Evaluation of Physicochemical Properties of Ipsapirone Derivatives Based on Chromatographic and Chemometric Approaches.

Drug discovery is a challenging process, with many compounds failing to progress due to unmet pharmacokinetic criteria. Lipophilicity is an important physicochemical parameter that affects various pharmacokinetic processes, including absorption, metabolism, and excretion. This study evaluated the lipophilic properties of a library of ipsapirone derivatives that were previously synthesized to affect dopamine and serotonin receptors. Lipophilicity indices were determined using computational and chromatographic approaches. In addition, the affinity to human serum albumin (HSA) and phospholipids was assessed using biomimetic chromatography protocols. Quantitative Structure-Retention Relationship (QSRR) methodologies were used to determine the impact of theoretical descriptors on experimentally determined properties. A multiple linear regression (MLR) model was calculated to identify the most important features, and genetic algorithms (GAs) were used to assist in the selection of features. The resultant models showed commendable predictive accuracy, minimal error, and good concordance correlation coefficient values of 0.876, 0.149, and 0.930 for the validation group, respectively.

Predicting zeta potential of liposomes from their structure: A nano-QSPR model for DOPE, DC-Chol, DOTAP, and EPC formulations.

Liposomes, nanoscale spherical structures composed of amphiphilic lipids, hold great promise for various pharmaceutical applications, especially as nanocarriers in targeted drug delivery, due to their biocompatibility, biodegradability, and low immunogenicity. Understanding the factors influencing their physicochemical properties is crucial for designing and optimizing liposomes. In this study, we have presented the kernel-weighted local polynomial regression (KwLPR) nano-quantitative structure-property relationships (nano-QSPR) model to predict the zeta potential (ZP) based on the structure of 12 liposome formulations, including 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), 3ß-[N-(N',N'-dimethylaminoethane)-carbamoyl]cholesterol (DC-Chol), 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP), and L-α-phosphatidylcholine (EPC). The developed model is well-fitted (R2 = 0.96, RMSEC = 5.76), flexible (QCVloo2 = 0.83, RMSECVloo = 10.77), and reliable (QExt2= 0.89 RMSEExt = 5.17). Furthermore, we have established the formula for computing molecular nanodescriptors for liposomes, based on constituent lipids' molar fractions. Through the correlation matrix and principal component analysis (PCA), we have identified two key structural features affecting liposomes' zeta potential: hydrophilic-lipophilic balance (HLB) and enthalpy of formation. Lower HLB values, indicating a more lipophilic nature, are associated with a higher zeta potential, and thus stability. Higher enthalpy of formation reflects reduced zeta potential and decreased stability of liposomes. We have demonstrated that the nano-QSPR approach allows for a better understanding of how the composition and molecular structure of liposomes affect their zeta potential, filling a gap in ZP nano-QSPR modeling methodologies for nanomaterials (NMs). The proposed proof-of-concept study is the first step in developing a comprehensive and computationally based system for predicting the physicochemical properties of liposomes as one of the most important drug nano-vehicles.

Toward Nano-Specific In Silico NAMs: How to Adjust Nano-QSAR to the Recent Advancements of Nanotoxicology?

The rapid development of engineered nanomaterials (ENMs) causes humans to become increasingly exposed to them. Therefore, a better understanding of the health impact of ENMs is highly demanded. Considering the 3Rs (Replacement, Reduction, and Refinement) principle, in vitro and computational methods are excellent alternatives for testing on animals. Among computational methods, nano-quantitative structure-activity relationship (nano-QSAR), which links the physicochemical and structural properties of EMNs with biological activities, is one of the leading method. The nature of toxicological experiments has evolved over the last decades; currently, one experiment can provide thousands of measurements of the organism's functioning at the molecular level. At the same time, the capacity of the in vitro systems to mimic the human organism is also improving significantly. Hence, the authors would like to discuss whether the nano-QSAR approach follows modern toxicological studies and takes full advantage of the opportunities offered by modern toxicological platforms. Challenges and possibilities for improving data integration are underlined narratively, including the need for a consensus built between the in vitro and the QSAR domains.

Modeling of small molecule's affinity to phospholipids using IAM-HPLC and QSRR approach enhanced by similarity-based machine algorithms.

Immobilized artificial membrane chromatography (IAM) has been proposed as a more biosimilar alternative to classical lipophilicity measurement. Determination of small molecule's affinity to phospholipids can be supported for predicting their behavior in the human body. Therefore, a better understanding of the molecular interaction mechanism between small xenobiotics and phospholipids can accelerate drug discovery. Here, the quantitative structure-retention relationships (QSRR) approach was integrated with mechanistic descriptors calculated using Chemicalize software to propose an easy-to-interpretation QSRR model. Considering the heterogeneous character of the data set, locally weighted least squares kernel regression belonging to similarity-based machine learning methods have been applied. The results showed that lipophilicity, charge, and maximum projection area determine molecule binding to phospholipids. Full validation of the obtained model based on OECD recommendations has been performed and the applicability domain was defined using the probability-oriented distance-based approach. The high values of predictive squared correlation coefficient (Q2), and small root mean square error of prediction (RMSEP), 0.812 and 6.739, respectively, confirmed that the obtained QSRR model is not well-fitted to the training data but also showed prediction power. Additionally, only 1.5% of molecules from the training set and 2.8% from the validation test are outside the applicability domain, confirming great predictive abilities.

Modification of gradient HPLC method for determination of small molecules' affinity to human serum albumin under column safety conditions: Robustness and chemometrics study.

In the early stages of drug discovery, beyond the biological activity screening, determining the physicochemical properties that affect the distribution of molecules in the human body is an essential step. Plasma protein binding (PPB) is one of the most important investigated endpoints. Nevertheless, the methodology for measuring %PPB is significantly less popular and standardized than other physicochemical properties, like lipophilicity. Here, we proposed how to modify protocols presented by Valko into column safety conditions and evaluated their robustness using fractional factorial design. For robustness testing, four factors were selected: column temperature, mobile phase flow rate, maximum isopropanol concentration in the mobile phase, and buffer pH. Elaborate methods have been applied for the analysis of HSA affinity for three groups of antibiotic-oriented substances that vary in chemical structure: fluoroquinolones, sulfonamides, and tetrazole derivatives. Furthermore, based on the reversed-phase chromatography the workflow of pilot studies was proposed to select molecules that have high affinity to HSA and can not be eluted from the HSA column using the concentration of organic modifier recommended by the column manufacturer.

Comprehensive Assessment of the Stability of Selected Coxibs in Variable Environmental Conditions along with the Assessment of Their Potential Hepatotoxicity.

Determining the influence of environmental factors on the stability of drugs is very helpful when choosing excipients, storage conditions or packaging materials. In addition, information about possible toxic degradation products enables detecting and avoiding the harmful side effects of the drug. We used the thin-layer chromatographic-densitometric procedure for the assay of five coxibs, conducted degradation studies in various environments and at different temperatures along with the determination of pharmacokinetic parameters. The results were subjected to chemometric analysis, to investigate and visualize the similarities and differences of the studied coxibs. Samples of the tested drug were also analyzed by UPLC-MS/MS in order to identify degradation products, and determine possible drug degradation pathways. Using the human liver cancer HepG2 cell line, the hepatotoxic effect of the degradation products was also determined. It was observed that all substances were relatively stable under the analyzed conditions and degraded more in acidic than alkaline environments. Robenacoxib is the drug that decomposes the fastest, and cimicoxib turned out to be the most stable. Robenacoxib also showed significant hepatotoxicity at the highest tested concentration, which correlates with the high degree of its degradation, and the probable formation of a more hepatoxic product. The obtained mass spectra of compounds formed as a result of hydrolysis of the protonated drug leading to the formation of several product ions, which enabled us to propose probable degradation pathways.

A bibliometric analysis of the recent achievements in pulmonary safety of nanoparticles.

Assessing research activity is an important step for planning future initiatives oriented toward filling the remaining gaps in a field. Therefore, the objective of the current study was to review recently published research on pulmonary toxicity caused by nanomaterials. However, here, instead of reviewing possible toxic effects and discussing their mode of action, the goal was to establish trends considering for example examined so far nanomaterials or used testing strategies. A total of 2316 related articles retrieved from the three most cited databases (PubMed Scopus, Web of Science), selected based on the title and abstract requirements, were used as the source of the review. Based on the bibliometric analysis, the nano-meter metal oxides, and carbon-based nanotubes were identified as the most frequently studied nanomaterials, while quantum dots, which might induce possible harmful effects, were not considered so far. The majority of testing of pulmonary safety is based on in vitro studies with observed growth of the contribution of novel testing strategies, such as 3D lung model, air-liquid interface system, or omic analysis.

Menthol- and thymol-based ciprofloxacin derivatives against Mycobacterium tuberculosis: in vitro activity, lipophilicity, and computational studies.

In this work, we investigated the antitubercular properties of Ciprofloxacin derivatives conjugated with menthol and thymol moieties. For the sixteen derivatives, we established minimal inhibitory concentrations (MIC) using isolates of Mycobacterium tuberculosis that were resistant or susceptible to other antibiotics. For the most potent compound 1-cyclopropyl-6-fluoro-7-{4-[6-((1R,2S,5R)-2-isopropyl-5-methylcyclohexyloxy)-6-oxohexyl]piperazin-1-yl}-4-oxo-1,4-dihydroquinoline-3-carboxylic acid (6), we determined fractional inhibitory concentration index (FICI) values to confirm antibacterial susceptibility and synergistic effects with other reference drugs. In addition, chromatographic studies of all the derivatives demonstrated a significant three to four-fold increase in lipophilicity and affinity to phospholipids compared to Ciprofloxacin. Finally, we conducted structure-based studies of the investigated compounds using molecular docking and taking into account protein target mutations associated with fluoroquinolone resistance. In summary, our findings indicate that the investigated compounds possess tuberculostatic properties, with some showing similar or even better activity against resistant strains compared to reference drugs. Increased lipophilicity and affinity to phospholipids of the new derivatives can offer several advantages for new drug candidates, beyond just improved cell membrane penetration. However, further studies are needed to fully understand their safety, efficacy, and mechanism of action.

The Effects of Two Kinds of Dietary Interventions on Serum Metabolic Profiles in Haemodialysis Patients.

The goal of this study was to evaluate the effects of two kinds of 24-week dietary interventions in haemodialysis patients, a traditional nutritional intervention without a meal before dialysis (HG1) and implementation of a nutritional intervention with a meal served just before dialysis (HG2), in terms of analysing the differences in the serum metabolic profiles and finding biomarkers of dietary efficacy. These studies were performed in two homogenous groups of patients (n = 35 in both groups). Among the metabolites with the highest statistical significance between HG1 and HG2 after the end of the study, 21 substances were putatively annotated, which had potential significance in both of the most relevant metabolic pathways and those related to diet. After the 24 weeks of the dietary intervention, the main differences between the metabolomic profiles in the HG2 vs. HG1 groups were related to the higher signal intensities from amino acid metabolites: indole-3-carboxaldehyde, 5-(hydroxymethyl-2-furoyl)glycine, homocitrulline, 4-(glutamylamino)butanoate, tryptophol, gamma-glutamylthreonine, and isovalerylglycine. These metabolites are intermediates in the metabolic pathways of the necessary amino acids (Trp, Tyr, Phe, Leu, Ile, Val, Liz, and amino acids of the urea cycle) and are also diet-related intermediates (4-guanidinobutanoic acid, indole-3-carboxyaldehyde, homocitrulline, and isovalerylglycine).

Antibacterial and antibiofilm activity of permanently ionized quaternary ammonium fluoroquinolones.

A series of quaternary ammonium fluoroquinolones was obtained by exhaustive methylation of the amine groups present at the 7-position of fluoroquinolones, including ciprofloxacin, enoxacin, gatifloxacin, lomefloxacin, and norfloxacin. The synthesized molecules were tested for their antibacterial and antibiofilm activities against Gram-positive and Gram-negative human pathogens, i.e. Staphylococcus aureus and Pseudomonas aeruginosa. The study showed that the synthesized compounds are potent antibacterial agents (MIC values at the lowest 6.25 µM) with low cytotoxicity in vitro as assessed on the BALB 3T3 mouse embryo cell line. Further experiments proved that the tested derivatives are able to bind to the DNA gyrase and topoisomerase IV active sites in a fluoroquinolone-characteristic manner. The most active quaternary ammonium fluoroquinolones, in contrast to ciprofloxacin, reduce the total biomass of P. aeruginosa ATCC 15442 biofilm in post-exposure experiments. The latter effect may be due to the dual mechanism of action of the quaternary fluoroquinolones, which also involves disruption of bacterial cell membranes. IAM-HPLC chromatographic experiments with immobilized artificial membranes (phospholipids) showed that the most active compounds were those with moderate lipophilicity and containing a cyclopropyl group at the N1 nitrogen atom in the fluoroquinolone core.

Development of Safirinium dyes for new applications: fluorescent staining of bacteria, human kidney cells, and the horny layer of the epidermis.

Low-molecular synthetic fluorophores are convenient tools in bioimaging applications. Several derivatives of Safirinium dyes as well as their reactive N-hydroxysuccinimide (NHS) esters bearing diverse substituents were synthesized and evaluated experimentally in terms of their lipophilicity by means of reverse-phase and immobilized artificial membrane high-performance liquid chromatography. Subsequently, the selected compounds were employed as novel cellular imaging agents for staining Gram-positive and Gram-negative bacteria, human kidney cell line, as well as human skin tissue. The analyzed dyes allowed for visualization of cellular structures such as mitochondria, endoplasmic reticulum, and cellular nuclei. They proved to be useful in fluorescent staining of stratum corneum, especially in the aspect of xenobiotic exposure and its penetration into the skin. The best results were obtained with the use of moderately lipophilic NHS esters of Safirinium Q. The development of Safirinium dyes is a promising alternative for commercially available dyes since the reported molecules have low molecular masses and exhibit efficient staining and remarkable water solubility. Moreover, they are relatively simple and low-cost in synthesis.

Modeling of Anticancer Sulfonamide Derivatives Lipophilicity by Chemometric and Quantitative Structure-Retention Relationships Approaches.

Sulfonamides are a classic group of chemotherapeutic drugs with a broad spectrum of pharmacological action, including anticancer activity. In this work, reversed-phase high-performance liquid chromatography and biomimetic chromatography were applied to characterize the lipophilicity of sulfonamide derivatives with proven anticancer activities against human colon cancer. Chromatographically determined lipophilicity parameters were compared with obtained logP, employing various computational approaches. Similarities and dissimilarities between experimental and computational logP were studied using principal component analysis, cluster analysis, and the sum of ranking differences. Furthermore, quantitative structure-retention relationship modeling was applied to understand the influences of sulfonamide's molecular properties on lipophilicity and affinity to phospholipids.

In vitro to in vivo extrapolation to support the development of the next generation risk assessment (NGRA) strategy for nanomaterials.

There is growing interest in developing novel strategies to support assessment of human health risks due to chemicals. Regulatory and decision-making agencies have recommended that non-animal-based alternatives should be applied whenever possible instead of experimentation on living animals. These alternative methods are beneficial because they are ethical, inexpensive, and rapid. Herein, we review recent activities aimed at developing in vitro to in vivo extrapolation (IVIVE) models as a part of the Next Generation Risk Assessment (NGRA) of nanomaterials. In this context, we show the adverse outcome pathway (AOP)-based methodology for the identification of mechanistically relevant events serving as biomarkers for the targeted selection of in vitro assays. Considered events need to be biologically plausible, regulatory relevant, and crucial for the examination of occurrence of adverse outcomes. The promising advantages of using high-throughout-based omics data are highlighted. Furthermore, the application of 3D in vitro models and nano genome atlases to study nanoparticle toxicity is briefly summarized. Additionally, the challenges related to the extrapolation of in vitro doses into in vivo-relevant responses are presented. We also discuss the limitations of models applied thus far to study the fate of chemicals in the human body, which exist due to the lack of available knowledge regarding transformations of nanomaterials occurring in biological systems.

Prediction of the chromatographic hydrophobicity index with immobilized artificial membrane chromatography using simple molecular descriptors and artificial neural networks.

Screening of physicochemical properties should be considered one of the essential steps in the drug discovery pipeline. Among the available methods, biomimetic chromatography with an immobilized artificial membrane is a powerful tool for simulating interactions between a molecule and a biological membrane. This study developed a quantitative structure-retention relationships model that would predict the chromatographically determined affinity of xenobiotics to phospholipids, expressed as a chromatographic hydrophobicity index determined using immobilized artificial membrane chromatography. A heterogeneous set of 261 molecules, mostly showing pharmacological activity or toxicity, was analyzed chromatographically to realize this goal. The chromatographic analysis was performed using the fast gradient protocol proposed by Valko, where acetonitrile was applied as an organic modifier. Next, quantitative structure-retention relationships modeling was performed using multiple linear regression (MLR) methods and artificial neural networks (ANNs) coupled with genetic algorithm (GA)-inspired selection. Subsequently, the selection of the best ANN was supported by statistical parameters, the sum of ranking differences approach with the comparison of rank by random numbers and hierarchical cluster analysis.

Can Immobilized Artificial Membrane Chromatography Support the Characterization of Antimicrobial Peptide Origin Derivatives?

The emergence and spread of multiple drug-resistant bacteria strains caused the development of new antibiotics to be one of the most important challenges of medicinal chemistry. Despite many efforts, the commercial availability of peptide-based antimicrobials is still limited. The presented study aims to explain that immobilized artificial membrane chromatography can support the characterization of antimicrobial peptides. Consequently, the chromatographic experiments of three groups of related peptide substances: (i) short cationic lipopeptides, (ii) citropin analogs, and (iii) conjugates of ciprofloxacin and levofloxacin, with a cell-penetrating peptide were discussed. In light of the discussion of the mechanisms of action of these compounds, the obtained results were interpreted.

Multivariate assessment of anticancer oleanane triterpenoids lipophilicity.

Naturally occurring molecules are excellent sources of lead compounds. A series of oleanolic acid (OA) derivatives previously synthesized in our laboratory, which show promising antitumor activity, have been analyzed in terms of lipophilicity evaluation applying chromatographic and computational approaches. Retention data obtained on three reversed-phase liquid chromatography stationary phases (RP-HPLC) and immobilized artificial membrane chromatography (IAM-HPLC) were compared with computational methods using chemometric tools such as cluster analysis, principal component analysis and sum of ranking differences. To investigate the molecular mechanism of retention quantitive structure retention relationship analysis was performed, based on the genetic algorithm coupled with multiple linear regression (GA-MLR). The obtained results suggested that the ionization potential of studied molecules significantly affects their retention in classical RP-HPLC. In IAM-HPLC additionally, polarizability-related descriptors also play an essential role in that process. The lipophilicity indices comparison shows significant differences between the computational lipophilicity and chromatographically determined ones.

Affinity of Antifungal Isoxazolo[3,4-b]pyridine-3(1H)-Ones to Phospholipids in Immobilized Artificial Membrane (IAM) Chromatography.

Currently, rapid evaluation of the physicochemical parameters of drug candidates, such as lipophilicity, is in high demand owing to it enabling the approximation of the processes of absorption, distribution, metabolism, and elimination. Although the lipophilicity of drug candidates is determined using the shake flash method (n-octanol/water system) or reversed phase liquid chromatography (RP-LC), more biosimilar alternatives to classical lipophilicity measurement are currently available. One of the alternatives is immobilized artificial membrane (IAM) chromatography. The present study is a continuation of our research focused on physiochemical characterization of biologically active derivatives of isoxazolo[3,4-b]pyridine-3(1H)-ones. The main goal of this study was to assess the affinity of isoxazolones to phospholipids using IAM chromatography and compare it with the lipophilicity parameters established by reversed phase chromatography. Quantitative structure-retention relationship (QSRR) modeling of IAM retention using differential evolution coupled with partial least squares (DE-PLS) regression was performed. The results indicate that in the studied group of structurally related isoxazolone derivatives, discrepancies occur between the retention under IAM and RP-LC conditions. Although some correlation between these two chromatographic methods can be found, lipophilicity does not fully explain the affinities of the investigated molecules to phospholipids. QSRR analysis also shows common factors that contribute to retention under IAM and RP-LC conditions. In this context, the significant influences of WHIM and GETAWAY descriptors in all the obtained models should be highlighted.

Drug affinity to human serum albumin prediction by retention of cetyltrimethylammonium bromide pseudostationary phase in micellar electrokinetic chromatography and chemically advanced template search descriptors.

The development of high-throughput methods for the estimation of physicochemical and biological properties of drug candidates is highly desired in the pharmaceutical landscape. Affinity to plasma protein is one of the most important biological properties, which should be taken under concern during the design and assessment of future potential medicines. The main goal of this study was to develop a quantitative retention-activity relationship model, with rationalized in vivo and in silico approach to predict the affinity to human serum albumin (HSA), which is one of the most important plasma proteins. To achieve this goal, a set of 27 chemically diverse drugs with known affinity to HSA were analyzed by micellar electrokinetic chromatography (MEKC). The proposed model for HSA affinity assessment was based on retention in hexadecyltrimethylmonium bromide (CTAB) pseudostationary phase and chemically advanced template search (CATS) pharmacophore descriptors. The comparison of various regression methods, namely multiple linear regression (MLR), partial least squares regression (PLS), orthogonal partial least squares (OPLS), and support vector machine (SVM) were performed to develop a model with highest predictability. The obtained models are suitable for the prediction of drug affinity to human serum albumin using retention factor determined by MEKC and CATS descriptors, and only slightly differ in terms of coefficients of determination, Q2 value calculated using leave-one-out cross-validation technique and root-mean-squared error of cross-validation (RMSECV) as well as root-mean-square error in prediction (RMSEP) obtained by external validation.

A Novel Approach to Optimize Hot Melt Impregnation in Terms of Amorphization Efficiency.

In this study, an innovative methodology to optimize amorphization during the hot melt impregnation (HMI) process was proposed. The novelty of this report revolves around the use of thermal analysis in combination with design of experiments (DoEs) to reduce residual crystallinity during the HMI process. As a model formulation, a mixture of ibuprofen (IBU) and Neusilin was used. The main aim of the study was to identify the critical process parameters of HMI and determine their optimal values to assure a robust impregnation process and possibly the highest possible amorphization rate of IBU. In order to realize this, a DoE approach was proposed based on a face-centered composite design involving three factors. The IBU/Neusilin ratio, the feeding rate, and the screw speed were considered as variables, while the residual crystallinity level of IBU, determined using differential scanning calorimetry (DSC), was measured as the response. Additionally, the stability of IBU under HMI was analyzed using high-performance liquid chromatography to estimate the extent of potential degradation. In order to verify the correctness of the DoE model, tested extrudates were manufactured by HMI and the obtained extrudates were thoroughly examined using scanning electron micrography, X-ray powder diffraction, and DSC.

Capillary zone electrophoresis of bacterial extracellular vesicles: A proof of concept.

The extracellular vesicles (EVs) released by plant pathogens of the Pectobacterium genus were investigated. The isolates were obtained using differential centrifugation followed by filtration and were characterized in terms of total protein content and particle size distribution. The transmission electron microscopy (TEM) analysis revealed the presence of two morphologically differentiated subpopulations of vesicles in the obtained isolates. The proteomic analysis using matrix-assisted laser desorption ionization mass spectrometry with time of flight detector (MALDI-TOF/TOF-MS) enabled to identify 62 proteomic markers commonly found in EVs of Gram-negative rods from the Enterobacteriaceae family. Capillary electrophoresis (CE) was proposed as a novel tool for the characterization of EVs. The method allowed for automated and fast (<15 min per sample) separation of vesicles from macromolecular aggregates with low sample consumption (about 10 nL per analysis). The approach required simple background electrolyte (BGE) composed of 50 mM BTP and 75 mM glycine (pH 9.5) and standard UV detection. The report presents a new opportunity for quality control of samples containing EVs.