Using Front-Face Fluorescence Spectroscopy and Biochemical Analysis of Honey to Assess a Marker for the Level of Varroa destructor Infestation of Honey Bee (Apis mellifera) Colonies.

Varroa destructor is a parasitic mite responsible for the loss of honey bee (Apis mellifera) colonies. This study aimed to find a promising marker in honey for the bee colony infestation level using fluorescence spectroscopy and biochemical analyses. We examined whether the parameters of the honey samples' fluorescence spectra and biochemical parameters, both related to proteins and phenolics, may be connected with the level of honey bee colonies' infestation. The infestation level was highly positively correlated with the catalase activity in honey (r = 0.936). Additionally, the infestation level was positively correlated with the phenolic spectral component (r = 0.656), which was tentatively related to the phenolics in honey. No correlation was found between the diastase activity in honey and the colonies' infestation level. The results indicate that the catalase activity in honey and the PFC1 spectral component may be reliable markers for the V. destructor infestation level of the colonies. The obtained data may be related to the honey yield obtained from the apiaries.

Elemental Profile of Propolis from Different Areas of Serbia.

Propolis is a resinous natural substance collected by honeybees from different plant sources. The element content of propolis is influenced by the content of elements in the soil, climatic factors, and the degree of pollution. The aim of the study was to characterize element composition and content of toxic elements in 51 propolis collected from different locations in Serbia and to evaluate the differences among them. Determination of the 21 elements were performed using Inductively coupled plasma - optical emission spectrometry. K was the most abundant element, followed by Ca, Mg, Si, Fe, Zn, and Al. The microelements B, Ba, Mn, Na, Pb, and Ti were also present in propolis, while Co, Cr, Cu, Mo, Ni, Sr, and V were found in trace. Toxic elements such as Pb, As, and Cd were found in the trace. Kruskal-Wallis tests differentiate groups of samples by geographical origin. The presence of B, Fe, Sr, Ti, Zn, and As demonstrated statistical significance between six regions of Serbia.

Primary Metabolite Chromatographic Profiling as a Tool for Chemotaxonomic Classification of Seeds from Berry Fruits.

Research background: Considering the importance of consumption of berry fruits with proven health-beneficial properties and difficulties in quality control of products of specific botanical and geographic origin, a fingerprint method was developed, based on advanced data analysis (pattern recognition, classification), in order to relate the variability of nutrients in the selected cultivars to primary metabolite profile. Experimental approach: Forty-five samples of genuine berry fruit cultivars (strawberry, raspberry, blackberry, black currant, blueberry, gooseberry, chokeberry, cape gooseberry and goji berry) were characterized according to chromatographic profiles of primary metabolites (sugars, lipids and fatty acids) obtained by three chromatographic techniques (high-performance thin-layer chromatography, gas chromatography coupled to mass spectrometry, and high-performance anion-exchange chromatography with pulsed amperometric detection). Results and conclusions: Comprehensive analysis allowed monitoring and identification of metabolites belonging to polar lipids, mono-, di- and triacylglycerols, free fatty acids, free sterols, sterol esters, mono- to heptasaccharides and sugar alcohols. Chemical fingerprint of berry seeds showed the uniformity of primary metabolites within each fruit species, but revealed differences depending on the botanical origin. All three chromatographic methods provided a discriminative, informative and predictive metabolomics methodology, which proved to be useful for chemotaxonomic classification. Novelty and scientific contribution: A novel methodology for the identification of bioactive compounds from primary metabolites of natural products was described. The proposed untargeted metabolite profiling approach could be used in the future as a routine method for tracing of novel bioactive compounds. The knowledge of metabolite composition obtained in this study can provide a better assessment of genotypic and phenotypic differences between berry fruit species and varieties, and could contribute to the development of new breeding programs.

Phenolic Compounds as Phytochemical Tracers of Varietal Origin of Some Autochthonous Apple Cultivars Grown in Serbia.

Domesticated international (standard) apple cultivars, together with resistant apple cultivars are the core of the Serbian apple production. Furthermore, autochthonous cultivars are characterized by a good adaptability to the local environmental conditions and represent a valuable source of genetic variability, as well as an important source of the gene pool for further breeding programs. Additionally, they show a higher phenolic content and a stronger antioxidant activity, in comparison to commercial cultivars. Therefore, they are more likely to be used as a functional food. The subjects of this study were seventeen samples of fruits and leaves from autochthonous apple cultivars, five international standard cultivars, and six resistant apple cultivars. The phenolic profile was determined using ultra-high performance liquid chromatography (UHPLC), coupled with a diode array detector and a TSQ Quantum Access Max triple-quadrupole mass spectrometer. A total of twenty compounds were quantified in the samples. Most of the analyzed phenolics were detected in higher amounts in the peel, compared to the mesocarp. The results of the multivariate analysis of variance (MANOVA) indicate that 5-O-caffeoylquinic acid is present in the highest amount in the mesocarp, while in the peel and leaves, quercetin-glycosides were detected in the highest amount. According to the MANOVA: phloretin, phlorizin, 5-O-caffeoylquinic acid, kaempferol, and p-coumaric acid are present in significantly higher levels in the autochthonous cultivars, compared to the standard and resistant ones (in both fruits and leaves). Therefore, these compounds can be used as chemical tracers of the apple varietal origin.

Effect-Directed Profiling of Strawberry Varieties and Breeding Materials via Planar Chromatography and Chemometrics.

Strawberries are an important fruit in the European diet because of their unique taste and high content of essential nutrients and bioactive compounds. The anthocyanins are known to be colorful phenolics in strawberries. In 17 samples of six strawberry cultivars produced in Serbia, i.e., the common varieties Alba, Asia, and Clery as well as promising breeding materials (11.29.11, 11.34.6, and 11.39.3), the anthocyanin profile as well as antimicrobial and antioxidative activity profiles were determined. All investigated extracts showed antioxidative and antibacterial activities against Gram-negative Aliivibrio fischeri. The responses were quite similar in number and intensity. The HPTLC-DPPH• scavenging assay and HPTLC-Aliivibrio fischeri bioassay coupled with high-resolution mass spectrometry identified pelargonidin-3-O-glucoside (Pg-3-glc) as the main anthocyanin and prominent antioxidative and antimicrobial compound in strawberries. The density functional theory calculations at the M06-2X/6-31+G(d,p) level showed that Pg-3-glc quenches free radicals via sequential proton loss electron transfer mechanism in water and in pentyl ethanoate, where the 5-OH group is the most reactive site for proton and hydrogen atom transfer. The results were confirmed via spectrophotometry. The highest total phenolic content was found in Clery and 11.39.3, while statistically significant differences between the genotypes regarding the antioxidant activity were not confirmed. Although very similar in the anthocyanin, antioxidative, and antimicrobial profile patterns, the strawberry genotypes were successfully classified using principal component analysis.

Quality Assessment of Apple and Grape Juices from Serbian and German Markets by Planar Chromatography-Chemometrics.

The high consumption of plant-based foods on a global scale has increased the number of adulterations in the food industry. Along with this, analytical approaches to fraud detection need to be further developed. A nontargeted effect-directed profiling by high-performance thin-layer chromatography hyphenated with five effect-directed assays (free radical scavenging assay, Aliivibrio fischeri bioassay, and acetylcholinesterase, butyrylcholinesterase, and tyrosinase inhibition assays) and multi-imaging provided additional information on the antioxidative, antimicrobial, and enzyme inhibition activities for 18 apple and 18 grape juices from markets in Serbia and Germany. Bioactive zones of interest were eluted using an elution head-based interface and further characterized by electrospray ionization high-resolution mass spectrometry. The different profiles were evaluated chemometrically, and several compounds, which were characteristic of samples from different markets located in Serbia and Germany, were identified in apple juice (such as chlorogenic acid, phloridzin, epicatechin, and caffeic acid) and grape juice (such as chlorogenic acid, epicatechin, and quercetin). The developed rapid and simple method for the quality assessment of fruit juices coming from different (geographic) markets showed clear quality differences. Thus, it could be used to learn more about quality differences, to detect fraud in fruit juice production, and to verify the authenticity of the origin.

Thin-layer chromatography in the authenticity testing of bee-products.

Quality control, nutritional value and the monitoring of hazardous residues in honey bee- products have become major topics for both producers and consumers. Due to its potential role in human health, bee-products rich in bioactive compounds are becoming increasingly popular. This review aims to provide an overview of thin-layer chromatography methods used in quality control,authenticity testing and chemical profiling of bee-products in order to help scientists engaged in the field of bee-products chemistry to utilize the advantages of this technique in the detection and elimination of fraudulent practices in bee-product manufacturing. Recently, hyphenation of thin-layer chromatography, image analysis and chemometrics support bee-products analysisbysimultaneousdeterminationofanalytes with different detection principles, identification of individual bioactive compounds as well as structure elucidation of compounds. Highlighted opportunities of thin-layer chromatography could encourage further investigations that would lead to improvements in the detection and elimination of marketing fraudulent practices.

Fast detection of apricot product frauds by added pumpkin via planar chromatography and chemometrics: Greenness assessment by analytical eco-scale.

The European Commission requires that fruit products distributed on the market meet standards of high quality and authenticity. For the quality assessment of apricot products susceptible to food fraud, an environmentally friendly, simple and cost-effective analytical profiling was developed by high-performance thin-layer chromatography multi-imaging (HPTLC-FLD/Vis). The new phytochemical profiling was applied for analysis of authentic samples (7 apricot and 5pumpkin samples) and simulated adulterated products (11 mixture samples prepared by addition of 2.5-53% pooled pumpkin to pooled apricot). Based on the analytical eco-scale assessment, the HPTLC-FLD/Vis method was proven as an excellent green analytical method with low energy and solvent consumption. Chemometric data analysis confirmed the difference between apricot and apricot-pumpkin mixtures based on the phytochemical profile. Chemical markers responsible for their differentiation were identified. The results indicated that frauds by adding pumpkin to apricot products can be detected at added contents as low as 2.5%.

Content and distribution of major and trace elements as a tool to assess the genotypes, harvesting time, and cultivation systems of potato.

The effects of organic versus integral and conventional crop management on content and distribution of major and trace elements in different varieties of potato were investigated in a three year field trial. A set of 48 potato tubers of four varieties with different harvesting times, cultivated in three types of agricultural systems: conventional (C), integral (I), and organic (O) were characterized based on the composition of the elements of their bulk and peel. A total of 16 elements were quantified. In order to determine the source of variation among the types of production, parts of potato and varieties, multivariate analysis of variance (MANOVA) was conducted. The results indicate that Ca, Mg, and K may be considered as important indicators of the type of production, genotypes of potato, and harvesting time. Additionally, the analyses show that ten microelements are able to distinguish between production types and genotypes of potato.

Lipophilicity Determination of Antifungal Isoxazolo[3,4-b]pyridin-3(1H)-ones and Their N1-Substituted Derivatives with Chromatographic and Computational Methods.

The lipophilicity of a molecule is a well-recognized as a crucial physicochemical factor that conditions the biological activity of a drug candidate. This study was aimed to evaluate the lipophilicity of isoxazolo[3,4-b]pyridine-3(1H)-ones and their N1-substituted derivatives, which demonstrated pronounced antifungal activities. Several methods, including reversed-phase thin layer chromatography (RP-TLC), reversed phase high-performance liquid chromatography (RP-HPLC), and micellar electrokinetic chromatography (MEKC), were employed. Furthermore, the calculated logP values were estimated using various freely and commercially available software packages and online platforms, as well as density functional theory computations (DFT). Similarities and dissimilarities between the determined lipophilicity indices were assessed using several chemometric approaches. Principal component analysis (PCA) indicated that other features beside lipophilicity affect antifungal activities of the investigated derivatives. Quantitative-structure-retention-relationship (QSRR) analysis by means of genetic algorithm-partial least squares (GA-PLS)-was implemented to rationalize the link between the physicochemical descriptors and lipophilicity. Among the studied compounds, structure 16 should be considered as the best starting structure for further studies, since it demonstrated the lowest lipophilic character within the series while retaining biological activity. Sum of ranking differences (SRD) analysis indicated that the chromatographic approach, regardless of the technique employed, should be considered as the best approach for lipophilicity assessment of isoxazolones.

Lipophilicity Determination of Quaternary (Fluoro)Quinolones by Chromatographic and Theoretical Approaches.

Lipophilicity is a vital physicochemical parameter of a molecule, which affects several biological processes such as absorption, tissue distribution, and pharmacokinetic properties. In this study, evaluation of lipophilicities of a series of novel fluoroquinolone-Safirinium dye hybrids using chromatographic and computational methods is presented. Fluoroquinolone-Safirinium dye hybrids have been synthesized as new dual-acting hydrophilic antibacterial agents. Reversed phase thin-layer chromatography and micellar electrokinetic chromatography experiments were carried out. Furthermore, logP values of the target structures were predicted by means of different software platforms and algorithms. In order to assess similarities and dissimilarities of the obtained lipophilicity indexes, cluster analysis and sum of ranking differences were performed. The significant differences of calculated logP values (α = 0.05, p < 0.001) indicated that an experimental approach is necessary for lipophilicity prediction of this class of antibiotics. Chromatographic data indicated that the newly synthesized hybrid (fluoro)quinolone-based quaternary ammonium derivatives show less lipophilic character than the parent (fluoro)quinolones. Additionally, the chromatographically obtained lipophilicity indexes were evaluated for possible application in quantitative retention-activity relationships. The established lipophilicity models have the potential to predict antimicrobial activities of a series of quaternary (fluoro)quinolones against Bacillus subtilis, Escherichia coli, and Proteus vulgaris.

Binary similarity measures for fingerprint analysis of qualitative metabolomic profiles.

INTRODUCTION: Contemporary metabolomic fingerprinting is based on multiple spectrometric and chromatographic signals, used either alone or combined with structural and chemical information of metabolic markers at the qualitative and semiquantitative level. However, signal shifting, convolution, and matrix effects may compromise metabolomic patterns. Recent increase in the use of qualitative metabolomic data, described by the presence (1) or absence (0) of particular metabolites, demonstrates great potential in the field of metabolomic profiling and fingerprint analysis. OBJECTIVES: The aim of this study is a comprehensive evaluation of binary similarity measures for the elucidation of patterns among samples of different botanical origin and various metabolomic profiles. METHODS: Nine qualitative metabolomic data sets covering a wide range of natural products and metabolomic profiles were applied to assess 44 binary similarity measures for the fingerprinting of plant extracts and natural products. The measures were analyzed by the novel sum of ranking differences method (SRD), searching for the most promising candidates. RESULTS: Baroni-Urbani-Buser (BUB) and Hawkins-Dotson (HD) similarity coefficients were selected as the best measures by SRD and analysis of variance (ANOVA), while Dice (Di1), Yule, Russel-Rao, and Consonni-Todeschini 3 ranked the worst. ANOVA revealed that concordantly and intermediately symmetric similarity coefficients are better candidates for metabolomic fingerprinting than the asymmetric and correlation based ones. The fingerprint analysis based on the BUB and HD coefficients and qualitative metabolomic data performed equally well as the quantitative metabolomic profile analysis. CONCLUSION: Fingerprint analysis based on the qualitative metabolomic profiles and binary similarity measures proved to be a reliable way in finding the same/similar patterns in metabolomic data as that extracted from quantitative data.

Analytical Methods in Tracing Honey Authenticity.

Honey is a precious natural product that is marketed with a wide range of nutritional and medicinal properties. However, it is also a product subjected to frequent adulteration through mislabeling and mixing with cheaper and lower-quality honeys and various sugar syrups. In that sense, honey authentication regarding its genuine botanical and geographical origins, as well as the detection of any adulteration, is essential in order to protect consumer health and to avoid competition that could create a destabilized market. Various analytical techniques have been developed to detect adulterations in honey, including measuring the ratios of stable isotopes (mostly 13C/12C) and the use of different spectroscopic, chromatographic, and electrochemical methods. This review aims to provide a cross-section of contemporary analytical methods used for the determination of honey authenticity in order to help the scientific community engaged in the field of honey chemistry make appropriate choices and select the best applications that should lead to improvements in the detection and elimination of fraudulent practices in honey manufacturing.

Long-Chain 4-Aminoquinolines as Quorum Sensing Inhibitors in Serratia marcescens and Pseudomonas aeruginosa.

Antibiotic resistance has become a serious global threat to public health; therefore, improved strategies and structurally novel antimicrobials are urgently needed to combat infectious diseases. Here we report a new type of highly potent 4-aminoquinoline derivatives as quorum sensing inhibitors in Serratia marcescens and Pseudomonas aeruginosa, exhibiting weak bactericidal activities (minimum inhibitory concentration (MIC) > 400 µM). Through detailed structure-activity study, we have identified 7-Cl and 7-CF3 substituted N-dodecylamino-4-aminoquinolines (5 and 10) as biofilm formation inhibitors with 50% biofilm inhibition at 69 µM and 63 µM in S. marcescens and P. aeruginosa, respectively. These two compounds, 5 and 10, are the first quinoline derivatives with anti-biofilm formation activity reported in S. marcescens. Quantitative structure-activity relationship (QSAR) analysis identified structural descriptors such as Wiener indices, hyper-distance-path index (HDPI), mean topological charge (MTC), topological charge index (TCI), and log D(o/w)exp as the most influential in biofilm inhibition in this bacterial species. Derivative 10 is one of the most potent quinoline type inhibitors of pyocyanin production described so far (IC50 = 2.5 µM). While we have demonstrated that 5 and 10 act as Pseudomonas quinolone system (PQS) antagonists, the mechanism of inhibition of S. marcescens biofilm formation with these compounds remains open since signaling similar to P. aeruginosa PQS system has not yet been described in Serratia and activity of these compounds on acylhomoserine lactone (AHL) signaling has not been detected. Our data show that 7-Cl and 7-CF3 substituted N-dodecylamino-4-aminoquinolines present the promising scaffolds for developing antivirulence and anti-biofilm formation agents against multidrug-resistant bacterial species.

Consensus-based comparison of chromatographic and computationally estimated lipophilicity of benzothiepino[3,2-c]pyridine derivatives as potential antifungal drugs.

Lipophilicity is one of the essential properties influencing drug absorption, excretion and metabolism. It is used for screening viable drug candidates. Chromatographic behavior of thiepino[3,2-c:6,7-c']dipyridine and 16 benzothiepino[3,2-c]pyridine derivatives as potential antifungal drugs was studied using thin-layer chromatography under typical reversed-phase conditions and two microemulsion chromatographic systems. Seventeen chromatographic and nine in silico lipophilicity measures were estimated. They were compared by classical multivariate approaches: principal component analysis, hierarchical cluster analysis, and ranked and grouped by the non-parametric method-Sum of ranking differences. Two computational and two chromatographic descriptors from the typical reversed-phase conditions using acetone/water mixtures emerged as the best candidates for lipophilicity estimation. The principal component scores related to typical reversed-phase conditions using dioxane/water were ranked as statistically insignificant (the worst). Microemulsion systems were positioned in between, performing worse than in silico estimates. Thiepine derivatives were ranked and grouped by sum of ranking differences, fusing multiple lipophilicity measures. In multicriteria maximization ranking, the compound substituted by phenyl group at position 8 was selected as the most lipophilic one. It is also the most active against Candida albicans. The ranking confirmed that introduction of phenyl core is essential for increasing the lipophilicity of the studied compounds.

How to compare separation selectivity of high-performance liquid chromatographic columns properly?

Comparison and selection of chromatographic columns is an important part of development as well as validation of analytical methods. Presently there is abundant number of methods for selection of the most similar and orthogonal columns, based on the application of limited number of test compounds as well as quantitative structure retention relationship models (QSRR), from among Snyder's hydrophobic-subtraction model (HSM) have been most extensively used. Chromatographic data of 67 compounds were evaluated using principal component analysis (PCA), hierarchical cluster analysis (HCA), non-parametric ranking methods as sum of ranking differences (SRD) and generalized pairwise correlation method (GPCM), both applied as a consensus driven comparison, and complemented by the comparison with one variable at a time (COVAT) approach. The aim was to compare the ability of the HSM approach and the approach based on primary retention data of test solutes (logk values) to differentiate among ten highly similar C18 columns. The ranking (clustering) pattern of chromatographic columns based on primary retention data and HSM parameters gave different results in all instances. Patterns based on retention coefficients were in accordance with expectations based on columns' physicochemical parameters, while HSM parameters provided a different clustering. Similarity indices calculated from the following dissimilarity measures: SRD, GPCM Fisher's conditional exact probability weighted (CEPW) scores; Euclidian, Manhattan, Chebyshev, and cosine distances; Pearson's, Spearman's, and Kendall's, correlation coefficients have been ranked by the consensus based SRD. Analysis of variance confirmed that the HSM model produced statistically significant increases of SRD values for the majority of similarity indices, i.e. HS transformation of original retention data yields significant loss of information, and finally results in lower performance of HSM methodology. The best similarity measures were obtained using primary retention data, and derived from Kendal's and Spearman's correlation coefficients, as well as GPCM and SRD score values. Selectivity function, Fs, originally proposed by Snyder, demonstrated moderate performance.

Linear modeling of the soil-water partition coefficient normalized to organic carbon content by reversed-phase thin-layer chromatography.

Soil-water partition coefficient normalized to the organic carbon content (KOC) is one of the crucial properties influencing the fate of organic compounds in the environment. Chromatographic methods are well established alternative for direct sorption techniques used for KOC determination. The present work proposes reversed-phase thin-layer chromatography (RP-TLC) as a simpler, yet equally accurate method as officially recommended HPLC technique. Several TLC systems were studied including octadecyl-(RP18) and cyano-(CN) modified silica layers in combination with methanol-water and acetonitrile-water mixtures as mobile phases. In total 50 compounds of different molecular shape, size, and various ability to establish specific interactions were selected (phenols, beznodiazepines, triazine herbicides, and polyaromatic hydrocarbons). Calibration set of 29 compounds with known logKOC values determined by sorption experiments was used to build simple univariate calibrations, Principal Component Regression (PCR) and Partial Least Squares (PLS) models between logKOC and TLC retention parameters. Models exhibit good statistical performance, indicating that CN-layers contribute better to logKOC modeling than RP18-silica. The most promising TLC methods, officially recommended HPLC method, and four in silico estimation approaches have been compared by non-parametric Sum of Ranking Differences approach (SRD). The best estimations of logKOC values were achieved by simple univariate calibration of TLC retention data involving CN-silica layers and moderate content of methanol (40-50%v/v). They were ranked far well compared to the officially recommended HPLC method which was ranked in the middle. The worst estimates have been obtained from in silico computations based on octanol-water partition coefficient. Linear Solvation Energy Relationship study revealed that increased polarity of CN-layers over RP18 in combination with methanol-water mixtures is the key to better modeling of logKOC through significant diminishing of dipolar and proton accepting influence of the mobile phase as well as enhancing molar refractivity in excess of the chromatographic systems.

Multivariate assessment of lipophilicity scales-computational and reversed phase thin-layer chromatographic indices.

Needs for fast, yet reliable means of assessing the lipophilicities of diverse compounds resulted in the development of various in silico and chromatographic approaches that are faster, cheaper, and greener compared to the traditional shake-flask method. However, at present no accepted "standard" approach exists for their comparison and selection of the most appropriate one(s). This is of utmost importance when it comes to the development of new lipophilicity indices, or the assessment of the lipophilicity of newly synthesized compounds. In this study, 50 well-known, diverse compounds of significant pharmaceutical and environmental importance have been selected and examined. Octanol-water partition coefficients have been measured with the shake-flask method for most of them. Their retentions have been studied in typical reversed thin-layer chromatographic systems, involving the most frequently employed stationary phases (octadecyl- and cyano-modified silica), and acetonitrile and methanol as mobile phase constituents. Twelve computationally estimated logP-s and twenty chromatographic indices together with the shake-flask octanol-water partition coefficient have been investigated with classical chemometric approaches-such as principal component analysis (PCA), hierarchical cluster analysis (HCA), Pearson's and Spearman's correlation matrices, as well as novel non-parametric methods: sum of ranking differences (SRD) and generalized pairwise correlation method (GPCM). Novel SRD and GPCM methods have been introduced based on the Comparisons with One VAriable (lipophilicity metric) at a Time (COVAT). For the visualization of COVAT results, a heatmap format was introduced. Analysis of variance (ANOVA) was applied to reveal the dominant factors between computational logPs and various chromatographic measures. In consensus-based comparisons, the shake-flask method performed the best, closely followed by computational estimates, while the chromatographic estimates often overlap with in silico assessments, mostly with methods involving octadecyl-modified silica stationary phases. The ones that employ cyano-modified silica perform generally worse. The introduction of alternative coloring schemes for the covariance matrices and SRD/GPCM heatmaps enables the discovery of intrinsic relationships among lipophilicity scales and the selection of best/worst measures. Closest to the recommended logKOW values are ClogP and the first principal component scores obtained on octadecyl-silica stationary phase in combination with methanol-water mobile phase, while the usage of slopes derived from Soczewinski-Matyisik equation should be avoided.

Towards better understanding of lipophilicity: assessment of in silico and chromatographic logP measures for pharmaceutically important compounds by nonparametric rankings.

Lipophilicity is one of the most frequently used physicochemical properties that affects compound solubility, determines its passive transport through biological membranes, influences biodistribution, metabolism and pharmacokinetics. We compared, ranked and grouped chromatographic lipophilicity indices and computationally estimated logP-s by sensitive and robust non-parametric approaches: sum of ranking differences (SRD) and generalized pairwise correlation method (GPCM). Chromatographic indices of fourteen neurotoxins and twenty one 1,2,4-triazole compounds have been derived from typical reversed-phase thin-layer chromatography and micellar chromatography. They were compared with in silico estimated logP-s. Under typical reversed-phase conditions, octadecyl-, octyl-, and cyanopropyl-modified silica have clear advantage over ethyl-, aminopropyl-, and diol-modified beds, i.e., the preferable choice of the stationary phase follows this order: octadecyl>octyl>cyanopropyl>ethyl>octadecylwettable>aminopropyl>diol. Many of these indices outperform the majority of computationally estimated logP-s. Clear distinction can be made based on cross-validation and statistical tests. Oppositely, micellar chromatography may not be successfully used for the lipophilicity assessment, since retention parameters obtained from the typical reversed-phase conditions outperform the parameters obtained by micellar chromatography. Both ranking approaches, SRD and GPCM, although based on different background, provide highly similar variable ordering and grouping leading to the same, above mentioned conclusions. However, GPCM results in more degeneracy, i.e., in some cases it cannot distinguish the lipophilicity parameters whereas SRD and its cross-validated version can. On the other hand GPCM produces a more characteristic grouping. Both methods can be successfully used for selection of the most and least appropriate lipophilicity measures.

Chromatographic and computational assessment of lipophilicity using sum of ranking differences and generalized pair-correlation.

Lipophilicity (logP) represents one of the most studied and most frequently used fundamental physicochemical properties. At present there are several possibilities for its quantitative expression and many of them stems from chromatographic experiments. Numerous attempts have been made to compare different computational methods, chromatographic methods vs. computational approaches, as well as chromatographic methods and direct shake-flask procedure without definite results or these findings are not accepted generally. In the present work numerous chromatographically derived lipophilicity measures in combination with diverse computational methods were ranked and clustered using the novel variable discrimination and ranking approaches based on the sum of ranking differences and the generalized pair correlation method. Available literature logP data measured on HILIC, and classical reversed-phase combining different classes of compounds have been compared with most frequently used multivariate data analysis techniques (principal component and hierarchical cluster analysis) as well as with the conclusions in the original sources. Chromatographic lipophilicity measures obtained under typical reversed-phase conditions outperform the majority of computationally estimated logPs. Oppositely, in the case of HILIC none of the many proposed chromatographic indices overcomes any of the computationally assessed logPs. Only two of them (logkmin and kmin) may be selected as recommended chromatographic lipophilicity measures. Both ranking approaches, sum of ranking differences and generalized pair correlation method, although based on different backgrounds, provides highly similar variable ordering and grouping leading to the same conclusions.