TY  - JOUR
AU  - Andrić, Filip
AU  - Bajusz, David
AU  - Racz, Anita
AU  - Šegan, Sandra B.
AU  - Héberger, Karoly
PY  - 2016
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/2270
AB  - 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 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. (C) 2016 Elsevier B.V. All rights reserved.
PB  - Elsevier Science Bv, Amsterdam
T2  - Journal of Pharmaceutical and Biomedical Analysis
T1  - Multivariate assessment of lipophilicity scales-computational and reversed phase thin-layer chromatographic indices
VL  - 127
SP  - 81
EP  - 93
DO  - 10.1016/j.jpba.2016.04.001
ER  - 

@article{
author = "Andrić, Filip and Bajusz, David and Racz, Anita and Šegan, Sandra B. and Héberger, Karoly",
year = "2016",
abstract = "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 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. (C) 2016 Elsevier B.V. All rights reserved.",
publisher = "Elsevier Science Bv, Amsterdam",
journal = "Journal of Pharmaceutical and Biomedical Analysis",
title = "Multivariate assessment of lipophilicity scales-computational and reversed phase thin-layer chromatographic indices",
volume = "127",
pages = "81-93",
doi = "10.1016/j.jpba.2016.04.001"
}

Andrić, F., Bajusz, D., Racz, A., Šegan, S. B.,& Héberger, K.. (2016). Multivariate assessment of lipophilicity scales-computational and reversed phase thin-layer chromatographic indices. in Journal of Pharmaceutical and Biomedical Analysis
Elsevier Science Bv, Amsterdam., 127, 81-93.
https://doi.org/10.1016/j.jpba.2016.04.001

Andrić F, Bajusz D, Racz A, Šegan SB, Héberger K. Multivariate assessment of lipophilicity scales-computational and reversed phase thin-layer chromatographic indices. in Journal of Pharmaceutical and Biomedical Analysis. 2016;127:81-93.
doi:10.1016/j.jpba.2016.04.001 .

Andrić, Filip, Bajusz, David, Racz, Anita, Šegan, Sandra B., Héberger, Karoly, "Multivariate assessment of lipophilicity scales-computational and reversed phase thin-layer chromatographic indices" in Journal of Pharmaceutical and Biomedical Analysis, 127 (2016):81-93,
https://doi.org/10.1016/j.jpba.2016.04.001 . .

TY  - JOUR
AU  - Andrić, Filip
AU  - Bajusz, David
AU  - Racz, Anita
AU  - Šegan, Sandra B.
AU  - Héberger, Karoly
PY  - 2016
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/3576
AB  - 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 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. (C) 2016 Elsevier B.V. All rights reserved.
PB  - Elsevier Science Bv, Amsterdam
T2  - Journal of Pharmaceutical and Biomedical Analysis
T1  - Multivariate assessment of lipophilicity scales-computational and reversed phase thin-layer chromatographic indices
VL  - 127
SP  - 81
EP  - 93
DO  - 10.1016/j.jpba.2016.04.001
ER  - 

@article{
author = "Andrić, Filip and Bajusz, David and Racz, Anita and Šegan, Sandra B. and Héberger, Karoly",
year = "2016",
abstract = "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 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. (C) 2016 Elsevier B.V. All rights reserved.",
publisher = "Elsevier Science Bv, Amsterdam",
journal = "Journal of Pharmaceutical and Biomedical Analysis",
title = "Multivariate assessment of lipophilicity scales-computational and reversed phase thin-layer chromatographic indices",
volume = "127",
pages = "81-93",
doi = "10.1016/j.jpba.2016.04.001"
}

Andrić, F., Bajusz, D., Racz, A., Šegan, S. B.,& Héberger, K.. (2016). Multivariate assessment of lipophilicity scales-computational and reversed phase thin-layer chromatographic indices. in Journal of Pharmaceutical and Biomedical Analysis
Elsevier Science Bv, Amsterdam., 127, 81-93.
https://doi.org/10.1016/j.jpba.2016.04.001

Andrić F, Bajusz D, Racz A, Šegan SB, Héberger K. Multivariate assessment of lipophilicity scales-computational and reversed phase thin-layer chromatographic indices. in Journal of Pharmaceutical and Biomedical Analysis. 2016;127:81-93.
doi:10.1016/j.jpba.2016.04.001 .

Andrić, Filip, Bajusz, David, Racz, Anita, Šegan, Sandra B., Héberger, Karoly, "Multivariate assessment of lipophilicity scales-computational and reversed phase thin-layer chromatographic indices" in Journal of Pharmaceutical and Biomedical Analysis, 127 (2016):81-93,
https://doi.org/10.1016/j.jpba.2016.04.001 . .

TY  - DATA
AU  - Andrić, Filip
AU  - Bajusz, David
AU  - Racz, Anita
AU  - Šegan, Sandra B.
AU  - Héberger, Karoly
PY  - 2016
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/3577
PB  - Elsevier Science Bv, Amsterdam
T2  - Journal of Pharmaceutical and Biomedical Analysis
T1  - Supplementary data for the article: Andrić, F.; Bajusz, D.; Rácz, A.; Šegan, S.; Héberger, K. Multivariate Assessment of Lipophilicity Scales—Computational and Reversed Phase Thin-Layer Chromatographic Indices. J. Pharm. Biomed. Anal. 2016, 127, 81–93. https://doi.org/10.1016/j.jpba.2016.04.001
UR  - https://hdl.handle.net/21.15107/rcub_cherry_3577
ER  - 

@misc{
author = "Andrić, Filip and Bajusz, David and Racz, Anita and Šegan, Sandra B. and Héberger, Karoly",
year = "2016",
publisher = "Elsevier Science Bv, Amsterdam",
journal = "Journal of Pharmaceutical and Biomedical Analysis",
title = "Supplementary data for the article: Andrić, F.; Bajusz, D.; Rácz, A.; Šegan, S.; Héberger, K. Multivariate Assessment of Lipophilicity Scales—Computational and Reversed Phase Thin-Layer Chromatographic Indices. J. Pharm. Biomed. Anal. 2016, 127, 81–93. https://doi.org/10.1016/j.jpba.2016.04.001",
url = "https://hdl.handle.net/21.15107/rcub_cherry_3577"
}

Andrić, F., Bajusz, D., Racz, A., Šegan, S. B.,& Héberger, K.. (2016). Supplementary data for the article: Andrić, F.; Bajusz, D.; Rácz, A.; Šegan, S.; Héberger, K. Multivariate Assessment of Lipophilicity Scales—Computational and Reversed Phase Thin-Layer Chromatographic Indices. J. Pharm. Biomed. Anal. 2016, 127, 81–93. https://doi.org/10.1016/j.jpba.2016.04.001. in Journal of Pharmaceutical and Biomedical Analysis
Elsevier Science Bv, Amsterdam..
https://hdl.handle.net/21.15107/rcub_cherry_3577

Andrić F, Bajusz D, Racz A, Šegan SB, Héberger K. Supplementary data for the article: Andrić, F.; Bajusz, D.; Rácz, A.; Šegan, S.; Héberger, K. Multivariate Assessment of Lipophilicity Scales—Computational and Reversed Phase Thin-Layer Chromatographic Indices. J. Pharm. Biomed. Anal. 2016, 127, 81–93. https://doi.org/10.1016/j.jpba.2016.04.001. in Journal of Pharmaceutical and Biomedical Analysis. 2016;.
https://hdl.handle.net/21.15107/rcub_cherry_3577 .

Andrić, Filip, Bajusz, David, Racz, Anita, Šegan, Sandra B., Héberger, Karoly, "Supplementary data for the article: Andrić, F.; Bajusz, D.; Rácz, A.; Šegan, S.; Héberger, K. Multivariate Assessment of Lipophilicity Scales—Computational and Reversed Phase Thin-Layer Chromatographic Indices. J. Pharm. Biomed. Anal. 2016, 127, 81–93. https://doi.org/10.1016/j.jpba.2016.04.001" in Journal of Pharmaceutical and Biomedical Analysis (2016),
https://hdl.handle.net/21.15107/rcub_cherry_3577 .

TY  - DATA
AU  - Andrić, Filip
AU  - Héberger, Karoly
PY  - 2015
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/3456
PB  - Elsevier Science Bv, Amsterdam
T2  - Journal of Pharmaceutical and Biomedical Analysis
T1  - Supplementary data for article: Andrić, F.; Héberger, K. Towards Better Understanding of Lipophilicity: Assessment of in Silico and Chromatographic LogP Measures for Pharmaceutically Important Compounds by Nonparametric Rankings. Journal of Pharmaceutical and Biomedical Analysis 2015, 115, 183–191. https://doi.org/10.1016/j.jpba.2015.07.006
UR  - https://hdl.handle.net/21.15107/rcub_cherry_3456
ER  - 

@misc{
author = "Andrić, Filip and Héberger, Karoly",
year = "2015",
publisher = "Elsevier Science Bv, Amsterdam",
journal = "Journal of Pharmaceutical and Biomedical Analysis",
title = "Supplementary data for article: Andrić, F.; Héberger, K. Towards Better Understanding of Lipophilicity: Assessment of in Silico and Chromatographic LogP Measures for Pharmaceutically Important Compounds by Nonparametric Rankings. Journal of Pharmaceutical and Biomedical Analysis 2015, 115, 183–191. https://doi.org/10.1016/j.jpba.2015.07.006",
url = "https://hdl.handle.net/21.15107/rcub_cherry_3456"
}

Andrić, F.,& Héberger, K.. (2015). Supplementary data for article: Andrić, F.; Héberger, K. Towards Better Understanding of Lipophilicity: Assessment of in Silico and Chromatographic LogP Measures for Pharmaceutically Important Compounds by Nonparametric Rankings. Journal of Pharmaceutical and Biomedical Analysis 2015, 115, 183–191. https://doi.org/10.1016/j.jpba.2015.07.006. in Journal of Pharmaceutical and Biomedical Analysis
Elsevier Science Bv, Amsterdam..
https://hdl.handle.net/21.15107/rcub_cherry_3456

Andrić F, Héberger K. Supplementary data for article: Andrić, F.; Héberger, K. Towards Better Understanding of Lipophilicity: Assessment of in Silico and Chromatographic LogP Measures for Pharmaceutically Important Compounds by Nonparametric Rankings. Journal of Pharmaceutical and Biomedical Analysis 2015, 115, 183–191. https://doi.org/10.1016/j.jpba.2015.07.006. in Journal of Pharmaceutical and Biomedical Analysis. 2015;.
https://hdl.handle.net/21.15107/rcub_cherry_3456 .

Andrić, Filip, Héberger, Karoly, "Supplementary data for article: Andrić, F.; Héberger, K. Towards Better Understanding of Lipophilicity: Assessment of in Silico and Chromatographic LogP Measures for Pharmaceutically Important Compounds by Nonparametric Rankings. Journal of Pharmaceutical and Biomedical Analysis 2015, 115, 183–191. https://doi.org/10.1016/j.jpba.2015.07.006" in Journal of Pharmaceutical and Biomedical Analysis (2015),
https://hdl.handle.net/21.15107/rcub_cherry_3456 .

TY  - JOUR
AU  - Andrić, Filip
AU  - Héberger, Karoly
PY  - 2015
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/1987
AB  - 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  gt  octyl  gt  cyanopropyl  gt  ethyl  gt  octadecyl wettable  gt  aminopropyl  gt  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.
PB  - Elsevier Science Bv, Amsterdam
T2  - Journal of Pharmaceutical and Biomedical Analysis
T1  - Towards better understanding of lipophilicity: Assessment of in silico and chromatographic logP measures for pharmaceutically important compounds by nonparametric rankings
VL  - 115
SP  - 183
EP  - 191
DO  - 10.1016/j.jpba.2015.07.006
ER  - 

@article{
author = "Andrić, Filip and Héberger, Karoly",
year = "2015",
abstract = "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  gt  octyl  gt  cyanopropyl  gt  ethyl  gt  octadecyl wettable  gt  aminopropyl  gt  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.",
publisher = "Elsevier Science Bv, Amsterdam",
journal = "Journal of Pharmaceutical and Biomedical Analysis",
title = "Towards better understanding of lipophilicity: Assessment of in silico and chromatographic logP measures for pharmaceutically important compounds by nonparametric rankings",
volume = "115",
pages = "183-191",
doi = "10.1016/j.jpba.2015.07.006"
}

Andrić, F.,& Héberger, K.. (2015). Towards better understanding of lipophilicity: Assessment of in silico and chromatographic logP measures for pharmaceutically important compounds by nonparametric rankings. in Journal of Pharmaceutical and Biomedical Analysis
Elsevier Science Bv, Amsterdam., 115, 183-191.
https://doi.org/10.1016/j.jpba.2015.07.006

Andrić F, Héberger K. Towards better understanding of lipophilicity: Assessment of in silico and chromatographic logP measures for pharmaceutically important compounds by nonparametric rankings. in Journal of Pharmaceutical and Biomedical Analysis. 2015;115:183-191.
doi:10.1016/j.jpba.2015.07.006 .

Andrić, Filip, Héberger, Karoly, "Towards better understanding of lipophilicity: Assessment of in silico and chromatographic logP measures for pharmaceutically important compounds by nonparametric rankings" in Journal of Pharmaceutical and Biomedical Analysis, 115 (2015):183-191,
https://doi.org/10.1016/j.jpba.2015.07.006 . .