Analysis of pharmacokinetic profile and ecotoxicological character of cefepime and its photodegradation products.

An important problem is the impact of photodegradation on product toxicity in biological tests, which may be complex and context-dependent. Previous studies have described the pharmacology of cefepime, but the toxicological effects of its photodegradation products remain largely unknown. Therefore, photodegradation studies were undertaken in conditions similar to those occurring in biological systems insilico, in vitro, in vivo and ecotoxicological experiments. The structures of four cefepime photodegradation products were determined by UPLC-MS/MS method. The calculated in silico ADMET profile indicates that carcinogenic potential is expected for compounds CP-1, cefepime, CP-2 and CP-3. The Cell Line Cytomotovity Predictor 2.0 tool was used to predict the cytotoxic effects of cefepime and related compounds in non-transformed and cancer cell lines. The results indicate that possible actions include: non-small cell lung cancer, breast adenocarcinoma, prostate cancer and papillary renal cell carcinoma. OPERA models were used to predict absorption, distribution, metabolism and excretion (ADME) endpoints, and potential bioactivity of CP-2, cefepime and CP-4. The results obtained in silico show that after 96h of exposure, cefepime, CP-1, CP-2, and CP-3 are moderately toxic in the zebrafish model, while CP-4 is highly toxic. On the contrary, cefepime is more toxic to T. platyurus (highly toxic) compared to the zebrafish model, similar to products CP-4, CP-3 and CP-2. In vitro cytotoxicity studies were performed by MTT assay and in vivo acute embryo toxicity studies using Danio rerio embryos and larvae. In vitro showed an increase in the cytotoxicity of products with the longest exposure period i.e. for 8 h. Additionally, at a concentration of 200 µg/mL, statistically significant changes in metabolic activity were observed depending on the irradiation time. In vivo studies conducted with Zebrafish showed that both cefepime and its photodegradation products have only low toxicity. Assessment of potential ecotoxicity included Microbiotests on invertebrates (Thamnotoxkit F and Daphtoxkit F), and luminescence inhibition tests (LumiMara). The observed toxicity of the tested solutions towards both Thamnocephalus platyurus and Daphnia magna indicates that the parent substance (unexposed) has lower toxicity, which increases during irradiation. The acute toxicity (Lumi Mara) of nonirradiated cefepime solution is low for all tested strains (<10%), but mixtures of cefepime and its photoproducts showed growth inhibition against all tested strains (except #6, Photobacterium phoreum). Generally, it can be concluded that after UV-Vis irradiation, the mixture of cefepime phototransformation products shows a significant increase in toxicity.

A comparative study of the predictive performance of different descriptor calculation tools: Molecular-based elution order modeling and interpretation of retention mechanism for isomeric compounds from METLIN database.

In the pharmaceutical industry, the need for analytical standards is a bottleneck for comprehensive evaluation and quality control of intermediate and end products. These are complex mixtures containing structurally related molecules. In this regard, chromatographic peak annotation, especially for critical pairs of isomers and closest structural analogs, can be supported by using a Quantitative Structure Retention Relationship (QSRR) approach. In our study, we investigated the fundamental basis of the reversed-phase (RP) retention mechanism for 1141 isomeric compounds from the METLIN SMRT dataset. Nine different descriptor calculation tools combined with different feature selection methods (genetic algorithm (GA), stepwise, Boruta) and machine learning (ML) approaches (support vector machine (SVM), multiple linear regression (MLR), random forest (RF), XGBoost) were applied to provide a reliable molecular structure-based interpretation of RP retention behaviour of the isomeric compounds. Strict internal and external validation metrics were used to select models with the best predictive capabilities (rtest > 0.73, order of elution > 60 %). For the developed models, mean absolute errors were in the range of 60 to 110 s. Stepwise and GA showed the most suitable performance as descriptor selection methods, while SVM and XGBoost modeling gave satisfactory predictive characteristics in most cases. Validation performed on the published experimental data for structurally related pharmaceutical compounds confirmed the best accuracy of MLR modeling in combination with GA feature selection of general physico-chemical properties. The resulting models will be useful for the prediction of separation and identification of structurally related compounds in pharmaceutical analysis, providing a simultaneous understanding of the interaction mechanisms leading to their retention under RP conditions.

Isolation of Garlic Bioactives by Pressurized Liquid and Subcritical Water Extraction.

Garlic (Allium sativum L.) is widely used in various food products and traditional medicine. Besides unique taste and flavour, it is well known for its chemical profile and bioactive potential. The aim of this study was to apply subcritical water extraction (SWE) and pressurized liquid extraction (PLE) for the extraction of bioactive compounds from the Ranco genotype of garlic. Moreover, PLE process was optimized using response surface methodology (RSM) in order to determine effects and optimize ethanol concentration (45-75%), number of cycles (1-3), extraction time (1-3 min) and temperature (70-110 °C) for maximized total phenols content (TP) and antioxidant activity evaluated by various in vitro assays. Furthermore, temperature effect in SWE process on all responses was evaluated, while allicin content (AC), as a major organosulphur compound, was determined in all samples. Results indicated that PLE provided tremendous advantage over SWE in terms of improved yield and antioxidant activity of garlic extracts. Therefore, high-pressure processes could be used as clean and green procedures for the isolation of garlic bioactives.

The evaluation of drug-plasma protein binding interaction on immobilized human serum albumin stationary phase, aided by different computational approaches.

The drug-human serum albumin binding interaction was evaluated on a stationary phase immobilized with human serum albumin using a mixture of phosphate buffer (pH 7.0) and acetonitrile modifier as mobile phase. The 33 compounds that have a wide structural and therapeutic diversity were analyzed by performing a large number of experiments. The interaction mechanism was interpreted based on: i) retention characteristics of structurally related compounds, ii) retention modeling, iii) quantitative structure retention relationship (QSRR), and iv) molecular docking. Small structural differences of related compounds (e.g., reflected in different lipophilicity and polarity) have been found to affect their different binding to human serum albumin. It was found that drug retention in HSA column can be successfully described by using the quadratic function. The isocratic (logk(14%)) and extrapolated (b0(LSS)) retention factors showed the highest correlation (r > 0.76) with the constant that defines the binding affinity for human serum albumin (ACD/I-Lab). Therefore, selected chromatographic parameters can demonstrate reliable applicability for rapid screening of drug-plasma protein binding in drug discovery. In QSRR study, the resulting SVM/logk(14%) and MLR/b0(LSS) models display high internal and external predictive power. The constitutional properties (double bonds, aromatic rings, benzyl, allyl, -amino and -sulfur containing functional groups) supported by the charged parts of surface area had a significant impact on human serum albumin-binding affinity, which was also confirmed with molecular docking study. The high structural diversity of the data set provides wide applicability of tested chromatographic conditions and constructed models for defining the pharmacokinetic profile and possible structural modifications that can increase plasma protein binding of newly synthesized, pharmaceutically important compounds.

Application of in vitro PAMPA technique and in silico computational methods for blood-brain barrier permeability prediction of novel CNS drug candidates.

Permeability assessment of small molecules through the blood-brain barrier (BBB) plays a significant role in the development of effective central nervous system (CNS) drug candidates. Since in vivo methods for BBB permeability estimation require a lot of time and resources, in silico and in vitro approaches are becoming increasingly popular nowadays for faster and more economical predictions in early phases of drug discovery. In this work, through application of in vitro parallel artificial membrane permeability assay (PAMPA-BBB) and in silico computational methods we aimed to examine the passive permeability of eighteen compounds, which affect serotonin and dopamine levels in the CNS. The data set was consisted of novel six human dopamine transporter (hDAT) substrates that were previously identified as the most promising lead compounds for further optimisation to achieve neuroprotective effect, twelve approved CNS drugs, and their related compounds. Firstly, PAMPA methods was used to experimentally determine effective BBB permeability (Pe) for all studied compounds and obtained results were further submitted for quantitative structure permeability relationship (QSPR) analysis. QSPR models were built by using three different statistical methods: stepwise multiple linear regression (MLR), partial least square (PLS), and support-vector machine (SVM), while their predictive capability was tested through internal and external validation. Obtained statistical parameters (MLR- R2pred=-0.10; PLS- R2pred=0.64, r2m=0.69, r/2m=0.44; SVM- R2pred=0.57, r2m=0.72, r/2m=0.55) indicated that the SVM model is superior over others. The most important molecular descriptors (H0p and SolvEMt_3D) were identified and used to propose structural modifications of the examined compounds in order to improve their BBB permeability. Moreover, steered molecular dynamics (SMD) simulation was employed to comprehensively investigate the permeability pathway of compounds through a lipid bilayer. Taken together, the created QSPR model could be used as a reliable and fast pre-screening tool for BBB permeability prediction of structurally related CNS compounds, while performed MD simulations provide a good foundation for future in silico examination.

Mixed-Mode Hydrophilic Interactions/Reversed-Phase Retention Mechanism in Thin-Layer Chromatography.

We investigated the dual retention mechanism in thin-layer chromatography taking place on three stationary phases of different polarity (C-18, plain silica gel and DIOL) and using binary mobile phases composed of acetonitrile as the main component and water, or methanol as a modifier. As the test analytes, we selected a set of 12 compounds of pharmaceutical importance and considerably different chemical structure, i.e. the imidazoline and serotonin receptor ligands, and their related compounds. Retention of each analyte in each investigated chromatographic system was determined in a wide enough range of the mobile phase composition, with volume fraction of the mobile phase modifier ranging from 0.10 to 0.90. Calculation of the exact turning point values as a proof of occurrence of the reversed-phase hydrophilic interaction chromatography (HILIC/RP) retention mechanism was based on the multimodal retention model. The dual retention mode was described with the use of the volume fraction of the mobile phase modifier, the total polarity and the total solubility models. For the DIOL, C-18 and silica gel stationary phase, the dual (HILIC/RP) retention mechanism was confirmed. In the case of the DIOL stationary phase and acetonitrile/methanol mobile phase, the observed retention mechanism was more complicated than the dual HILIC/RP one.

Novel computational approaches to retention modeling in dual hydrophilic interactions/reversed phase chromatography.

The mixed-mode chromatographic behavior was estimated for imidazoline and serotonin receptor ligands, and their related compounds on dual hydrophilic/reversed phase stationary phase. The Box-Cox transformation was used to obtain the most suitable mathematical equations which describe the mixed-mode retention. Optimal equations were found for the optimization parameter (λ): λ = -1, λ = -0.5, λ = 0, λ = 0.5, and λ = 1. The proposed equations show satisfactory characteristics compared to standard multimodal and quadratic approaches. For a wide range of volume fractions of the mobile phase modifier, crossing between hydrophilic and reversed phase interactions (the turning point) was defined in terms of the minimal retention and the minimum value of the volume fraction of the aqueous eluent in the mobile phase. The cubic spline interpolation was used as a reference method for estimation of the turning point. It was found out that the newly proposed equations can be used as alternative mathematical forms for the description of the dual retention mechanism and for the evaluation of the turning point. Three new experimental descriptors of the mixed-mode retention were proposed. Two descriptors quantitatively characterize hydrophilic (log kH) and reversed phase (log kR) interactions, while the third one (log kA) refers to the average retention for the whole HILIC/RP range. It was established that the main factors which control dual nature of the mixed-mode retention are lipophilicity, dipol-dipol, van der Waals and hydrogen bonding interactions. It was concluded that the newly proposed estimations of the retention data reliably characterize the mixed-mode chromatographic behavior.

The comparison of retention behaviour of imidazoline and serotonin receptor ligands in non-aqueous hydrophilic interaction chromatography and supercritical fluid chromatography.

This work presents an investigation of retention characteristics of imidazoline and serotonin receptor ligands in non-aqueous hydrophilic interaction liquid chromatography (NA-HILIC) and supercritical fluid chromatography (SFC). The separation has been carried out by using methanol as a mobile phase modifier with addition of two types of additives (NH4HCOO; NH4HCOO/HCOOH) and two different stationary phases (diol; mixed-mode diol). The selectivity characteristics were observed based on S-factors, logk-logk plots and radar plots. NA-HILIC vs. SFC retention of tested compounds was also described by considering the molecular properties of the analytes within the LSER analysis. The differences between SFC vs. NA-HILIC retention of imidazoline and serotonin receptor ligands grow with the acid addition to a mobile phase, noticeably on mixed-mode diol stationary phase (S ≥ 87). In addition, the good selectivity performances of the certain NA-HILIC and SFC conditions were confirmed by good separation of structurally related compounds (α ≥ 2). The molecular basis of NA-HILIC and SFC retention were explained by using Abraham's equation. The dominant analyte descriptors influencing retention were hydrogen bonding and dipolar interactions. The current study will present the theory, and discuss the applicability within the SFC vs. NA-HILIC regimes. In this way, it was provided the placing of two relatively new methods (SFC, NA-HILIC) in the map of modern analytical chromatography in terms of the pharmaceutical analysis.

Investigation and prediction of retention characteristics of imidazoline and serotonin receptor ligands and their related compounds on mixed-mode stationary phase.

Investigation of the retention behavior of a wide range of analytes, 43 nitrogen containing heterocyclic and guanidine derivatives such, as imidazoline and serotonin receptor ligands or their related compounds, was performed on mixed-mode stationary phase in the combined reversed-phase (RP) and hydrophilic interaction liquid chromatography (HILIC) modes. Suitability of the linear retention modelling in the HILIC and RP modes was tested including separate contributions from adsorption and partition. For the HILIC retention, the partition model was found to provide better description compared with the adsorption model. In a wider range of the aqueous eluent volume fractions, φ(aq), retention was described as a function of volume fractions and total polarity of mobile phase using the mixed-mode retention modelling. The obtained results revealed that the shift of the chromatographic mode can be calculated from the change of total polarity of mobile phase in a multi-modal relation, logarithm of retention factor vs. total polarity, with the minimum value representing the turning point between the HILIC and the RP mode. Molecular properties of the investigated compounds that influence the retention behavior and the turning point were selected using Multiple Linear Regression (MLR) and Support Vector Machine (SVM). Slightly better statistical results were found for the logkwRP(aq)/MLR, logkwHILIC(org)/MLR, logkbHILIC(aq)/MLR, and φmin (aq)/SVM (RBF) QSRR models than for the logkwRP(aq)/SVM, logkwHILIC(org)/SVM, logkbHILIC(aq)/SVM, and φmin(aq)/MLR modelling. With this insight, it is possible to precisely define and predict the retention characteristics based on physico-chemical properties of imidazoline and piperazine related compounds.