Fast Determination of Lipophilicity by HPLC

Ayouni, Linda; Cazorla, Georges; Chaillou, D.; Herbreteau, B.; Rudaz, Serge; Lantéri, Pierre; Carrupt, Pierre‐Alain

doi:10.1365/s10337-005-0608-6

Cited by 44 publications

(41 citation statements)

References 31 publications

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“…2.1. log P oct Determination on the 20-mm Discovery RP Amide C16 Column with a Conventional HPLC System. Based on the work of Ayouni et al [9], a 20-mm Discovery RP Amide C16 stationary phase was first investigated to widen the lipophilicity range up to 8. This column was tested as it mimics the octan-1-ol/H 2 O partitioning process (according to LSERs analysis [12] [13]), and good results were previously reported in terms of lipophilicity determination [12] [13].…”

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confidence: 99%

Lipophilicity Determination of Highly Lipophilic Compounds by Liquid Chromatography

Guillot¹,

Henchoz²,

Moccand³

et al. 2009

Chemistry & Biodiversity

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Different experimental strategies using short columns in both conventional liquid chromatography (HPLC) and ultra-high pressure liquid chromatography (UHPLC) were evaluated to allow, for the first time with these techniques, the lipophilicity determination of compounds with log P>5. Various organic modifiers, stationary phases, and elution modes were tested on 14 rigid compounds with a CLogP between 5 and 8, and 38 compounds with log P(oct) from 0 to 5. The best results in HPLC were obtained with the 20-mm Discovery RP Amide C16 stationary phase in isocratic mode using MeOH as organic modifier. To improve analysis time, the UHPLC approach was then evaluated. Consequently, a generic method was developed with a 30-mm Acquity BEH Shield RP18 column in gradient mode using MeOH as organic modifier, allowing a fourfold gain of time compared to the HPLC method, for the highly lipophilic compounds tested. Finally, the most rapid and accurate results were obtained with a 10-mm Hypersil GOLD Javelin HTS stationary phase in UHPLC, enabling an eightfold gain of time compared to the HPLC method.

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mentioning

confidence: 99%

Lipophilicity Determination of Highly Lipophilic Compounds by Liquid Chromatography

Guillot¹,

Henchoz²,

Moccand³

et al. 2009

Chemistry & Biodiversity

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“…Thus, in this case, the analysis time of 26 compounds including conditioning time, solvent change and data processing was reduced from 24 h using a 150 × 4.6 mm column to 14 h using a 20 × 4.6 mm column with an increase in quality of results (no extrapolation required). It was also verifi ed on this latter stationary phase that retention factors did not signifi cantly differ between the 150 × 4.6 and the 20 × 4 mm column [33] .…”

Section: Column Lengthmentioning

confidence: 76%

“…The use of 1 -octanol increased the correlation between extrapolated log k w and log P oct for a set of diverse compounds. Furthermore, comparing the two equations obtained with [33] and without [24] 1 -octanol showed that slopes of the linear correlations were slightly closer to unity when using 1 -octanol. However, preliminary studies evidenced that the presence of 1 -octanol in the mobile phase requires careful experimental designs, especially with longer conditioning times at least for Discovery ™ RP -amide -C 16 as stationary phase because the retention factors seem to decrease steadily before reaching a plateau [37] .…”

Section: Addition Of 1 -Octanol In the Mobile Phasementioning

confidence: 93%

“…This phenomenon is probably due to the stationary phase solvation which differs with the organic modifi er. However, recent studies on Discovery ™ RPamide -C 16 established a good correlation between nonextrapolated log w ne k , retention factors directly measured in 100% aqueous mobile phase and extrapolated log w e k , retention factors obtained by linear extrapolation of isocratic log k measured with different methanol -aqueous mobile phases [33] . Moreover quadratic extrapolated log k w values obtained from log k measured for the same compounds with acetonitrile -aqueous mobile phases were also well -correlated with non extrapo lated log w ne k , suggesting that extrapolated log k w using different organic modifi ers could be used with some specifi c stationary phases [34] in quantitative structure -property relationship analyses.…”

Section: Organic Modifi Ersmentioning

confidence: 98%

“…Moreover, according to stationary phases, retention factors can be obtained directly with an aqueous mobile phase with an acceptable analysis time for quite lipophilic compounds (log P oct up to 4) as recently shown with a Discovery ™ RP -amide -C 16 20 × 4 mm column [33] . Conversely, nonextrapolated values can be obtained only for a limited range (log P oct less than 1.5) when using Discovery ™ RP -amide -C 16 150 × 4 mm columns.…”

Section: Column Lengthmentioning

confidence: 99%

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Chromatographic Approaches for Measuring Log P

Martel

Guillarme

Henchoz

et al. 2007

Methods and Principles in Medicinal Chemistry

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AbbreviationsADMET absorption, distribution, metabolism, elimination and toxicity CE capillary electrophoresis CHI chromatographic hydrophobicity index IAM immobilized artifi cial membrane LC liguid chromatography LEKC/VEKC liposome/vesicular electrokinetic chromatography LSER linear solvation energy relationship LSS linear solvent strength MEEKC microemulsion electrokinetic chromatography MEKC micellar electrokinetic chromatography MS mass spectrometry ODP octadecyl polyvinyl ODS octadecylsilane OS octylsilane PC phosphatidylcholine QSAR quantitative structure -activity relationship RPLC reversed -phase liquid chromatography SDS sodium dodecyl sulfate UV ultraviolet Symbols S slope V D system dwell volume log P oct octanol -water partition coeffi cient 331 Molecular Drug Properties. Measurement and Prediction. R. Mannhold (Ed.)

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In Silico Tools and In Vitro HTS Approaches to Determine Lipophilicity During the Drug Discovery Process

Martel

Gasparik

Carrupt

2009

Hit and Lead Profiling

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Advances in rational drug design and combinatorial chemistry increased drastically the number of newly promising active compounds. As inappropriate pharmacokinetics (PK) was recognized as one of the major factors leading to the withdrawal of new chemical entities (NCEs) from drug development [1,2], efficient in silico and in vitro models were developed to replace in vivo studies for absorption, distribution, metabolism, excretion (ADME) and toxicity (T) in the early phases of drug research [3]. The large number of approaches offering suitable estimates of ADMET properties in the early stages of drug discovery has been extensively reviewed [4][5][6][7][8][9][10][11]. These approaches used largely (Q)SAR models based on physicochemical parameters such as solubility, ionization and lipophilicity. Thus these fundamental physicochemical properties have to be estimated early in drug discovery programs to filter out unsuitable compounds and to rank validated hits in order to select the most promising compounds according to their pharmacodynamic and pharmacokinetic profiles. As the paradigms of hit-like [12,13], lead-like [13][14][15][16] or drug-like properties [17][18][19][20][21][22][23][24] are governing the research, considerable efforts are still carried out to develop efficient virtual and experimental filters to reduce large chemical databases to smaller collections of compounds with suitable PK properties for an in vivo high therapeutic potency [25].Among the physicochemical properties involved in ADMET profiling, lipophilicity has a place of choice as the major contributor to solubility, membrane permeation and protein binding [26,27], metabolism and the ability to reach and to bind the targeted receptors [28]. This predominant position is well illustrated by numerous papers devoted to this topic (for recent reviews, see [6,11,29,30]). To overcome the limitations of the time-consuming traditional methods such as the shake-flask, potentiometry (for ionizable compounds) and cyclic voltammetry (for ions only), a number of in silico and experimental high-throughput techniques Hit and Lead Profiling. Edited by Bernard Faller and Laszlo Urban j91 emerged. The scope of this chapter is to review these HTS methods for log P and log D determination in the 1-octanol/water system and in other solvent/water systems useful in the early stages of drug discovery. 5.2Virtual Filtering: In Silico Prediction of log P and log D Among the large number of existing lipophilicity parameters [31], the descriptor frequently estimated by in silico methods is the partition coefficient of a solute between 1-octanol and water, expressed as log P oct [32]. However, lipophilicity determination in different solvent systems, such as alkane/water system, proved its utility in (Q)SAR studies and therefore some predictive methods also emerged in this field. Many publically available databases include numerous experimental values collected through the literature; the quality of the experimental data represents the cornerstone of most of the models ...

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Fast Determination of Lipophilicity by HPLC

Cited by 44 publications

References 31 publications

Lipophilicity Determination of Highly Lipophilic Compounds by Liquid Chromatography

Lipophilicity Determination of Highly Lipophilic Compounds by Liquid Chromatography

Chromatographic Approaches for Measuring Log P

In Silico Tools and In Vitro HTS Approaches to Determine Lipophilicity During the Drug Discovery Process

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