Revisiting thin-layer chromatography as a lipophilicity determination tool—A comparative study on several techniques with a model solute set

Komsta, Łukasz; Skibiński, Robert; Berecka, Anna; Gumieniczek, Anna; Radkiewicz, Beata; Radoń, Małgorzata

doi:10.1016/j.jpba.2010.06.024

Cited by 91 publications

(62 citation statements)

References 28 publications

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“…Aside from very specific applications of chromatographic approaches that tend to mimic biosystems such as micellar liquid chromatography (MLC) [10][11][12][13][14][15], immobilized artificial membrane chromatography (IAM) [16,17], immobilized proteins etc. [18], the mainstream methods in the determination of lipophilicity are still based on typical reversed-phase chromatography including a variety of chemically bonded stationary phases [19][20][21][22], where octyl-, octadecyl-, and cyanopropyl-modified silica beds are the most frequently used in combination with a polar mobile phase (usually binary mixtures of miscible organic solvents and water) [23][24][25].…”

Section: Introductionmentioning

confidence: 99%

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

Andrić

Bajusz

Rácz

et al. 2016

Journal of Pharmaceutical and Biomedical Analysis

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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 consensusbased 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 octadecylmodified 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 logK OW 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.

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Section: Introductionmentioning

confidence: 99%

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

Andrić

Bajusz

Rácz

et al. 2016

Journal of Pharmaceutical and Biomedical Analysis

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“…The extrapolated and values at pure water as mobile phase ( , 0 ) were used as the lipophilicity parameters. Both HPLC and TLC methods are used to determine the lipophilicity and to predict the relationship between molecular structure and its biological activity [3][4][5][6][7] . A linear relationships between the retention parameters and the concentration (ϕ) of organic modifier in the aqueous mobile phase has to be established for chromatographic measurement of lipophilicity and it can be represented as the dependence (1)…”

Section: Introductionmentioning

confidence: 99%

Determination of lipophilicity of some new 1,2,4-triazole derivatives by RP-HPLC and RP-TLC and calculated methods

Hawrył

Świeboda²,

Gawroński³

et al. 2015

10.5267/j.ccl

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Experimental and computational approaches were used to estimate the lipophilicity of novel 1,2,4-triazole derivatives. These derivatives have been subjected to this research, because they exhibit antimicrobial activity. The chromatographic analysis of RP-HPLC and RP-TLC was carried out using methanol-water or acetonitrile-water as mobile phase. The linear relationships between (or ) values and the concentration of organic modifier were obtained. The lipophilicity was expressed as chromatographically derived descriptors:, , ϕ0 and scores and corresponding to the first principal component. The experimental lipophilicity data have been compared with the computer calculated lipophilicity parameters ( ,ℎ ) of the same molecules. The matrices were created with or 0 and logP and they have been the subject of PCA analysis.

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“…This fact inspired us to previous parts of the study, where we decided to compare different modifiers, adsorbents and computational techniques on 35 model compounds with simple molecules. We have performed such study on RP18 (Part I, [23]), silica gel (Part II, [24]), and cyanopropyl adsorbent (Part III, [25]). The reader is referred to these papers for detailed literature background regarding older papers.…”

Section: Introductionmentioning

confidence: 99%

Revisiting thin-layer chromatography as a lipophilicity determination tool. Part IV — A closer look on extrapolation and averaging

Komsta

Gowin

2014

Acta Chromatographica

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Summary. The paper compares linear, quadratic, and cubical regression together with several weighted and robust approaches in the context of lipophilicity determination. The comparison is done on 35 model compounds on data from different modifiers used on RP18, CN, and silica plates. It can be concluded that the use of weighted and moderately robust regression technique increases correlation between extrapolated retention and real lipophilicity, whereas polynomial and very robust techniques give visibly worse results due to their excessive flexibility and higher extrapolation uncertainty. Additionally, we have compared averaging retention from different modifiers by R F , k, and R M values. The results are similar; however, surprisingly, R F averaging performs slightly better to the other approaches.

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Revisiting thin-layer chromatography as a lipophilicity determination tool—A comparative study on several techniques with a model solute set

Cited by 91 publications

References 28 publications

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

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

Determination of lipophilicity of some new 1,2,4-triazole derivatives by RP-HPLC and RP-TLC and calculated methods

Revisiting thin-layer chromatography as a lipophilicity determination tool. Part IV — A closer look on extrapolation and averaging

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