Into the first biomimetic sphingomyelin stationary phase: Suitability in drugs’ biopharmaceutic profiling and block relevance analysis of selectivity

Immobilised artificial membrane liquid chromatography vs liposome electrokinetic capillary chromatography: Suitability in drug/bio membrane partitioning studies and effectiveness in the assessment of the passage of drugs through the respiratory mucosa

This study pioneers a comparison of the application of biomimetic techniques, immobilised artificial membrane liquid chromatography (IAM LC) and liposome electrokinetic capillary chromatography (LEKC), for the prediction of pulmonary drug permeability. The pulmonary absorption profiles of 26 structurally unrelated drug-like molecules were evaluated using their IAM hydrophobicity index (CHI IAM) measured in IAM LC, and the logarithm of distribution constants (log KLEKC) derived from the LEKC experiments. Lipophilicity (phospholipids) parameters obtained from IAM LC and most LEKC analyses were linearly related to the n-octanol/water partitioning coefficients of the neutral forms (i.e., log Po/w values) to a moderate extent. However, the relationship with distribution coefficients at the experimental pH (7.4) (i.e., log D7.4) were weaker overall for IAM LC data and sigmoidal for some liposome compositions (phosphatidyl choline (PC): phosphatidyl inositol (PI) 85:15 mol% and 90:10 mol%) and concentrations (4 mM) in LEKC. This suggests that phospholipid partitioning supports both hydrophobic and electrostatic interactions occurring between ionised drugs and charged phospholipid moieties. The latter interactions are original when compared to those taking place in the more established n-octanol/water partitioning systems. A stronger correlation (R2 > 0.65) was identified between the LEKC retention parameters, and the experimental apparent lung permeability (i.e., log Papp values) as opposed to the values obtained by IAM LC. Therefore, LEKC offers unprecedented advantages over IAM LC in simulating cell membrane partitioning processes in the pulmonary delivery of drugs. Although LEKC has the advantage of more effectively simulating the electrostatic and hydrophobic forces in drug/pulmonary membrane interactions in vitro, the technique is unsuitable for analysing highly hydrophilic neutral or anionic compounds at the experimental pH. Conversely, IAM LC is useful for analysing compounds spanning a wider range of lipophilicity. Its simpler and more robust implementation, and propensity for high-throughput automation make it a favourable choice for researchers in drug development and pharmacological studies.

Recent developments in the application of immobilized artificial membrane (IAM) chromatography to drug discovery

INTRODUCTION

Immobilized artificial membrane (IAM) chromatography is widely used in many aspects of drug discovery. It employs stationary phases, which contain phospholipids combining simulation of biological membranes with rapid measurements.

AREAS COVERED

Advances in IAM stationary phases, chromatographic conditions and the underlying retention mechanism are discussed. The potential of IAM chromatography to model permeability and drug-membrane interactions as well as its use to estimate pharmacokinetic properties and toxicity endpoints including ecotoxicity, is outlined. Efforts to construct models for prediction IAM retention factors are presented.

EXPERT OPINION

IAM chromatography, as a border case between partitioning and binding, has broadened its application from permeability studies to encompass processes involving tissue binding. Most IAM-based permeability models are hybrid models incorporating additional molecular descriptors, while for the estimation of pharmacokinetic properties and binding to off targets, IAM retention is combined with other biomimetic properties. However, for its integration into routine drug discovery protocols, reliable IAM prediction models implemented in relevant software should be developed, to enable its use in virtual screening and the design of new molecules. Conversely, preparation of new IAM columns with different phospholipids or mixed monomers offers enhanced flexibility and the potential to tailor the conditions according to the target property.

Into the toxicity potential of an array of parabens by biomimetic liquid chromatography, cell viability assessments and in silico predictions

Five parabens (PBs) i.e., Methylparaben (MP), Ethylparaben (EP), Isopropylparaben (iPrP), Isobutylparaben (iBuP), Benzylparaben (BzP), and their parent compound i.e., para-hydroxy Benzoic Acid (pHBA), were studied both in vitro and in silico. Specifically, we determined their retention on several both protein- (Human Serum Albumin and α1-acidic glycoprotein) and (phospho) lipid- (immobilized artificial membrane (IAM)) based biomimetic stationary phases to evaluate their penetration potential through the biomembranes and their possible distribution in the body. The IAM phases were based either on phosphatidylcholine (PC) analogues i.e., PC.MG and PC.DD2 or on sphingomyelin (SPH). We also assessed their viability effect on breast cancer cells (MCF-7) via MTT assay subjecting the cells to five different PB concentrations i.e., 100 μM, 10 μM, 1 μM, 0.1 μM and 0.01 μM. Finally, their pharmacokinetics and toxicity were assessed by the ADMET Predictor™ software. Isopropylparaben was found to be more active than 17β estradiol (E2) employed as positive control, on the screened cell line inducing cell proliferation up to 150 % more of untreated cells. Other analogues showed only a slight/moderate cell proliferation activity, with parabens having longer/branched side chain showing, on average, a higher proliferation rate. Significant linear direct relationships (for PC.DD2 r2 = 0.89, q2 = 0.86, for SPH r2 = 0.89, q2 = 0.85, for both P value < 0.05) were observed between the difference in proliferative effect between the readout and the control at 0.01 μM concentration and the retention on the IAM phases measured at pH 5.0 for all compounds but pHBA, which is the only analyte of the dataset supporting a carboxylic acid moiety. IAM affinity data measured at pH 7.0 were found to be related to the effective human jejunal permeability as predicted by the software ADMET® Predictor, which is relevant when PBs are added to pharmaceutical and food commodities.

Potential of liposomes and lipid membranes for the separation of β-blockers by capillary electromigration and liquid chromatographic techniques

β-Blockers belong to a frequently used class of drugs primarily used to treat heart and circulatory conditions. Here we describe the use of lipid vesicles and liposomes as cell membrane biomimicking models in capillary electromigration (CE) and liquid chromatography (LC) techniques for the investigation of interactions between lipid membranes and β-blockers. In addition to liposomes, the use of commercial intravenous lipid emulsions, and their interactions with β-blockers are also discussed. Different CE and LC instrumental techniques designed for these purposes are introduced. Other methodologies for studying interactions between β-blockers and lipid membranes are also briefly discussed, and the different methodologies are compared. The aim is to give the reader a good overview on the status of the use of liposomes and lipids in CE and LC for studying β-blocker interactions.

cΔlog kw IAM: can we afford estimation of small molecules' blood-brain barrier passage based upon in silico phospholipophilicity?

56 compounds, whose log BB values were known from the scientific literature, were considered and their phospholipophilicity values were calculated in silico. These values, along with either experimentally determined or calculated lipophilicity values, were used to extract cΔ/Δ'log k w IAM parameters. cΔ/Δ'log k w IAM values were found inversely related to data of blood-brain barrier passage, especially in the < -0.20 log BB range and on the IAM.PC.DD2 phase (r2 = 0.79). In multiple linear regression, satisfactory statistic models (r2 (n-1) = 0.76), based on cΔ/Δ'log k w IAM.MG along with other in silico calculated descriptors, were achieved. This method brings the potential to be applied, along with other methodologies, to filter out solutes whose BBB permeation is foreseen to be substandard, thus allowing pharmaceutical companies/research institutes to focus on candidates that are more likely to concentrate in the brain.

Characterization of the new CelerisTM Arginine column: Retentive behaviour through a combination of chemometric tools and potential in drug analysis

Celeris^TM Arginine (ARG) is a mixed-mode stationary phase recently released on the market. To characterize its analytical behavior, the retention factors of a pool (n=100, of which 36 neutrals, 26 acids and 38 bases) of pharmaceutically relevant compounds have been measured on this phase over eight percentages (from 10 to 90% v/v) of acetonitrile (MeCN) as organic modifier. The ARG phase exhibited enhanced affinity for the molecules that are in their anionic form at the experimental pH, whilst basic compounds, albeit over a wide range of lipophilicity and pK_a values, were on average poorly retained. To dissect the separation mechanism of the ARG phase, the overall analytical retention has been deconvoluted into the individual contributions of intermolecular forces by a QSPR/ Partial Least Square (PLS)/Block Relevance (BR) analysis tool recently developed by us. For the neutrals, the most relevant blocks were found to be Size, describing the interaction due to the dimension of the molecule, and O, representing the solute's hydrogen bond donor properties. The change in sign from positive to negative of the Size block, which occurs between 10% and 20% MeCN, allowed to visually appreciate the switch in the separation mode from reversed phase to normal phase. Some good statistic models for rationalizing the analytical behaviour of neutrals were developed from VS+ descriptors. However, their performance in modelling the analytical retention of acids was substandard, probably due to the intrinsic inefficacy of VS+ descriptors in handling electric charges. This instance was addressed by a complimentary MLR strategy, which led to successfully model the retention of acids on the ARG column and to shed light into their retention mechanism, which seemed to be substantially driven by electrostatics.