New Chemicals Suppressing SARS-CoV-2 Replication in Cell Culture

Candidates to being inhibitors of the main protease (Mpro) of SARS-CoV-2 were selected from the database of Voronezh State University using molecular modeling. The database contained approximately 19,000 compounds represented by more than 41,000 ligand conformers. These ligands were docked into Mpro using the SOL docking program. For one thousand ligands with best values of the SOL score, the protein–ligand binding enthalpy was calculated by the PM7 quantum-chemical method with the COSMO solvent model. Using the SOL score and the calculated protein–ligand binding enthalpies, eighteen compounds were selected for the experiments. Several of these inhibitors suppressed the replication of the coronavirus in cell culture, and we used the best three among them in the search for chemical analogs. Selection among analogs using the same procedure followed by experiments led to identification of seven inhibitors of the SARS-CoV-2 replication in cell culture with EC50 values at the micromolar level. The identified inhibitors belong to three chemical classes. The three inhibitors, 4,4-dimethyldithioquinoline derivatives, inhibit SARS-CoV-2 replication in Vero E6 cell culture just as effectively as the best published non-covalent inhibitors, and show low cytotoxicity. These results open up a possibility to develop antiviral drugs against the SARS-CoV-2 coronavirus.     

Can We Merge the Weak and Strong Tetrel Bonds? Electronic Features of Tetrahedral Molecules Interacted with Halide Anions

Using the orbital-free quantum crystallography approach, we have disclosed the quantitative trends in electronic features for bonds of different strengths formed by tetrel (Tt) atoms in stable molecular complexes consisting of electrically neutral tetrahedral molecules and halide anions. We have revealed the role of the electrostatic and exchange-correlation components of the total one-electron static potential that are determined by the equilibrium atomic structure and by kinetic Pauli potential, which reflects the spin-dependent electron motion features of the weak and strong bonds. The gap between the extreme positions in the electrostatic and total static potentials along the line linking the Tt atom and halide anion is wide for weak bonds and narrow for strong ones. It is in very good agreement with the number of minima in the Pauli potential between the bounded atoms. This gap exponentially correlates with the exchange-correlation potential in various series with a fixed nucleophilic fragment. A criterion for categorizing the noncovalent tetrel bonds (TtB) based on the potential features is suggested.     

Machine Learning for Evaluating the Cytotoxicity of Mixtures of Nano-TiO2 and Heavy Metals: QSAR Model Apply Random Forest Algorithm after Clustering Analysis

With the development and application of nanomaterials, their impact on the environment and organisms has attracted attention. As a common nanomaterial, nano-titanium dioxide (nano-TiO₂) has adsorption properties to heavy metals in the environment. Quantitative structure-activity relationship (QSAR) is often used to predict the cytotoxicity of a single substance. However, there is little research on the toxicity of interaction between nanomaterials and other substances. In this study, we exposed human renal cortex proximal tubule epithelial (HK-2) cells to mixtures of eight heavy metals with nano-TiO₂, measured absorbance values by CCK-8, and calculated cell viability. PLS and two ensemble learning algorithms are used to build multiple QSAR models for data sets, and the test set R² is increased from 0.38 to 0.78 and 0.85, and RMSE is decreased from 0.18 to 0.12 and 0.10. After selecting the better random forest algorithm, the K-means clustering algorithm is used to continue to optimize the model, increasing the test set R² to 0.95 and decreasing the RMSE to 0.08 and 0.06. As a reliable machine algorithm, random forest can be used to predict the toxicity of the mixture of nano-metal oxides and heavy metals. The cluster analysis can effectively improve the stability and predictability of the model, and provide a new idea for the prediction of cytotoxicity model in the future.     

Thermodynamic Properties of Crystalline Cellulose Allomorphs Studied with Dispersion-Corrected Density Functional Methods

The phonon properties and thermodynamics of four crystalline cellulose allomorphs, Iα, Iβ, II, and III1, have been investigated using dispersion-corrected density functional theory (DFT). In line with experimental findings, the free energy differences between the studied cellulose allomorphs are small, less than 1 kJ/mol per atom. The calculated specific heat at constant volume (Cv) has been compared with the available experimental data in the temperature range 10–300 K. Quasiharmonic approximation has been employed to study thermodynamics and specific heat at constant pressure (Cp). For the studied temperature range of 10–400 K, the specific heat of all cellulose allomorphs shows very similar behavior. The calculated and experimental specific heat agree well at low temperatures below 100 K, but the deviation between theory and experiment increases with temperature. This may be due to increasing phonon anharmonicity as the temperature increases.     

A Hydrothermal Method to Generate Carbon Quantum Dots from Waste Bones and Their Detection of Laundry Powder

Surfactants are one of the major pollutants in laundry powder, which have an impact on the environment and human health. Carbon quantum dots (CQDs) are spherical zero-dimensional fluorescent nanoparticles with great potential for fluorescent probing, electrochemical biosensing and ion sensing. Herein, a bottom-up approach was developed for the synthesis of CQDs from biomass to detect laundry detergent and laundry powder. Waste chicken bones were used as carbon precursors after being dried, crushed and reacted with pure water at 180 °C for 4 h to generate CQDs, which exhibited a monodisperse quasi-spherical structure with an average particle size of 3.2 ± 0.2 nm. Functional groups, including -OH, C=O, C=C and C-O, were identified on the surface of the prepared CQDs. The optimal fluorescence excitation wavelength of the yellow-brown CQDs was 380 nm, with a corresponding emission peak at 465 nm. CQDs did not significantly increase cell death in multiple cell lines at concentrations of 200 µg·mL⁻¹. Fluorescence enhancement of CQDs was observed after addition of sodium dodecyl benzene sulphonate, a major anionic surfactant in laundry powder. A linear relationship between fluorescence enhancement CQDs and the concentration of laundry powder was established. Thus, a hydrothermal method was developed to generate CQDs from waste biomass that may be used as a fluorescent probe to detect laundry powder.     

Magnetic Torus Microreactor as a Novel Device for Sample Treatment via Solid-Phase Microextraction Coupled to Graphite Furnace Atomic Absorption Spectroscopy: A Route for Arsenic Pre-Concentration

This work studied the feasibility of using a novel microreactor based on torus geometry to carry out a sample pretreatment before its analysis by graphite furnace atomic absorption. The miniaturized retention of total arsenic was performed on the surface of a magnetic sorbent material consisting of 6 mg of magnetite (Fe₃O₄) confined in a very small space inside (20.1 µL) a polyacrylate device filling an internal lumen (inside space). Using this geometric design, a simulation theoretical study demonstrated a notable improvement in the analyte adsorption process on the solid extractant surface. Compared to single-layer geometries, the torus microreactor geometry brought on flow turbulence within the liquid along the curvatures inside the device channels, improving the efficiency of analyte–extractant contact and therefore leading to a high preconcentration factor. According to this design, the magnetic solid phase was held internally as a surface bed with the use of an 8 mm-diameter cylindric neodymium magnet, allowing the pass of a fixed volume of an arsenic aqueous standard solution. A preconcentration factor of up to 60 was found to reduce the typical “characteristic mass” (as sensitivity parameter) determined by direct measurement from 53.66 pg to 0.88 pg, showing an essential improvement in the arsenic signal sensitivity by absorption atomic spectrometry. This methodology emulates a miniaturized micro-solid-phase extraction system for flow-through water pretreatment samples in chemical analysis before coupling to techniques that employ reduced sample volumes, such as graphite furnace atomic absorption spectroscopy.     

Fabrication of Orange Fluorescent Boron-Doped Graphene Quantum Dots for Al3+ Ion Detection

Aluminum is a kind of metal that we often encounter. It can also be absorbed by the human body invisibly and will affect our bodies to a certain extent, e.g., by causing symptoms associated with Alzheimer’s disease. Therefore, the detection of aluminum is particularly important. The methods to detect metal ions include precipitation methods and electrochemical methods, which are cumbersome and costly. Fluorescence detection is a fast and sensitive method with a low cost and non-toxicity. Traditional fluorescent nanomaterials have a high cost, high toxicity, and cause harm to the human body. Graphene quantum dots are a new type of fluorescent nanomaterials with a low cost and non-toxicity that can compensate for the defects of traditional fluorescent nanomaterials. In this paper, c-GQDs and o-GQDs with good performance were prepared by a bottom-up hydrothermal method using o-phenylenediamine as a precursor and citric acid or boric acid as modulators. They have very good optical properties: o-GQDs exhibit orange fluorescence under UV irradiation, while c-GQDs exhibits cyan fluorescence. Then, different metal ions were used for ion detection, and it was found that Al³⁺ had a good quenching effect on the fluorescence of the o-GQDs. The reason for this phenomenon may be related to the strong binding of Al³⁺ ions to the N and O functional groups of the o-GQDs and the rapid chelation kinetics. During the chelation process, the separation of o-GQDs’ photoexcited electron hole pairs leads to their rapid electron transfer to Al³⁺, in turn leading to the occurrence of a fluorescence-quenching phenomenon. In addition, there was a good linear relationship between the concentration of the Al³⁺ ions and the fluorescence intensity, and the correlation coefficient of the linear regression equation was 0.9937. This illustrates the potential for the wide application of GQDs in sensing systems, while also demonstrating that Al³⁺ sensors can be used to detect Al³⁺ ions.     

Stabilizing Halogen-Bonded Complex between Metallic Anion and Iodide

Halogen bonds (XBs) between metal anions and halides have seldom been reported because metal anions are reactive for XB donors. The pyramidal-shaped Mn(CO)₅⁻ anion is a candidate metallic XB acceptor with a ligand-protected metal core that maintains the negative charge and an open site to accept XB donors. Herein, Mn(CO)₅⁻ is prepared by electrospray ionization, and its reaction with CH₃I in gas phase is studied using mass spectrometry and density functional theory (DFT) calculation. The product observed experimentally at m/z = 337 is assigned as [IMn(CO)₄(OCCH₃)]⁻, which is formed by successive nucleophilic substitution and reductive elimination, instead of the halogen-bonded complex (XC) CH₃−I···Mn(CO)₅⁻, because the I···Mn interaction is weak within XC and it could be a transient species. Inspiringly, DFT calculations predict that replacing CH₃I with CF₃I can strengthen the halogen bonding within the XC due to the electro-withdrawing ability of F. More importantly, in so doing, the nucleophilic substitution barrier can be raised significantly, ~30 kcal/mol, thus leaving the system trapping within the XC region. In brief, the combination of a passivating metal core and the introduction of an electro-withdrawing group to the halide can enable strong halogen bonding between metallic anion and iodide.     

Nearest-Neighbour and Non-Nearest-Neighbour Non-Covalent Interactions between Substituents in the Aromatic Systems: Experimental and Theoretical Investigation of Functionally Substituted Benzophenones

Benzophenone derivatives exhibit not only biological activity but also act as photo initiator and UV blocker. We carried out experimental and theoretical thermochemical studies of hydroxy- and methoxy-substituted benzophenones. Standard molar enthalpies of vaporisation were obtained from the temperature dependence of vapour pressures measured by the transpiration method. The thermodynamic data on phase transitions available in the literature (crystal–gas, crystal–liquid, and liquid–gas) were also collected and evaluated. High-level quantum chemical methods G3MP2 and G4 were used to estimate the standard molar enthalpies of formation of substituted benzophenones in the gas phase and establish agreement between experimental and theoretical results. The application of the “centrepiece” group-contribution approach to hydroxy- and methoxy-substituted benzophenones was demonstrated. A quantitative assessment of the hydrogen bond was carried out using various approaches based on experimental data and quantum chemical calculations.