<p>Lipophilicity is considered one of the most critical physicochemical properties as it significantly impacts the biological activity and pharmacokinetics of drug molecules. It can be determined by experimental methods as well as by computational methods on the basis of the application of different software packages. In this paper, the retention behavior of 17 synthesized morpholino propiophenone derivatives in four reversed-phase thin-layer chromatography (RP-TLC) systems (tetrahydrofuran‒water, acetonitrile‒water, ethanol‒water, and acetone‒water) is presented, and the chromatography parameters <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="764_2025_356_Article_IEq1.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="28" /> </InlineMediaObject> <EquationSource Format="TEX">\(R_{M}^{0}\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>R</mi> <mrow> <mi>M</mi> </mrow> <mn>0</mn> </msubsup> </math></EquationSource> </InlineEquation>, <i>S</i> and<i> C</i><sub><i>0</i></sub> were determined. The most suitable RP-TLC system (acetone‒water) and chromatography parameter (<InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="764_2025_356_Article_IEq1.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="28" /> </InlineMediaObject> <EquationSource Format="TEX">\(R_{M}^{0}\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>R</mi> <mrow> <mi>M</mi> </mrow> <mn>0</mn> </msubsup> </math></EquationSource> </InlineEquation>) for the lipophilicity prediction of the tested compounds was selected on the basis of the highest correlations with the calculated logP values. In this system, compounds <b>11</b> and <b>16</b> (derivatives with –OH as substituent in ring B) had the lowest, while compounds <b>4</b>, <b>6</b>, and <b>7</b> (with two halogen substituents) had the highest values of <i>R</i><sub>M</sub><sup>0</sup>. Quantitative structure‒retention relationship (QSRR) analysis was performed, and six models (OLS1(<InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="764_2025_356_Article_IEq1.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="28" /> </InlineMediaObject> <EquationSource Format="TEX">\(R_{M}^{0}\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>R</mi> <mrow> <mi>M</mi> </mrow> <mn>0</mn> </msubsup> </math></EquationSource> </InlineEquation>), OLS2(<InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="764_2025_356_Article_IEq1.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="28" /> </InlineMediaObject> <EquationSource Format="TEX">\(R_{M}^{0}\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>R</mi> <mrow> <mi>M</mi> </mrow> <mn>0</mn> </msubsup> </math></EquationSource> </InlineEquation>), PLS1(<InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="764_2025_356_Article_IEq1.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="28" /> </InlineMediaObject> <EquationSource Format="TEX">\(R_{M}^{0}\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>R</mi> <mrow> <mi>M</mi> </mrow> <mn>0</mn> </msubsup> </math></EquationSource> </InlineEquation>), PLS2(<InlineEquation ID="IEq6"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="764_2025_356_Article_IEq1.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="28" /> </InlineMediaObject> <EquationSource Format="TEX">\(R_{M}^{0}\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>R</mi> <mrow> <mi>M</mi> </mrow> <mn>0</mn> </msubsup> </math></EquationSource> </InlineEquation>), SVM1(<InlineEquation ID="IEq7"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="764_2025_356_Article_IEq1.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="28" /> </InlineMediaObject> <EquationSource Format="TEX">\(R_{M}^{0}\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>R</mi> <mrow> <mi>M</mi> </mrow> <mn>0</mn> </msubsup> </math></EquationSource> </InlineEquation>), and SVM2(<InlineEquation ID="IEq8"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="764_2025_356_Article_IEq1.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="28" /> </InlineMediaObject> <EquationSource Format="TEX">\(R_{M}^{0}\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mi>R</mi> <mrow> <mi>M</mi> </mrow> <mn>0</mn> </msubsup> </math></EquationSource> </InlineEquation>)) were created to represent the relationships between <i>R</i><sub>M</sub><sup>0</sup> and selected molecular descriptors. The molecular descriptors that form five most reliable models (<i>ALOGP2, CATS2D_07_AL, Am</i>, <i>CATS2D_02_AL, RDF110m, DISPm</i>, and <i>CATS3D_03_LL</i>) prove the existence of the relationship between lipophilicity and retention behavior in the selected RP-TLC system and indicate the importance of the selection of substituents in ring B.</p>

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Evaluation of the lipophilicity of morpholino propiophenones by reversed-phase thin-layer chromatography and computational methods

  • Nastasija Anđelković,
  • Miloš Marić,
  • Vladimir Dobričić,
  • Milkica Crevar,
  • Branka Ivković

摘要

Lipophilicity is considered one of the most critical physicochemical properties as it significantly impacts the biological activity and pharmacokinetics of drug molecules. It can be determined by experimental methods as well as by computational methods on the basis of the application of different software packages. In this paper, the retention behavior of 17 synthesized morpholino propiophenone derivatives in four reversed-phase thin-layer chromatography (RP-TLC) systems (tetrahydrofuran‒water, acetonitrile‒water, ethanol‒water, and acetone‒water) is presented, and the chromatography parameters \(R_{M}^{0}\) R M 0 , S and C0 were determined. The most suitable RP-TLC system (acetone‒water) and chromatography parameter ( \(R_{M}^{0}\) R M 0 ) for the lipophilicity prediction of the tested compounds was selected on the basis of the highest correlations with the calculated logP values. In this system, compounds 11 and 16 (derivatives with –OH as substituent in ring B) had the lowest, while compounds 4, 6, and 7 (with two halogen substituents) had the highest values of RM0. Quantitative structure‒retention relationship (QSRR) analysis was performed, and six models (OLS1( \(R_{M}^{0}\) R M 0 ), OLS2( \(R_{M}^{0}\) R M 0 ), PLS1( \(R_{M}^{0}\) R M 0 ), PLS2( \(R_{M}^{0}\) R M 0 ), SVM1( \(R_{M}^{0}\) R M 0 ), and SVM2( \(R_{M}^{0}\) R M 0 )) were created to represent the relationships between RM0 and selected molecular descriptors. The molecular descriptors that form five most reliable models (ALOGP2, CATS2D_07_AL, Am, CATS2D_02_AL, RDF110m, DISPm, and CATS3D_03_LL) prove the existence of the relationship between lipophilicity and retention behavior in the selected RP-TLC system and indicate the importance of the selection of substituents in ring B.