Density function theory calculation to study the oxidation potential of electron-donating compounds; affirming the oxidation mechanism by NICS calculations.

The manuscript describes a method for understanding the correlation of structural features and first oxidation potentials [Formula: see text] of electron-donating compounds (EDCs) with tetrathiafulvalene (TTF), dithiadiazafulvalenes (DTDAF), and tetraazafulvalene (TAF) frameworks. The density functional theory (DFT) procedure at B3LYP (6-31 + g(d)) was used for geometric optimization, given the large dimensions of the molecules studied, and their high structural similarity. First of all, the correlation between the oxidation potential and the highest occupied molecular orbital (HOMO) energy level as an effective quantum chemical descriptor was examined. Then, nucleus-independent chemical shifts (NICSs) calculation was applied to affirm the oxidation mechanism and interpret the effect of replacing the sulfur atoms by nitrogen, on the oxidation process. Finally, a more comprehensive investigation of structural features that affect the oxidation potential, topological, geometrical, constitutional, as well as, electrostatic, charged partial surface area, quantum-chemical, molecular orbital, and thermodynamic descriptors was calculated. A predictive model was developed based on the genetic algorithm multivariate linear regression (GA-MLR). There was an outstanding agreement between the theoretical and the experimental values obtained for the first oxidation potentials of the test set (Q2Ext = 0.981).

An Urgent Industrial Scheme Both for Total Synthesis, and for Pharmaceutical Analytical Analysis of Umifenovir as an Anti-viral API for Treatment of COVID-19.

BACKGROUND: This paper aims to reveal an urgent industrial scheme for a fast and facile total synthesis of umifenovir (arbidol) (by one-pot stages) as an antiviral agent for treating the 2019-nCoV virus via inhibiting its viral replication in the human cells. As COVID-19 takes thousands of lives all around the world, it seems that the medicinal resources would not be enough to supply billions of peoples currently living on the planet. Thus, this pandemic and its subsequent impacts on the natural order of our life would be one of the most important threats against the entire human race. METHODS: In this project, we have made attempts to find an operative approach for synthesizing this compound as an active pharmaceutical ingredient (API), which showed it could be effective in inhibiting the newly emerged coronavirus.. RESULTS: The designed scheme uses relatively cheap precursors and contains one pot stage instead of seven time-consuming and more costly linear steps. Moreover, safe and cheap solvents have been used like water and ethanol, instead of toxic ones like methanol and pyridine which could cause rejection of the API in the organic volatile impurities (OVI) test of pharmacopeia analysis, as well as increase the concern of inflammability, explosivity, and carcinogenic properties of those common solvents. CONCLUSION: The most important pharmaceutical analytical methods containing OVI test (mainly ethanol (about 171 ppm) much lower than the limits, by gas chromatography-Flame Ionization Detector (GC-FID) instrument), assay content (about 99.6% by potentiometric titration), and related purity analysis (by high-performance liquid chromatography-Ultraviolet Detector (HPLCUV)) (about 99.8%) were performed and described to give a more clear industrial scheme.

Determination of Cholesterol and its Derivatives in Nanoliposomes as Drug Delivery Conveyances by HPLC-UV: A Simple, Accurate and Cost-Effective Method Development and Validation Approach.

Nanoliposomes are extensively used as ideal vehicles in drug delivery systems due to their unique biocompatibility and biodegradability properties. They can be used as sustained release and target selective conveyances to deliver the encapsulated drugs at specific cells or tissues by improving their efficacy along with reducing the side effects. As an analytical perspective, the determination of various lipid components in the final formulation is one of the practical issues while the agents are applied in an industrial-scale. Herein, the maximum ultra violet (UV) absorbances for the most of the lipids are within 200-210 nm that cause significant cut-off conflicts with the general solvents or additives of high-performance liquid chromatography (HPLC) during its method development procedure. In this study, a simple, accurate and cost-effective isocratic HPLC-UV method has been successfully developed for the simultaneous determination of α-(3-O-cholesteryloxy)-δ-(N-ethylmorpholine)-succineamide (MoChol), cholesteryl-hemisuccinate (Chems) and Cholesterol in nanoliposomes drug carriers containing an active pharmaceutical ingredient (anti-BCL-2 DNA oligonucleotide). The isocratic mobile phase consisted of ethanol/acetonitrile/water including trifluoroacetic acid (60/30/10 with 0.1% v/v, respectively) at a flow rate of 1.0 mL min-1 was run through a commercial reverse-phase C18 analytical column while UV detector was set at 202 nm. To confirm the applicability, a full validation of the proposed method was performed according to the International Council for Harmonization (ICH) guidelines.

Mixed hemimicelles solid-phase extraction based on sodium dodecyl sulfate (SDS)-coated nano-magnets for the spectrophotometric determination of Fingolomid in biological fluids.

In this study, mixed hemimicelles solid-phase extraction (SPE) based on sodium dodecyl sulfate (SDS)-coated nano-magnets Fe3O4 was investigated as a novel method for the separation and determination of Fingolimod (FLM) in water, urine and plasma samples prior to spectrophotometeric determination. Due to the high surface area of these new sorbents and the excellent adsorption capacity after surface modification by SDS, satisfactory extraction recoveries can be produced. The main factors affecting the adsolubilization of analysts, such as pH, surfactant and adsorbent amounts, ionic strength, extraction time and desorption conditions were studied and optimized. Under the selected conditions, FLM has been quantitatively extracted. The accuracy of the method was evaluated by recovery measurements on spiked samples, and good recoveries of 96%, 95% and 88% were observed for water, urine and plasma respectively. Proper linear behaviors over the investigated concentration ranges of 2-26, 2-17 and 2-13 mg/L with good coefficients of determination, 0.998, 0.997 and 0.995 were achieved for water, urine and plasma samples, respectively. To the best of our knowledge, this is the first time that a mixed hemimicelles SPE method based on magnetic separation and nanoparticles has been used as a simple and sensitive method for monitoring of FLM in water and biological samples.

Release of quercetin from micellar nanoparticles with saturated and unsaturated core forming polyesters--a combined computational and experimental study.

Computational and experimental studies were combined to obtain new insight into the widely reported anomalous release mechanism of hydrophobic drug (quercetin) from polymeric micellar nanoparticles. Saturated and unsaturated amphiphilic triblock copolymers from monomethoxy polyethylene glycol (mPEG), poly(butylene adipate) (PBA) and poly(cis-2-butene adipate) (PCBA) (mPEG-PBA-mPEG and mPEG-PCBA-mPEG) were utilized as model polymers to specify the contribution of polymer-micelle degradation and polymer-drug interactions on the observed differences in the release rates by applicable computational investigation and experimental evaluations. Monitoring the size of the micelles through the releasing process together with hydrolytic degradation studies of the core forming polymers proved that the contribution of polymer hydrolysis and micelle degradation on the observed differences in the release rates during the release time window was minimal. The compatibility between quercetin and the core forming polymer is another factor influencing the drug encapsulation and the relative release rate and it was therefore investigated theoretically (using density functional theory (DFT) at B3LYP/6-311(++)G level of theory) and experimentally (FT-IR imaging). The drug-polymer interactions in the core were shown to be much more important than the polymer and/or micelle swelling-dissociation-degradation processes under the studied conditions.

Highlighting and trying to overcome a serious drawback with QSPR studies; data collection in different experimental conditions (mixed-QSPR).

The experimental conditions in quantitative structure-property relationship (QSPR) studies need to be the same for each dataset in case one wishes to relate the property, only to the structure. This major drawback limits QSPR studies due to two reasons: (1) Gathering of physicochemical data obtained under the same experimental condition is difficult. (2) The obtained model is just useful to predict the physicochemical properties under the specific experimental condition. In this article, we report an attempt to highlight the shortcoming of QSPR studies for a property that was measured under different experimental conditions. In addition, we reveal inadequacies that correlating the fluorescence properties and the descriptor of the solvent has. These defects are eventually removed by taking into account the solvent-solute interactions in descriptor calculations. Quantum chemical calculations (HF/6-31G*) were carried out to optimize geometry and calculate the structural descriptors. The genetic algorithm combined with multiple linear regression method was utilized to construct the linear QSPR models. Because of the better nonlinear relationship between the quantum yield of fluorescence and structural descriptors in comparison with those of a linear relationship, support vector machine was used to construct the nonlinear QSPR model. Result analyses demonstrated that the proposed models meet our goal.

Simultaneous spectrophotometric determination of 2-thiouracil and 2-mercaptobenzimidazole in animal tissue using multivariate calibration methods: concerns and rapid methods for detection.

Two multivariate calibration methods, partial least squares (PLS) and principal component regression (PCR), were applied to the spectrophotometric simultaneous determination of 2-mercaptobenzimidazole (MB) and 2-thiouracil (TU). A genetic algorithm (GA) using partial least squares was successfully utilized as a variable selection method. The concentration model was based on the absorption spectra in the range of 200 to 350 nm for 25 different mixtures of MB and TU. The calibration curve was linear across the concentration range of 1 to 10 microg mL(-1) and 1.5 to 15 microg mL(-1) for MB and TU, respectively. The values of the root mean squares error of prediction (RMSEP) were 0.3984, 0.1066, and 0.0713 for MB and 0.2010, 0.1667, and 0.1115 for TU, which were obtained using PCR, PLS, and GA-PLS, respectively. Finally, the practical applicability of the GA-PLS method was effectively evaluated by the concurrent detection of both analytes in animal tissues. It should also be mentioned that the proposed method is a simple and rapid way that requires no preliminary separation steps and can be used easily for the analysis of these compounds, especially in quality control laboratories.

Quantum chemical calculations to reveal the relationship between the chemical structure and the fluorescence characteristics of phenylquinolinylethynes and phenylisoquinolinylethynes derivatives, and to predict their relative fluorescence intensity.

In this paper the relationship between the chemical structure and fluorescence characteristics of 30 phenylquinolinylethyne (PhQE), and phenylisoquinolinylethyne (PhIE) derivatives compounds employing ab initio calculations have been elucidated. Quantum chemical calculations (6-31G) were carried out to obtain: the optimized geometry, energy levels, charges and dipole moments of these compounds, in the singlet (steady and excited states) and triplet states. The relationship between quantum chemical descriptors, and wavelength of maximum excitation and emission indicated that these two parameters have the most correlation with quantum chemical hardness (eta). Also, stokes shift has the most correlation with the square of difference between the maximum of positive charges in the singlet steady and singlet excited states. The quantitative structure-property relationship (QSPR) of PhQE and PhIE was studied for relative fluorescence intensity (RFI). The genetic algorithm (GA) was applied to select the variables that resulted in the best-fit models. After the variable selection, multiple linear regression (MLR) and support vector machine (SVM) were both utilized to construct linear and non-linear QSPR models, respectively. The SVM model demonstrated a better performance than that of the MLR model. The route mean square error (RMSE) in the training and the test sets for the SVM model was 0.195 and 0.324, and the correlation coefficients were 0.965 and 0.960, respectively, thus revealing the reliability of this model. The resulting data indicated that SVM could be used as a powerful modeling tool for QSPR studies. According to the best of our knowledge, this is the first research on QSPR studies to predict RFI for a series of PhQE and PhIE derivative compounds using SVM.

Quantitation of atorvastatin in human plasma using directly suspended acceptor droplet in liquid-liquid-liquid microextraction and high-performance liquid chromatography-ultraviolet detection.

A simple and sensitive methodology based on liquid-liquid-liquid microextraction (LLLME) followed by high-performance liquid chromatography-ultraviolet detection (HPLC-UV) has been successfully developed for the determination of atorvastatin (AT) in human plasma. AT was first extracted from 4.5 mL acidic aqueous sample (diluted plasma, donor phase, pH 1) at temperature 45 degrees C through 400 microL 1-octanol for 4.5 min, while being agitated by a stirring bar at 1250 rpm. Then, a 5.5 microL free suspended basic aqueous droplet (acceptor phase, pH 10) was delivered to the top-center position of the organic membrane. The mixture was stirred at 650 rpm for 7.5 min and the analyte was back-extracted into the droplet. Finally, the acceptor phase was taken into a microsyringe and injected directly into the HPLC. An enrichment factor of 187 along with substantial sample clean up was obtained under the optimized conditions. The calibration curve showed linearity in the range of 1-500 ng mL(-1) with regression coefficient corresponding to 0.996. Limits of detection (S/N=3) and quantification (S/N=10) were 0.4 and 1 ng mL(-1), respectively. A reasonable relative recovery (91%) and satisfactory intra-assay (4.4-7.0%, n=6) and inter-assay (4.9-7.7%, n=8) precision illustrated good performance of the analytical procedure. This technique was eventually applied for the determination of AT in human plasma after oral administration of 40 mg single dose of drug. The protocol proved to be highly cost-effective and reliable for the screening purpose.

A novel QSPR study of normalized migration time for drugs in capillary electrophoresis by new descriptors: quantum chemical investigation.

Some drugs' migration time (MT) has been studied employing quantitative structure-property relationship using new descriptors that are able to predict MT value with high accuracy. MT property modeling of the drugs was established as a function of the new theoretically derived descriptors applying multiple linear regressions and partial least-squares regression. The genetic algorithm was used to select those variables that resulted in the best-fitted models. To select a set of descriptors that are most relevant to MT, illustrating the affecting degree for the affinity of different descriptors, the linear models with 1-14 variables were constructed and were then investigated based on F-value, squared regression coefficients of cross-validated (Q2), adjusted R2 (R2adj) and standard error of estimate (S) statistical parameters. Finally, the best model with ten variables was selected. Statistical parameters of the test set, such as standard deviation error in test, were 0.559 and 0.616, while relative error of test was equal to 7.648 and 8.497% for multiple linear regressions and partial least-squares models, respectively, confirming the good predictive ability of the model. Since the capillary lengths were not the same for the drugs in the data set, MT values were normalized based on a specific capillary before modeling, which is also one of the advantages of this method, enabling us to use the model for different capillary lengths.