Chromatographic Data in Statistical Analysis of BBB Permeability Indices.

Blood-brain barrier (BBB) permeability is an essential phenomena when considering the treatment of neurological disorders as well as in the case of central nervous system (CNS) adverse effects caused by peripherally acting drugs. The presented work contains statistical analyses and the correlation assessment of the analyzed group of active pharmaceutical ingredients (APIs) with their BBB-permeability data collected from the literature (such as computational log BB; Kp,uu,brain, and CNS+/- groups). A number of regression models were constructed in order to observe the connections between the APIs' physicochemical properties in combination with their retention data from the chromatographic experiments (TLC and HPLC) and the indices of bioavailability in the CNS. Conducted analyses confirm that descriptors significant in BBB permeability modeling are hydrogen bond acceptors and donors, physiological charge, or energy of the lowest unoccupied molecular orbital. These molecular descriptors were the basis, along with the chromatographic data from the TLC in log BB regression analyses. Normal-phase TLC data showed a significant contribution to the creation of the log BB regression model using the multiple linear regression method. The model using them showed a good predictive value at the level of R2 = 0.87. Models for Kp,uu,brain resulted in lower statistics: R2 = 0.56 for the group of 23 APIs with the participation of k IAM.

Immobilized Keratin HPLC Stationary Phase-A Forgotten Model of Transdermal Absorption: To What Molecular and Biological Properties Is It Relevant?

Chromatographic retention data collected on immobilized keratin (KER) or immobilized artificial membrane (IAM) stationary phases were used to predict skin permeability coefficient (log Kp) and bioconcentration factor (log BCF) of structurally unrelated compounds. Models of both properties contained, apart from chromatographic descriptors, calculated physico-chemical parameters. The log Kp model, containing keratin-based retention factor, has slightly better statistical parameters and is in a better agreement with experimental log Kp data than the model derived from IAM chromatography; both models are applicable primarily to non-ionized compounds.Based on the multiple linear regression (MLR) analyses conducted in this study, it was concluded that immobilized keratin chromatographic support is a moderately useful tool for skin permeability assessment.However, chromatography on immobilized keratin may also be of use for a different purpose-in studies of compounds' bioconcentration in aquatic organisms.

Statistical Methods in the Study of Protein Binding and Its Relationship to Drug Bioavailability in Breast Milk.

Protein binding (PB) is indicated as the factor most severely limiting distribution in the organism, reducing the bioavailability of the drug, but also minimizing the penetration of xenobiotics into the fetus or the body of a breastfed child. Therefore, PB is an important aspect to be analyzed and monitored in the design of new drug substances. In this paper, several statistical analyses have been introduced to find the relationship between protein binding and the amount of drug in breast milk and to select molecular descriptors responsible for both pharmacokinetic phenomena. Along with descriptors related to the physicochemical properties of drugs, chromatographic descriptors from TLC and HPLC experiments were also used. Both methods used modification of the stationary phase, using bovine serum albumin (BSA) in TLC and human serum albumin (HSA) in HPLC. The use of the chromatographic data in the protein binding study was found to be positive -the most effective application of normal-phase TLC and HPLCHSA data was found. Statistical analyses also confirmed the prognostic value of affinity chromatography data and protein binding itself as the most important parameters in predicting drug excretion into breast milk.

IAM Chromatographic Models of Skin Permeation.

Chromatographic retention factor log kIAM obtained from IAM HPLC chromatography with buffered aqueous mobile phases and calculated molecular descriptors (surface area-Sa; molar volume-VM; polar surface area-PSA; count of freely rotable bonds-FRB; H-bond acceptor count-HA; energy of the highest occupied molecular orbital-EHOMO; energy of the lowest unoccupied orbital-ELUMO; and polarizability-α) obtained for a group of 160 structurally unrelated compounds were tested in order to generate useful models of solutes' skin permeability coefficient log Kp. It was established that log kIAM obtained in the conditions described in this study is not sufficient as a sole predictor of the skin permeability coefficient. Simple put, potentially useful models based on log kIAM and readily available calculated descriptors, accounting for 85 to 91% of the total variability, were generated using Multiple Linear Regression (MLR).The models proposed in the study were tested on a group of 20 compounds with known experimental log Kp values.

RP-18 TLC and Computational Descriptors of Skin Permeability of Sunscreens.

The relationships between the reversed-phase thin layer chromatographic retention parameters obtained on octadecyl-modified silica (RP-18) sorbent for mobile phases containing water and one of six water-miscible organic modifiers (acetone, methanol, acetonitrile, tetrahydrofurane, N,N-dimethylformamide, 1,4-dioxane) and skin permeability coefficients were studied for a group of 21 cosmetic raw materials, mainly organic sunscreens and preservatives. The correlations between the skin permeability coefficients log Kd calculated in silico using EpiSuite software and the RP-18 thin layer chromatographic retention parameters are mostly linear, especially for compounds of lower-to-medium lipophilicity. It was established that skin permeability coefficient models based on retention parameters collected for mobile phases containing acetone or dioxane (75% v/v), proposed for structurally unrelated cosmetic raw materials are also applicable to other actives, as shown using a test set of compounds whose in vivo log Kd data are available. Skin permeability models developed in this study have the benefit of being based on easily obtained, chromatographic descriptors and their applicability extends beyond cosmetic chemistry.

RP-18 TLC Chromatographic and Computational Study of Skin Permeability of Steroids.

The skin permeability of steroids, as investigated in this study, is important because some of these compounds are, or could, be used in preparations applied topically. Several models of skin permeability, involving thin layer chromatographic and calculated descriptors, were generated and validated using Kp reference values obtained in silico and then tested on a group of solutes whose experimental Kp values could be found (log Kpexp). The study established that the most applicable log Kp model is based on RP-18 thin layer chromatographic data (RM) and the calculated descriptors VM (molar volume) and PSA (polar surface area). Two less efficient, yet simple, equations based on PSA or VM combined with HD (H-donor count) can be used with caution for rapid, rough estimations of compounds' skin permeability prior to their chemical synthesis.

In silico Plasma Protein Binding Studies of Selected Group of Drugs Using TLC and HPLC Retention Data.

Plasma protein binding is an important determinant of the pharmacokinetic properties of chemical compounds in living organisms. The aim of the present study was to determine the index of protein binding affinity based on chromatographic experiments. The question is which chromatographic environment will best mimic the drug-protein binding conditions. Retention data from normal phase thin-layer liquid chromatography (NP TLC), reversed phase (RP) TLC and HPLC chromatography experiments with 129 active pharmaceutical ingredients (APIs) were collected. The stationary phase of the TLC plates was modified with protein and the HPLC column was filled with immobilized human serum albumin. In both chromatographic methods, the mobile phase was based on a buffer with a pH of 7.4 to mimic physiological conditions. Chemometric analyses were performed to compare multiple linear regression models (MLRs) with retention data, using protein binding values as the dependent variable. In the course of the analysis, APIs were divided into acidic, basic and neutral groups, and separate models were created for each group. The MLR models had a coefficient of determination between 0.73 and 0.91, with the highest values from NP TLC data.

Application of RP-18 TLC Retention Data to the Prediction of the Transdermal Absorption of Drugs.

Several chromatographic parameters (RM0 and S obtained from RP-18 TLC with methanol-pH 7.4 phosphate buffer mobile phases by extrapolation to zero concentration of methanol; Rf and RM obtained from RP-18 TLC with acetonitrile-pH 7.4 phosphate buffer 70:30 v/v as a mobile phase) and calculated molecular descriptors (molecular weight-MW; molar volume-VM; polar surface area-PSA; total count of nitrogen and oxygen atoms-(N+O); H-bond donor count-HD; H-bond acceptor count-HA; distribution coefficient-log D; total energy-ET; binding energy-Eb; hydration energy-Eh; energy of the highest occupied molecular orbital-EHOMO; energy of the lowest unoccupied orbital-ELUMO; electronic energy-Ee; surface area-Sa; octanol-water partition coefficient-log P; dipole moment-DM; refractivity-R, polarizability-α) and their combinations (Rf/PSA, RM/MW, RM/VM) were tested in order to generate useful models of solutes' skin permeability coefficient log Kp. It was established that neither RM0 nor S obtained in the conditions used in this study is a good predictor of the skin permeability coefficient. The chromatographic parameters Rf and Rf/PSA were also unsuitable for this purpose. A simple and potentially useful, purely computational model based on (N+O), log D and HD as independent variables and accounting for ca. 83% of total variability was obtained. The evaluation of parameters derived from RM (RM, RM/MW, RM/VM) as independent variables in log Kp models proved that RM/VM is the most suitable descriptor belonging to this group. In a search for a reliable log Kp model based on this descriptor two possibilities were considered: a relatively simple model based on 5 independent variables: (N+O), log D, RM/VM, ET and Eh and a more complex one, involving also Eb, MW and PSA.

Fluorimetric Properties of 3-Aminoflavone Biomolecule (3-AF). X-ray Crystal Structure of New Polymorph of 3-AF.

The crystal structure of the new polymorphic form of 3-aminoflavone (3-AF) has been determined by single crystal X-ray diffraction. This report presents results of fluorimetric studies on 3-AF in methanol and aquatic solvents. Based on 3D fluorescence emission spectra, optimal values for excitation (λex) and emission/analytical (λem) wavelength, the analytical concentration range as well as the range of concentration quenching for the studied compound were established. Moreover, the limit of detection (LOD) and the limit of quantification (LOQ) were determined. The results were compared with those obtained using the standard UV-Vis absorption spectrophotometric method. The effect of acidity (pH) and the concentration of halide anions (chlorides, bromides, iodides and fluorides) on fluorescence quenching were analysed.

Aspects of Drug-Protein Binding and Methods of Analyzing the Phenomenon.

In recent decades, drug-protein interactions have been widely studied and several methods of analysis of these phenomena have been developed and improved. These can be classified into separation, physical, chromatographic and electrophoretic methods. This review depicts the assumptions and mechanisms of methods from each group, details their strengths and weaknesses, and presents examples of their usage from the literature. Equilibrium dialysis, ultrafiltration, Hummel-Dreyer method or high performance affinity chromatography are given as representative examples, but this issue is far more expanded. Nowadays, increasing attention is paid to the computational methods and molecular modeling which are convenient tools to estimate protein binding affinity based on the physicochemical properties of compounds. To gain a broader overview, the study also examines the protein binding ability and pharmacotherapy of drugs against a range of substrates such as plasma, skin, tissue and human milk.

Phospholipid-based Immobilized Artificial Membrane (IAM) Chromatography: A Powerful Tool to Model Drug Distribution Processes.

A review of applications of the Immobilized Artificial Membrane (IAM) chromatography in drug discovery is given. IAM chromatography is presented as a tool to predict the interactions of solutes with biomembranes, blood-brain barrier permeability, volume of distribution, oral and skin absorption of drugs and compared to other in vitro techniques used to study drug bioavailability (caco-2 cells, liposome partition). Unbound phosphatidylcholine based stationary phases are also discussed. Some new trends and ideas in the IAM chromatography are presented.

SPE/TLC/Densitometric Quantification of Selected Synthetic Food Dyes in Liquid Foodstuffs and Pharmaceutical Preparations.

Selected synthetic food dyes (tartrazine, Ponceau 4R, Brilliant Blue, orange yellow, and azorubine) were isolated from liquid preparations (mouthwashes and beverages) by Solid Phase Extraction on aminopropyl-bonded silica with diluted aqueous sodium hydroxide as an eluent. The extraction step was followed by thin layer chromatography on silica gel 60 with chloroform-isopropanol-25% aq. ammonia 1 : 3 : 1 (v/v/v) as mobile phase and the densitometric quantification of dyes was achieved using quadratic calibration plots (R2 > 0.997; LOQ = 0.04-0.09 µgspot-1). The overall recoveries for all studied dyes were at the average level of over 90% and the repeatability of the proposed procedure (CV ≤ 4.1%) was sufficient to recommend it for the routine quantification of the aforementioned dyes in liquid matrices.

Quantification of Sunscreen Benzophenone-4 in Hair Shampoos by Hydrophilic Interactions Thin-Layer Chromatography/Densitometry or Derivative UV Spectrophotometry.

Benzophenone-4 (BZ4) was separated from surfactants, dyes, preservatives, and other components of hair shampoos by thin-layer chromatography on silica gel 60 stationary phase, with ethyl acetate-ethanol-water-pH 6 phosphate buffer (15 : 7 : 5 : 1 v/v/v/v) as mobile phase. Densitometry scanning of chromatograms was performed at 285 nm. The densitometric calibration curve for BZ4 was nonlinear (second-degree polynomial), with R > 0.999. The limits of detection and quantification were ca. 0.03 and ca. 0.1 µg spot(-1), respectively. The results obtained by HPTLC-densitometry were compared to those obtained by zero and 2nd derivative UV spectrophotometry. In the case of spectrophotometric methods, calibration curves were linear with R > 0.9998. The chromatographic method was fully validated.

Comparative (Q)SAR analysis of benzodiazepine derivatives with different biological activity.

211 compounds containing a benzodiazepine moiety (BZD) and belonging to 4 groups of different biological activity (H - inhibitors of reverse transcriptase of HIV-I virus, A - antiarrhythmic agents, G - ligands of benzodiazepine receptor in GABAergic system and C - cholecystokinin receptor antagonists) were subjected to structure-activity relationship (SAR) analysis. SAR investigations of all 211 BZD were based on Discriminant Function Analysis (DFA) of physicochemical data connected with BBB (blood-brain barrier) permeability of studied compounds. DFA was performed with STATISTICA 10.0 software by the stepwise method and resulted in 3 discriminant functions whose quality was assessed by Wilk's lambda parameter. Calculated discriminant functions (roots) were applied to draw the scatter diagram of canonical values that showed all 211 cases divided into 4 groups of different biological activity. The method was successfully validated with a set of 38 BZD derivatives expected to belong to groups H, A, G and C. The reliability of the obtained model was confirmed with a cross-validation test. Classification functions presented in this study may be used as a practical tool for predicting new BZD drugs activity.

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.

Application of chromatographic data in QSAR Studies of 3-[ω-(4-Arylpiperazin-1-yl)alkyl]pyrimido[5,4-c]quinolin-4(3H)-one derivatives as 5-HT1A receptor ligands.

The activity of several 3-[ω-(4-arylpiperazin-1-yl)alkyl]pyrimido[5,4-c]quinolin-4(3H)-ones (LCAPs) with well-defined serotonin 1A (5-HT1A) receptor affinity was described by using chromatographic and calculated physicochemical parameters in quantitative structure-activity relationship analysis. Normal-phase thin-layer chromatography plates impregnated with solutions of L-aspartic acid, L-serine, L-phenylalanine, L-tryptophan, L-tyrosine, L-asparagine, L-threonine and their mixtures (denoted as S1-S11 biochromatographic models) were used with two mobile phases as a model of the interaction between LCAP and 5-HT1A receptors. Molecular descriptors for the investigated compounds were calculated by using HyperChem and ACD/Labs programs. The significant relationship explains that 82% of the variance was successfully validated by leave-one-out and leave-many-out tests. The results demonstrated that this model has significant predictive ability and can be used for the preliminary screening of newly synthesized potential 5-HT1A receptor ligands.

Studies on esterification and sulfonation of riboflavin via semi-empirical methods.

The article presents extended computer investigations of various sulfate derivatives of riboflavin. A number of physicochemical parameters such as total energy, binding energy and formation heat were calculated via semi-empirical methods AM1 and PM3 for the different derivatives of riboflavin. Their analysis made it possible to determine the sequence of formation of sulfate derivatives--esterification is the easiest at hydroxyl groups at the farthest positions from the ring. This methodology may be used to study biologically active compounds.

Strategies of sunscreen separation by thin layer chromatography.

So far sunscreens separation has been achieved primarily by HPLC or TLC on RP-18 or (less frequently) unmodified silica gel as stationary phase. The conditions of chromatographic separation published so far are not suitable for many combinations of UV filters found commonly in cosmetic products. It is therefore reasonable to seek alternative conditions that would make it possible to separate these substances more effectively. Chromatographic separation of 15 UV filters used commonly for skin and hair protection was investigated. The effectiveness of separation of investigated compounds by normal- and reversed-phase thin layer chromatography was compared on RP-18, RP-2 and silica gel 60 stationary phases. In the case of some typical combinations of sunscreens normal-phase chromatography was found superior compared to the reversed-phase technique proposed in some published papers. It was suggested that sunscreens of totally different lipophilicity could be separated by multiple development TLC.

Development and validation of quantitative structure-activity relationship models for compounds acting on serotoninergic receptors.

A quantitative structure-activity relationship (QSAR) study has been made on 20 compounds with serotonin (5-HT) receptor affinity. Thin-layer chromatographic (TLC) data and physicochemical parameters were applied in this study. RP2 TLC 60F(254) plates (silanized) impregnated with solutions of propionic acid, ethylbenzene, 4-ethylphenol, and propionamide (used as analogues of the key receptor amino acids) and their mixtures (denoted as S1-S7 biochromatographic models) were used in two developing phases as a model of drug-5-HT receptor interaction. The semiempirical method AM1 (HyperChem v. 7.0 program) and ACD/Labs v. 8.0 program were employed to calculate a set of physicochemical parameters for the investigated compounds. Correlation and multiple linear regression analysis were used to search for the best QSAR equations. The correlations obtained for the compounds studied represent their interactions with the proposed biochromatographic models. The good multivariate relationships (R(2) = 0.78-0.84) obtained by means of regression analysis can be used for predicting the quantitative effect of biological activity of different compounds with 5-HT receptor affinity. "Leave-one-out" (LOO) and "leave-N-out" (LNO) cross-validation methods were used to judge the predictive power of final regression equations.

A structure-activity relationship study of thiazole derivatives with H1-antihistamine activity.

A structure-activity relationship (QSAR) analysis of 19 thiazole derivatives with H1-antihistamine activity was carried out. The semi-empirical method AMI was employed to calculate a set of physicochemical parameters for investigated compounds. The principal component analysis (PCA), discriminant function analysis (DFA) and regression analysis (RA) were employed to reduce dimensionality and investigate which subset of variables is effective for classifying the thiazole derivatives according to their degree of anti-H1 activity. In PCA the studied compounds were separated into two groups: group A with lower degree of H,-antihistamine activity and group B with higher activity. The DFA showed that the parameters: alpha (polarizability), AB (distance between aliphatic and aromatic nitrogen atoms), Eb (binding energy), Hh (hydration energy), eHOMO (HOMO energy), and QAr are responsible for separation between compounds exhibiting higher and lower H1-antihistamine activity. The importance of hydrophobic and steric parameters for thiazole derivatives 1-19 with HL-antihistamine activity was established via RA. On the basis of PCA, DFA and RA methods, a prediction rule for classifying new thiazole derivatives with H1-antihistamine activity was elaborated.