Lipophilicity study of different cephalosporins: Computational prediction of minimum inhibitory concentration using salting-out chromatography

The chromatographic and lipophilicity characters of seven cephalosporins of different four classes (cephradine, cefaclor, cefprozil, cefixime, cefotaxime, ceftazidime and cefepime) were examined by salting out thin-layer chromatography (SOTLC). SOTLC using ammonium sulfate salt was employed to predict the lipophilicity of the proposed drugs via their retention behavior. The calculated R_M0 values showed liner relationship with the molar concentration of ammonium sulfate in mobile phase in the range of 0.5-2.5 mol/L. Additionally, quantitative structure retention relationship (QSRR) was generated to figure out the relationship between the calculated chromatographic parameters (R_M0 and C₀) and log P of the studied cephalosporins. Good correlations were found between the chromatographically obtained retention parameters (R_M0 and C₀) and some molecular descriptors of the examined drugs. Furthermore, an efficient QSAR model was carried out using the calculated chromatographic parameters (R_M0 and C₀) and log P of the studied cephalosporins to predict minimum inhibitory concentration (MIC) and blood brain barrier (BBB) penetration of the examined drugs. The study was extended to separate and quantify the selected antibiotics in their pure forms and pharmaceutical formulations. Normal phase thin layer chromatographic (NP-TLC) method using a usable developing system of acetone: methanol: water: ammonium hydroxide: glacial acetic acid (90: 10: 18: 3: 2, by volume) was successfully applied to resolve the studied cephalosporins. Linearity was achieved in the range of 0.2-3 µg/mL for most of the studied antibiotics. The developed SOTLC method can be considered as a good start alternative to reversed phase thin layer chromatography (RP-TLC) for prediction of the lipophilic properties of examined cephalosporins. Moreover, the proposed NP-TLC densitometric method can be easily applied for quality control analysis of the chosen drugs and other structurally related components.

Prediction of the Blood-Brain Barrier Permeability Using RP-18 Thin Layer Chromatography

The Blood-Brain Barrier (BBB) permeability is an important factor governing a drug’s ability to act upon the Central Nervous System. The measure of the BBB permeability used throughout this study is the log BB (the blood/brain partitioning coefficient) measured in vivo or calculated. Useful yet simple models of the BBB permeability were developed by Stepwise Multiple Regression Analysis based on the chromatographic parameters Rf and Rf/PSA obtained by RP-18 TLC with acetonitrile - pH 7.4 phosphate buffered saline 70:30 (v/v) as mobile phase, combined with descriptors - the number of H-bond donors (HD), the number of H-bond acceptors (HA), energy of the highest occupied molecular orbital – (eH), energy of the lowest unoccupied molecular orbital (eL). The ability of the solutes to cross the BBB has been studied qualitatively using Discriminant Function Analysis. Almost all compounds with the known BB vivo parameter were correctly classified as CNS+/-. The classification functions based on Rf/PSA have been verified using an external group. The results of the chromatographic analysis proposed in this study (RP-18 TLC) are a source of valuable information on the BBB permeability of compounds available even on a very small scale.

Application of salting-out thin layer chromatography in computational prediction of minimum inhibitory concentration and blood-brain barrier penetration of some selected fluoroquinolones

The 2017 FDA safety review regarding the CNS (central nervous system) side effects associated with the systemic use of fluoroquinolones antibacterials (FQs) was the key motivation to carry out this work. The main objective of this study is to investigate lipophilicity and retention parameters of some selected fluoroquinolones antibacterials (FQs) namely; levofloxacin (LEV), ofloxacin (OFL), gatifloxacin (GAT), norfloxacin (NOR), sparfloxacin (SPA), ciprofloxacin (CIP) and lomefloxacin (LOM) using salting-out thin layer chromatography (SOTLC). Statistically significant correlations between the chromatographically-obtained retention parameters and experimental log P values were found and expressed as quantitative structure retention relationship (QSRR) equations. Principal component analysis was carried out to explain the variation between chromatographic and both experimental and computed lipophilicity parameters. In another aspect of this study, a comparison between the chromatographically-determined retention parameters (for five of the drugs under study) obtained using SOTLC (current study) and relative lipophilicity (R_M0) determined using a previously reported RP (reversed-phase)-TLC method was carried out. Statistically significant correlation between the two methods was found, although R_M0 values obtained using SOTLC was lower than those reported using RP-TLC. Multiple linear regression analysis was performed to predict MIC (minimum inhibitory concentration) and blood brain barrier (BBB) penetration of the examined drugs in which efficient QSAR (quantitative structure-activity relationship) and QSPR (quantitative structure-property relationship) models were generated using the calculated chromatographic parameters (R_M0 and C₀). The described models can provide a useful approach to predict MIC and BBB penetration of newly synthesized FQs targeting to increase their activity against Gram-positive organisms and to minimize the associated CNS side effects.

Combined computational-experimental approach to predict blood-brain barrier (BBB) permeation based on "green" salting-out thin layer chromatography supported by simple molecular descriptors

The objective of this paper is to build QSRR/QSAR model for predicting the blood-brain barrier (BBB) permeability. The obtained models are based on salting-out thin layer chromatography (SOTLC) constants and calculated molecular descriptors. Among chromatographic methods SOTLC was chosen, since the mobile phases are free of organic solvent. As consequences, there are less toxic, and have lower environmental impact compared to classical reserved phases liquid chromatography (RPLC). During the study three stationary phase silica gel, cellulose plates and neutral aluminum oxide were examined. The model set of solutes presents a wide range of log BB values, containing compounds which cross the BBB readily and molecules poorly distributed to the brain including drugs acting on the nervous system as well as peripheral acting drugs. Additionally, the comparison of three regression models: multiple linear regression (MLR), partial least-squares (PLS) and orthogonal partial least squares (OPLS) were performed. The designed QSRR/QSAR models could be useful to predict BBB of systematically synthesized newly compounds in the drug development pipeline and are attractive alternatives of time-consuming and demanding directed methods for log BB measurement. The study also shown that among several regression techniques, significant differences can be obtained in models performance, measured by R² and Q², hence it is strongly suggested to evaluate all available options as MLR, PLS and OPLS.

Sequence-dependent separation of trinucleotides by ion-interaction reversed-phase liquid chromatography-A structure-retention study assisted by soft-modelling and molecular dynamics

We studied sequence-dependent retention properties of synthetic 5'-terminal phosphate absent trinucleotides containing adenine, guanine and thymine through reversed-phase liquid chromatography (RPLC) and QSRR modelling. We investigated the influence of separation conditions, namely mobile phase composition (ion interaction agent content, pH and organic constituent content), on sequence-dependent separation by means of ion-interaction RPLC (II-RPLC) using two types of models: experimental design-artificial neural networks (ED-ANN), and linear regression based on molecular dynamics data. The aim was to determine those properties of the above-mentioned analytes responsible for the retention dependence of the sequence. Our results show that there is a deterministic relation between sequence and II-RPLC retention properties of the studied trinucleotides. Further, we can conclude that the higher the content of ion-interaction agent in the mobile phase, the more prominent these properties are. We also show that if we approximate the polar component of solvation energy in QSRR by the electrostatic work in transferring molecules from vacuum to water, and the non-polar component by the solvent accessible surface area, these parameters best describe the retention properties of trinucleotides. There are some exceptions to this finding, namely sequences 5'-NAN-3', 5'-ANN-3', 5'-TGN-3', 5'-NTA-3'and 5'-NGA-3' (N stands for generic nucleotide). Their role is still unknown, but since linear regression including these specific constellations showed a higher observable variance coverage than the model with only the basic descriptors, we may assume that solvent-analyte interactions are responsible for the exceptional behaviour of 5'-NAN-3' & 5'-ANN-3' trinucleotides and some intramolecular interactions of neighbouring nucleobases for 5'-TGN-3', 5'-NTA-3'and 5'-NGA-3' trinucleotides.

Evaluation of the lipophilicity of selected sunscreens--a chemometric analysis of thin-layer chromatographic retention data

The lipophilicities of 22 selected sunscreens, preservatives, and vitamins used in topical skin products were measured by thin-layer chromatography. Lipophilicity was calculated in silico from the sunscreen molecular structures and compared to the experimental octanol/water partition coefficients found in the literature. The retention of the compounds was investigated on an RP-18 stationary phase with mobile phases consisting of water and one of six organic modifiers (dioxane, tetrahydrofuran, acetone, acetonitrile, methanol, and dimethylformamide) at different concentrations. The theoretical lipophilicities were calculated by several computational algorithms and the results of these calculations were compared using cluster analysis. The results showed that two out of the six investigated organic modifiers (dioxane and acetone) may be used to estimate the octanol/water partition coefficients of highly lipophilic compounds having lipophilicities that cannot be measured directly by the shake-flask method.