future. However, there is still no knowledge about the exact mechani sms of toxicity and possible interactions with macromolecules, such as proteins. In our study we tr ied to determine, if the nanotubes could interfere with the innate immune system by interac ting with TLR s. For this purpose, we used the following TLR structures downloaded from the RCSB Protein Data Bank: TLR 2 (3 A 7 C ), TLR 4/ MD (3 FXI ), TLR 5 (3 V 47), TLR 3 (2 A 0 Z ), and the complexes of TLR 1/ TLR 2 (2 Z 7 X ) and TLR 2/ TLR 6 (3 A 79). The preliminary results of our Steered Molecular Dynamics ( SMD ) simulations have shown that nanotubes interact very strongly with the binding pockets of some receptors ( e.g. TLR 2), which results in their binding to these sites without subst antial use of the external force

Towards mechanisms of nanotoxicity - interaction of gold nanoparticles with proteins and DNA

Even though most of the existing studies of gold nanoparticles indicate that they are safe to use, some researchers show that specific forms of nanoparticles (e.g. nanorods) are able to destroy the cell membrane and very small nanoparticles (below 37nm in diameter) in high concentration have been deadly for mice. We used the Amber12 package to perform a series of molecular dynamics (MD) simulations of gold nanoparticles with various small proteins important for the human body and a DNA molecule to determine the interactions and consequently the possible toxicity of gold clusters. Lennard-Jones interactions were used to simulate the behavior of gold nanoparticles with biomacromolecules in water with an optimal set of parameters (selected based on a comparison of MD structures and structures computed by DFT). Gold nanoparticle structures were obtained as a result of MD simulations from an initial structure, where gold atoms were at a distance of 10 ̊ A from one another. A predicted BDNA structure of a palindromic sequence‘ CGCATGAGTACGC ’ and a 2 JYK molecule were used as representatives of the DNA molecule. The preliminary results show that, in particular small gold nanoparticles, interact strongly with proteins and DNA by creating stable complexes, which can then cause harmful reactions to the human body when present in high concentration

Virtual Method Of Determining Modern Local Vibration Parameters In Life Safety Training

Creating, incorporating, and improving virtual labs is now a task that needs to be done today, not tomorrow's technology.In addition to the lecture materials, the virtual laboratory work can be demonstrated during the lecture. This eliminates the time gap between lectures and laboratory sessions, resulting in increased efficiency and quality of teaching. Effective use of virtual laboratories not only improves the quality of teaching, but also saves a lot of money.The use of personal computers has led to the creation of virtual laboratories as an alternative to traditional training laboratories. A virtual laboratory is generally a numerical programming program that has an interface that mimics a researcher's real laboratory actions (work). With the help of numerical methods of calculations on modern personal computers with high speed and large amount of memory, it is possible to study complex examples with the same accuracy as the results obtained in experiments conducted on real objects.In the following article, the use of personal computers led to the creation of virtual laboratories as an alternative to traditional training laboratories. A virtual laboratory is generally a numerical programming program that has an interface that mimics the real laboratory actions (work) of a researcher

Synthesis, Tautomeric States and Crystal Structure of (Z)-Ethyl 2-Cyano-2-(3H-Quinazoline-4-ylidene) Acetate and (Z)-Ethyl 2-Cyano-2-(2-Methyl-3H-Quinazoline-4-ylidene) Acetate

The new compounds (Z)-ethyl 2-cyano-2-(3H- and 2-methyl-3H-quinazoline-4-ylidene) acetate (1 and 2, respectively) were synthesized by multi-step reactions. Thestructures in a solution have been determined by 1H-NMR spectroscopy and in the crystalform by X-ray analysis. Molecule 1 crystallized in a primitive monoclinic cell, spacegroup à21/c. The cell dimensions are a=7.970(6) Ã¥, b=7.061(2) Ã¥, c=20.537(7) Ã¥,β=97.69(5)°, V=1145.3(10) Ã¥3. Molecule 2 crystallized in a triclinic cell, space group P-1, the cell dimensions are a=8.196(5) Ã¥, b=8.997(6) Ã¥, c=9.435(4) Ã¥, α=74.22(4)°,β=89.75(4)°, γ=74.07(5)°, V=641.9(6) Ã¥3. In both compounds the presence of intra-molecular NH---O=C hydrogen bonding between the nitrogen atom in position 3 of thequinazoline ring and a carbonyl group of the ethyl cyanoacetate residue was proven byquantum-chemical, 1H-NMR and X-ray methods

Classification nano-SAR modeling of metal oxides nanoparticles genotoxicity based on comet assay data

In nearly a decade of vigorous attempt in the toxicology and exposure research carried out to provide evidence for the assessment of health and environmental risks of nanomaterials (NMs), some progress has been made in generating the health effects and exposure data needed to perform risk assessment and develop risk management guidance. Quantitative Structure Activity Relationship ((Q)SAR) models are a powerful tool for rapid screening of large numbers and types of materials with advantage of saving time, funds and animal suffering. In this work we present first (Q)SAR models developed to predict genotoxicity of metal oxide NMs by using large initial sets of nano descriptors. We used a dataset containing in vitro comet assay genotoxicity for 16 nano metal oxides with different chemical core composition. This multi-source data was retrieved from genotoxicity profiles collected in our previous work. To properly analyse the data, we used a weight of evidence approach for evaluation of quality of the comet in vitro data for (Q)SAR modelling. Subsequently, based on the quality of checked dataset, we assigned genotoxic or non-genotoxic property to each metal core composition. By employing orthogonal partial least squares–discriminant analysis (OPLS-DA) method, nano-(Q)SAR models were derived with significant predictive power: accuracy 0.83 and 1. Conventional molecular descriptors and quantum chemical descriptors together with descriptors based on metal-ligand binding properties have been analysed to discuss the key factors affecting genotoxicity of metal oxide NMs. All derived models involve descriptors that describe possible structural factors influencing genotoxic behaviour of metal oxide NMs