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.

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.

Application of reversed-phase thin layer chromatography and QSRR modelling for prediction of protein binding of selected ß-blockers.

Chromatographic properties of sixteen ß-blockers were studied using planar chromatography. The aim of presented study was to investigate influence of different organic solvents (acetonitrile, methanol, dioxin and tetrahydrofurane) on ß-blockers' retention on C18 bonded silica gel stationary phase. Group of sixteen, diverse in terms of structure, beta blockers was used as a model set. The main goal of this study was to compare chromatographically estimated lipophilicity parameters with values obtained with the use of computational methods. Furthermore, in order to understand molecular mechanisms of retention better, quantitative structure-retention relationships (QSRR) analysis was performed. The next step was focused on application of chromatographically obtained lipophilicity parameters for prediction of protein binding (PB), based on quantitative retention-activity relationships (QRAR) approach. The obtained results showed that reversed-phase thin layer chromatography (RP-TLC), especially with tetrafydrofurane used as an organic modifier of mobile phase, is a useful tool for lipophilicity estimation, as well as for prediction of ß-blockers' biological properties. The QRAR model included C0 parameters for tetrahydrofuran-water as a mobile phase, as well as maximal projection area, and can be easily applied for prediction of systematically synthesized ß-blockers structures' PB.