Design,Synthesis, Docking,DFT, MD Simulation Studies of a New Nicotinamide-Based Derivative: In Vitro Anticancer and VEGFR-2 Inhibitory Effects

A nicotinamide-based derivative was designed as an antiproliferative VEGFR-2 inhibitor with the key pharmacophoric features needed to interact with the VEGFR-2 catalytic pocket. The ability of the designed congener ((E)-N-(4-(1-(2-(4-benzamidobenzoyl)hydrazono)ethyl)phenyl)nicotinamide), compound 10, to bind with the VEGFR-2 enzyme was demonstrated by molecular docking studies. Furthermore, six various MD simulations studies established the excellent binding of compound 10 with VEGFR-2 over 100 ns, exhibiting optimum dynamics. MM-GBSA confirmed the proper binding with a total exact binding energy of −38.36 Kcal/Mol. MM-GBSA studies also revealed the crucial amino acids in the binding through the free binding energy decomposition and declared the interactions variation of compound 10 inside VEGFR-2 via the Protein–Ligand Interaction Profiler (PLIP). Being new, its molecular structure was optimized by DFT. The DFT studies also confirmed the binding mode of compound 10 with the VEGFR-2. ADMET (in silico) profiling indicated the examined compound’s acceptable range of drug-likeness. The designed compound was synthesized through the condensation of N-(4-(hydrazinecarbonyl)phenyl)benzamide with N-(4-acetylphenyl)nicotinamide, where the carbonyl group has been replaced by an imine group. The in-vitro studies were consonant with the obtained in silico results as compound 10 prohibited VEGFR-2 with an IC₅₀ value of 51 nM. Compound 10 also showed antiproliferative effects against MCF-7 and HCT 116 cancer cell lines with IC₅₀ values of 8.25 and 6.48 μM, revealing magnificent selectivity indexes of 12.89 and 16.41, respectively.     

Genetically Encoded Ratiometric RNA‐Based Sensors for Quantitative Imaging of Small Molecules in Living Cells

Precisely determining the intracellular concentrations of metabolites and signaling molecules is critical in studying cell biology. Fluorogenic RNA‐based sensors have emerged to detect various targets in living cells. However, it is still challenging to apply these genetically encoded sensors to quantify the cellular concentrations and distributions of targets. Herein, using a pair of orthogonal fluorogenic RNA aptamers, DNB and Broccoli, we engineered a modular sensor system to apply the DNB‐to‐Broccoli fluorescence ratio to quantify the cell‐to‐cell variations of target concentrations. These ratiometric sensors can be broadly applied for live‐cell imaging and quantification of metabolites, signaling molecules, and other synthetic compounds.     

Multicolor low‐rank preconditioner for general sparse linear systems

This article presents a multilevel parallel preconditioning technique for solving general large sparse linear systems of equations. Subdomain coloring is invoked to reorder the coefficient matrix by multicoloring the adjacency graph of the subdomains, resulting in a two‐level block diagonal structure. A full binary tree structure $\mathrm{??}$ is then built to facilitate the construction of the preconditioner. A key property that is exploited is the observation that the difference between the inverse of the original matrix and that of its block diagonal approximation is often well approximated by a low‐rank matrix. This property and the block diagonal structure of the reordered matrix lead to a multicolor low‐rank (MCLR) preconditioner. The construction procedure of the MCLR preconditioner follows a bottom‐up traversal of the tree $\mathrm{??}$. All irregular matrix computations, such as ILU factorizations and related triangular solves, are restricted to leaf nodes where these operations can be performed independently. Computations in nonleaf nodes only involve easy‐to‐optimize dense matrix operations. In order to further reduce the number of iteration of the Preconditioned Krylov subspace procedure, we combine MCLR with a few classical block‐relaxation techniques. Numerical experiments on various test problems are proposed to illustrate the robustness and efficiency of the proposed approach for solving large sparse symmetric and nonsymmetric linear systems.     

Phenolic content and antioxidant properties of seeds from different grape cultivars grown in Iran

This study investigated the antioxidant activity and phenolic composition of seed extracts from three grape cultivars grown in Iran. Folin Ciocalteu method was used for the determination of the total phenolic contents and GC–MS was used for the analysis of phenolic compositions. 1,1-diphenyl-2-picrylhydrazyl (DPPH) method was used to evaluate the antioxidant activity. The highest and the lowest total phenolic contents of seed extract were found in the black and green grape, respectively. The content of individual phenols such as Frulic acid, Gentistic acid, Syringic acid, (+) Catechin, Chlorogenic acid and (?)- Epicatchin gallate was cultivars dependent. The antioxidant activity of the seed extracts ranged from 34.03% (Green) to 53.63% (Black). Generally, the Black grape seed extract with the total phenolic content (3 ± 0.01 mg tannic acid/g DM), DPPH (53.63 ± 0.34%), IC₅₀ and AEAC (7.41 and 16.92 mg/mL) showed the highest level of total antioxidant capacity.     

Electrochemical Oxidation of Nortriptyline and Its Voltammetric Sensing at a Carbon Ionic Liquid Electrode

The electrochemical oxidation of nortriptyline at a carbon ionic liquid electrode (CILE) was investigated. Nortriptyline is electrochemically inactive on conventional electrodes but CILE exhibited excellent electrocatalytic activity toward oxidation of nortriptyline with the well-defined anodic peak at 860 mV. This characteristic was attributed to the outstanding conductivity and electrocatalytic effect of the ionic liquid, 1-octylpyridinum hexaflourophosphate, used as a binder in the construction of the electrode. The influence of experimental parameters such as pH and sweep rate was also studied. The quantitative determination of nortriptyline was performed using differential pulse voltammetry technique. Under selected conditions the anodic peak current was linear to nortriptyline concentration in the ranges of 4.8 × 10^–6 to 2.4 × 10^–5 M and 2.4 × 10^–5 to 6.4 × 10^–5 M, with correlation coefficients of 0.9992 and 09949, respectively. The detection limit was 3 × 10^–7 M.     

Preparation of PMMA/mesoporous diatomite nanocomposites by in situ SR&;NI ATRP

The catalytic effect of lead oxide nano- and microparticles (PbO) on the thermal behavior and decomposition kinetics of energetic formulations composed of nitrocellulose (NC), triethyleneglycol dinitrate (TEGDN) and diaminoglyoxime (DAG) was investigated by simultaneous thermogravimetric analysis and differential scanning calorimetry. The results show that lead oxide nano- and microparticles could significantly alter thermal pattern of the studied energetic compositions. The effect of lead oxide content on thermal behavior of energetic compositions was also studied, and the results revealed that addition of different amounts of lead oxide caused to shift in the DSC peaks. Moreover, the catalyst decreases activation energy of the decomposition stage of energetic composition at about 20–40 kJ mol^?1. However, the catalyst enhances decomposition temperature of TEGDN/NC/DAG energetic compositions. By the aid of DSC data resulted by non-isothermal methods, the thermokinetic parameters such as activation energy (E _a), frequency factor (A), the critical ignition temperature of thermal explosion, the self-accelerating decomposition temperature (T _SADT) and also thermodynamic parameters of the studied energetic compositions were calculated and compared.     

Prediction of coefficients of the Langmuir adsorption isotherm using various artificial intelligence (AI) techniques

Adsorption is a process that utilizes porous solid materials to separate some solutes from gas or liquid mixtures. The extent of this separation is often determined using the adsorption isotherms, i.e., semi-empirical correlation for relating the amount of adsorbed substances by the solid medium to its associated concentration in fluid phase at constant temperature. Prior to employing an adsorption isotherm, its coefficients should be adjusted using experimental data of a considered adsorption system. In this study, the coefficients of Langmuir model have been predicted using various types of artificial neural networks (ANNs), support vector machines, and adaptive neuro fuzzy interface systems, and coupled scheme of ANN-genetic algorithm. The employed ANN types are multi-layer perceptron neural network (MLPNN), radial basis function neural network, cascade feedforward neural network, and generalized neural network. The considered coefficients tried to be modeled as functions of temperature, pH, adsorbent density, and adsorbate molecular weight. Predictive accuracies of the AI techniques have been compared utilizing different statistical indices such as correlation coefficient (R²), mean square error, and absolute average relative deviation (AARD%). The results indicated that MLPNN was the most accurate model for predicting the coefficients of Langmuir isotherm, due to its AARDs of 24.64 and 22.40% for the first and second coefficients, respectively.     

Interpretation of water isotherm hysteresis for an activated charcoal using stochastic pore networks

Water vapor adsorption equilibria on activated carbons typically exhibit hysteresis. The size and shape of the hysteresis loop which separates the adsorption and desorption branches is a strong function of the pore size and interconnectivity of the pores. Neither conventional pore filling models nor statistical thermodynamics approaches provide a means for predicting the extent of hysteresis from only adsorption measurements. This work uses the Kelvin Equation in conjunction with the structural concept of a stochastic pore network to describe measured water isotherms on BPL carbon. Using a pore segment distribution function determined from the adsorption branch, it is shown that totally random assemblies underestimate the extent of hysteresis. It is possible, however, to closely fit the measured BPL-water hysteresis loop using a patchy heterogeneity in which a proportion of the larger pores are preferentially located on the exterior, mid-range pores are concentrated in a sub-surface layer and some large pores form shielded voids behind much smaller pores.Nomenclature p vapor phase partial pressure of sorbate - p _sat saturation vapor pressure of sorbate - R gas constant - r pore radius - T absolute temperature - t adsorbed layer thickness - V _L molar volume of adsorbed phase - surface tension - contact angle