Bioassay-guided isolation of human carboxylesterase 2 inhibitory and antioxidant constituents from Laportea bulbifera: Inhibition interactions and molecular mechanism

Laportea bulbifera (Sieb. et. Zucc.) Wedd has long been utilized in Traditional Chinese Medicines (TCM) for the treatment of rheumatoid arthritis. However, the study of systematic anti-inflammatory chemical constituents in L. bulbifera has never been reported. Thus, bioassay-guided isolation for its roots part led to 46 compounds, including 38 phenolic derivatives. Their structures were determined on the basis of ¹H and ¹³C NMR and MS spectra. All compounds were isolated from L. bulbifera for the first time except for 13 compounds. Most of the compounds showed good COX-2 inhibitory activity (IC₅₀: 0.13–3.94 μM) and DPPH radical-scavenging activity (IC₅₀: 1.57–9.55 μM). Four compounds (4, 17, 35, and 43) with different skeletons showed preferential COX-2 over COX-1 inhibition with selective indices ranging from 12 to 171. High content active compounds are important for elucidating the basis of the active substance of TCM. Compound 4 (COX-2, IC₅₀ 0.24 μM), a high content compound, represented one of the best selective COX-2 inhibitors. Another high content active compound (35) with a different skeleton might have different mechanism. Further study for the inhibition kinetics against COX-2 indicated compounds 4 and 35 were noncompetitive and competitive COX-2 inhibitors, respectively. Moreover, molecular docking and molecular dynamics simulation data further indicated that compound 4 could bind in the cavity of COX-2 and interacted with key residues VAL-538, PHE-142, and GLY-225 of COX-2 through hydrogen bonds. The results indicated that L. bulbifera roots could be applied as antioxidant and anti-inflammatory agents due to their potent selective COX-2 inhibitory and antioxidant activity of phenolic compounds.     

Numerical Investigation of Graphene as a Back Surface Field Layer on the Performance of Cadmium Telluride Solar Cell

This paper numerically explores the possibility of ultrathin layering and high efficiency of graphene as a back surface field (BSF) based on a CdTe solar cell by Personal computer one-dimensional (PC1D) simulation. CdTe solar cells have been characterized and studied by varying the carrier lifetime, doping concentration, thickness, and bandgap of the graphene layer. With simulation results, the highest short-circuit current (I_sc = 2.09 A), power conversion efficiency (η = 15%), and quantum efficiency (QE~85%) were achieved at a carrier lifetime of 1 × 10³ μs and a doping concentration of 1 × 10¹⁷ cm⁻³ of graphene as a BSF layer-based CdTe solar cell. The thickness of the graphene BSF layer (1 μm) was proven the ultrathin, optimal, and obtainable for the fabrication of high-performance CdTe solar cells, confirming the suitability of graphene material as a BSF. This simulation confirmed that a CdTe solar cell with the proposed graphene as the BSF layer might be highly efficient with optimized parameters for fabrication.     

Influence of Substitutional Defects in ZIF-8 Membranes on Reverse Osmosis Desalination: A Molecular Dynamics Study

In this study, molecular dynamics simulation is used to investigate the effects of water-based substitutional defects in zeolitic imidazolate frameworks (ZIF)-8 membranes on their reverse osmosis (RO) desalination performance. ZIF-8 unit cells containing up to three defect sites are used to construct the membranes. These substitutional defects can either be Zn defects or linker defects. The RO desalination performance of the membranes is assessed in terms of the water flux and ion rejection rate. The effects of defects on the interactions between the ZIF-8 membranes and NaCl are investigated and explained with respect to the radial distribution function (RDF) and ion density distribution. The results show that ion adsorption on the membranes occurs at either the nitrogen atoms or the defect sites. Complete NaCl rejection can be achieved by introducing defects to change the size of the pores. It has also been discovered that the presence of linker defects increases membrane hydrophilicity. Overall, molecular dynamics simulations have been used in this study to show that water-based substitutional defects in a ZIF-8 structure reduce the water flux and influence its hydrophilicity and ion adsorption performance, which is useful in predicting the type and number of defect sites per unit cell required for RO applications. Of the seven ZIF-8 structures tested, pristine ZIF-8 exhibits the best RO desalination performance.     

How to Predict Excited State Geometry by Using Empirical Parameters Obtained from Franck-Condon Analysis of Optical Spectrum

Excited state geometries of molecules can be calculated with highly reliable wavefunction schemes. Most of such schemes, however, are applicable to small molecules and can hardly be viewed as error-free for excited state geometries. In this study, a theoretical approach is presented in which the excited state geometries of molecules can be predicted by using vibrationally resolved experimental absorption spectrum in combination with the theoretical modelling of vibrational pattern based on Franck-Condon approximation. Huang-Rhys factors have been empirically determined and used as input for revealing the structural changes occurring between the ground and the excited state geometries upon photoexcitation. Naphthalene molecule has been chosen as a test case to show the robustness of the proposed theoretical approach. Predicted 1B_2u excited state geometry of the naphthalene has similar but slightly different bond length alternation pattern when compared with the geometries calculated with CIS, B3LYP, and CC2 methods. Excited state geometries of perylene and pyrene molecules are also determined with the presented theoretical approach. This powerful method can be applied to other molecules and specifically to relatively large molecules rather easily as long as vibrationally resolved experimental spectra are available to use.     

Structure-based virtual screening of dipeptidyl peptidase 4 inhibitors and their in vitro analysis

Type 2 diabetes mellitus (T2DM) is one of the most widely prevalent metabolic disorders with no cure to date thus remains the most challenging task in the current drug discovery. Therefore, the only strategy to control diabetes prevalence is to develop novel efficacious therapeutics. Dipeptidyl Peptidase 4 (DPP-4) inhibitors are currently used as anti-diabetic drugs for the inhibition of incretins. This study aims to construct the chemical feature based on pharmacophore models for dipeptidyl peptidase IV. The structure-based pharmacophore modeling has been employed to evaluate new inhibitors of DPP-4. A four-featured pharmacophore model was developed from crystal structure of DPP-4 enzyme with 4-(2-aminoethyl) benzenesulfonyl fluoride in its active site via pharmacophore constructing tool of Molecular Operating Environment (MOE) consisting F1 Hyd (hydrophobic region), F2 Hyd|Cat|Don (hydrophobic cationic and donor region), F3 Acc (acceptor region) and F4 Hyd (hydrophobic region). The generated pharmacophore model was used for virtual screening of in-house compound library (the available compounds which were used for initial screening to get the few compounds for the current studies). The resultant selected compounds, after virtual screening were further validated using in vitro assay. Furthermore, structure-activity relationship was carried out for the compounds possessing significant inhibition potential after docking studies. The binding free energy of analogs was evaluated via molecular mechanics generalized Born surface area (MM-GBSA) and Poisson-Boltzmann surface area (MM-PBSA) methods using AMBER 16 as a molecular dynamics (MD) simulation package. Based on potential findings, we report that selected candidates are more likely to be used as DPP-4 inhibitors or as starting leads for the development of novel and potent DPP-4 inhibitors.     

Identification of Potential SARS-CoV-2 Main Protease and Spike Protein Inhibitors from the Genus Aloe: An In Silico Study for Drug Development

Severe acute respiratory syndrome coronavirus (SARS-CoV-2) disease is a global rapidly spreading virus showing very high rates of complications and mortality. Till now, there is no effective specific treatment for the disease. Aloe is a rich source of isolated phytoconstituents that have an enormous range of biological activities. Since there are no available experimental techniques to examine these compounds for antiviral activity against SARS-CoV-2, we employed an in silico approach involving molecular docking, dynamics simulation, and binding free energy calculation using SARS-CoV-2 essential proteins as main protease and spike protein to identify lead compounds from Aloe that may help in novel drug discovery. Results retrieved from docking and molecular dynamics simulation suggested a number of promising inhibitors from Aloe. Root mean square deviation (RMSD) and root mean square fluctuation (RMSF) calculations indicated that compounds 132, 134, and 159 were the best scoring compounds against main protease, while compounds 115, 120, and 131 were the best scoring ones against spike glycoprotein. Compounds 120 and 131 were able to achieve significant stability and binding free energies during molecular dynamics simulation. In addition, the highest scoring compounds were investigated for their pharmacokinetic properties and drug-likeness. The Aloe compounds are promising active phytoconstituents for drug development for SARS-CoV-2.     

A New Approach for Controlling Mesoporosity in Activated Carbon by the Consecutive Process of Air Oxidation,Thermal Destruction of Surface Functional Groups,and Carbon Activation (the OTA Method)

A new and simple method, based entirely on a physical approach, was proposed to produce activated carbon from longan fruit seed with controlled mesoporosity. This method, referred to as the OTA, consisted of three consecutive steps of (1) air oxidation of initial microporous activated carbon of about 30% char burn-off to introduce oxygen surface functional groups, (2) the thermal destruction of the functional groups by heating the oxidized carbon in a nitrogen atmosphere at a high temperature to increase the surface reactivity due to increased surface defects by bond disruption, and (3) the final reactivation of the resulting carbon in carbon dioxide. The formation of mesopores was achieved through the enlargement of the original micropores after heat treatment via the CO₂ gasification, and at the same time new micropores were also produced, resulting in a larger increase in the percentage of mesopore volume and the total specific surface area, in comparison with the production of activated carbon by the conventional two-step activation method using the same activation time and temperature. For the activation temperatures of 850 and 900 °C and the activation time of up to 240 min, it was found that the porous properties of activated carbon increased with the increase in activation time and temperature for both preparation methods. A maximum volume of mesopores of 0.474 cm³/g, which accounts for 44.1% of the total pore volume, and a maximum BET surface area of 1773 m²/g was achieved using three cycles of the OTA method at the activation temperature of 850 °C and 60 min activation time for each preparation cycle. The two-step activation method yielded activated carbon with a maximum mesopore volume of 0.270 cm³/g (33.0% of total pore volume) and surface area of 1499 m²/g when the activation temperature of 900 °C and a comparable activation time of 240 min were employed. Production of activated carbon by the OTA method is superior to the two-step activation method for better and more precise control of mesopore development.     

The evolution of numerical methods for predicting the distribution of surfactant in the bubble-scale dynamics of foams

Many numerical methods now exist to simulate the structure and dynamics of surface-tension-dominated aqueous foams at the level of the individual films and the liquid structures where they meet. We review these methods, focusing in particular on bubble-scale simulations of foam rheology. We highlight methods that allow the distribution of surfactant during flow to be taken into account.     

Combined Experimental and Theoretical Insights into the Corrosion Inhibition Activity on Carbon Steel Iron of Phosphonic Acids

The inhibition effect of N,N′-phosphonomethylglycine (PMG) and vinyl phosphonic acid (VPA) on the 3% NaCl acidic solution corrosion of carbon steel iron was studied at different immersion times by potentiodynamic polarization, electrochemical impedance spectroscopy, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, and computational methods. It is found from the polarization studies that PMG and VPA behave as mixed-type inhibitors in NaCl. Values of charge transfer resistance (R_ct) and double layer capacitance (C_dl) in the absence and presence of inhibitors are determined. The PMG and VPA inhibitors were capable of inhibiting the corrosion process up to ≈91% and ≈85%, respectively. In the presence of PMG, the synergic effect of chlorine ions was observed. Density functional theory (DFT) was engaged to establish the adsorption site of PMG, VPA, and their deprotonated states. For studied compounds, the resulted values of E_LUMO, E_HOMO, energy gap (∆E), dipole moment (μ), electronic hardness (η), global softness (σ), electrophilic index (ω), and the electronic potential map are in concordance with the experimental data results regarding their corrosion inhibition behavior and adsorption on the metal surface.     

物理化学混合式教学设计与实践——以“单组分系统相变热力学”为例*

以“单组分系统相变热力学”为例介绍了物理化学混合式教学设计与教学实践。围绕课程教学目标,在课前、课中、课后的每一个教学环节中践行课程教学理念,通过“问题+案例”方式突出物理化学基本方法的应用性、普适性与前沿性,让学生在教学过程中获取原理、体验探究、发展思维、生成智慧。教学评价结果显示,绝大部分学生对混合式教学模式给予了积极的评价。