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Original Articles

USE OF RP-TLC AND THEORETICAL COMPUTATIONAL METHODS TO COMPARE THE LIPOPHILICITY OF SALICYLIC ACID AND ITS DERIVATIVES

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Pages 179-190 | Published online: 29 Dec 2009
 

Abstract

Salicylic acid (SA) and its derivatives, namely acetylsalicylic acid (ASA), salicylanilide (SAND), salicylaldehyde (SALD), salicylamide (SAMD), salicylhydroxamic acid (SHXA), methyl salicylate (MS), phenyl salicylate (PS), 3,5-dinitrosalicylic acid (3,5-DNSA), 2,5-dihydroxybenzoic acid (2,5-DHBA), 3-aminosalicylic acid (3-AMSA), 4-aminosalicylic acid (4-AMSA), and 5-aminosalicylic acid (5-AMSA) were investigated with the use of reversed phase thin layer chromatography on RP8 F254, RP18 F254s, RP18 W, and CN (E. Merck), using methanol-water in different volume compositions as a mobile phase. The chromatographic parameters of lipophilicity (RMw(RP8), RMw(RP18), RMw(RP18W), and RMw(CN)) of the studied compounds were determined. Lipophilic parameters (RMw(RP8), RMw(RP18), RMw(RP18W), and RMw(CN) were compared, both with measured (log Pexp), and calculated partition coefficients (Alog Ps, AClog P, AB/log P, COSMOFrag, miLog P, Alog P, mlog P, KOWWIN, xlog P2, and xlog P3). Similarity analysis indicates that the chromatographic parameters of lipophilicity RMw(RP8), and RMw(CN) are more appropriate for the experimental n-octanol-water partition coefficient. Comparing all calculation procedures, generally miLog P is more appropriate for the chromatographic parameter of lipophilicities RMW(RP8) and RMW(CN), as well as the experimental n-octanol-water partition coefficient of the studied compounds. The results indicate that the chromatographic parameter of lipophilicity determined on RP8 F254s and CN plates may be used as a measure of lipophilicity of the investigated salicylic acid and its derivatives.

ACKNOWLEDGMENT

This research was financed by the Medical University of Silesia as part of statutory research project KNW-1-005/09.

Notes

Where: SE – standard error; n – number of points to drive the particular regression equation; r – correlation coefficient; SEE – standard error of the estimation; F - the values of the Fisher test; for all regression equation the significance level (p) is <0.0001.

Where: SE – standard error; n – number of points to drive the particular regression equation; r – correlation coefficient; SEE – standard error of the estimation; F – the values of the Fisher test; for all regression equation the significance level (p) is <0.0001.

Where: SE – standard error; n – number of points to drive the particular regression equation; r – correlation coefficient; SEE – standard error of the estimation; F – the values of the Fisher test; for all regression equation the significance level (p) is <0.0001.

where: SE – standard error; n – number of points to drive the particular regression equation; r – correlation coefficient; SEE – standard error of the estimation; F – the values of the Fisher test; for all regression equation the significance level (p) is <0.0001.

a n = 9 for log Pexp.

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