Novel application of capillary electrophoresis with a liposome coated capillary for prediction of blood-brain barrier permeability

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.

Liposomes: preparation and characterization with a special focus on the application of capillary electrophoresis

Liposomes are nowadays a matter of tremendous interest. Due to their amphiphilic character, various substances with different properties can be incorporated into them and they are especially suitable as a model system for controlled transport of bioactive substances and drugs to the final destination in the body; for example, COVID-19 vaccines use liposomes as a carrier of mRNA. Liposomes mimicking composition of various biological membranes can be prepared with a proper choice of the lipids used, which proved to be important tool in the early drug development. This review deals with commonly used methods for the preparation and characterization of liposomes which is essential for their later use. The alternative capillary electrophoresis methods for physico-chemical characterization such as determination of membrane permeability of liposome, its size and charge, and encapsulation efficiency are included. Two different layouts using liposomes to yield more efficient separation of various analytes are also presented, capillary electrochromatography, and liposomal electrokinetic chromatography.

Preparation of covalently bonded liposome capillary column and its application in evaluation of drug membrane permeability

Two liposomes, including 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC) + 1,2-dimyristoyl-sn-glycero-3-phosphoethanolamine (PE) + cholesterol (Chol) (DSPC/PE/Chol liposomes) and soybean lecithin (SPC) + PE + Chol (SPC/PE/Chol liposomes), were prepared and fixed on the inner wall of capillary column by using the adhesion of polydopamine (PDA) membrane and the cross-linking property of glutaraldehyde (GA). The immobilized liposome capillary column (ILCC) has good repeatability and stability based on the electrophoretic mobility of analyte. A CE method based on the immobilized liposome capillary column chromatography (ILCCC) was successfully developed to study the retention behavior of drugs on ILCC, and the logarithm of retention factor (log k) of neutral and ionic drugs were determined. The results show that the log k measured by the ILCCC based on two liposomes have a good linear fitting (R2 = 0.86). Moreover, the linear relationship between ILCCC system and other related research systems (octanol-water system and immobilized artificial membrane (IAM)) was analyzed, and the results indicate that SPC/PE/Chol ILCCC, DSPC/PE/Chol ILCCC and IAM systems have good fitting results, R2 values are 0.86 and 0.78, respectively. In addition, the normalization coefficients of ILCCC and IAM systems obtained by the linear free energy relationship (LFER) analysis are close and the d value is small. In short, the ILCCC is a simple and feasible method for studying drug membrane permeability.

Sensitivity enhancement in capillary electrophoresis and their applications for analyses of pharmaceutical and related biochemical substances

This review aims to illustrate sensitivity enhancement methods in capillary electrophoresis (CE) and their applications for pharmaceutical and related biochemical substance analyses. The first two parts of the article describe the introduction and principle of CE. The main part focuses on strategies for sensitivity improvement in CE including detector and capillary technologies and pre-concentration techniques. Applications of these techniques for pharmaceutical and biomedical substance analyses are surveyed during the years 2018-2021. This article is protected by copyright. All rights reserved.

Strategies for Structural Modification of Small Molecules to Improve Blood-Brain Barrier Penetration: A Recent Perspective

In the development of central nervous system (CNS) drugs, the blood-brain barrier (BBB) restricts many drugs from entering the brain to exert therapeutic effects. Although many novel delivery methods of large molecule drugs have been designed to assist transport, small molecule drugs account for the vast majority of the CNS drugs used clinically. From this perspective, we review studies from the past five years that have sought to modify small molecules to increase brain exposure. Medicinal chemists make it easier for small molecules to cross the BBB by improving diffusion, reducing efflux, and activating carrier transporters. On the basis of their excellent work, we summarize strategies for structural modification of small molecules to improve BBB penetration. These strategies are expected to provide a reference for the future development of small molecule CNS drugs.

Determination of lipid-water partition coefficient of neutral and ionic drugs by liposome electrokinetic chromatography

Profiling of lipid-water partition coefficients (KL/W ) of drugs is an essential issue during the early stage of drug development. In this study, two liposomes, including 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC) + cholesterol (Chol) (DSPC/Chol liposomes) and soybean lecithin (SPC) + Chol (SPC/Chol liposomes), were prepared for the liposome electrokinetic chromatography (LEKC) analysis, and the logarithm of lipid-water partition coefficients (log KL/W ) of neutral and ionic drugs were determined based on an iterative method. The log KL/W values determined by the SPC/Chol or DSPC/Chol liposomes LEKC were linearly fitted, which showed a good fitting coefficient (R2 = 0.89). Furthermore, the linear relationship between the data obtained from LEKC system and octanol-water system, immobilized artificial membrane, Caco-2 cell model, and software prediction was analyzed, respectively. Results illustrated that DSPC/Chol liposomes or SPC/Chol liposomes had a good linear relationship with Caco-2 cell model, and R2 was 0.81 and 0.72, respectively. Moreover, the linear free energy relationship analysis suggested that the solute volume, hydrogen bond basicity, and J- were the main descriptors that drove the partition process of solutes in the SPC/Chol or DSPC/Chol LEKC system. In addition, the normalized properties of the SPC/Chol and DSPC/Chol LEKC systems through linear free energy relationship analysis were very close. In short, DSPC/Chol liposomes are more suitable for simulating cell membranes than SPC/Chol liposomes, and the developed LEKC is an effective partitioning model for measuring the log KL/W of drugs.

Sampling efficiency of the counting method for permeability calculations estimated with the inhomogeneous solubility-diffusion model

Permeability is a key property in various fields such as membrane technology for chemical separation and transport of substances through cell membranes. At the molecular scale, the counting method uses the number of membrane crossings in a conventional unbiased molecular dynamics simulation to predict the permeability. This contribution investigates under which conditions the counting method has insufficient statistics. An equation is derived for a compartmental model based on the inhomogeneous solubility-diffusion (Smoluchowski) model, giving insight into how the flux correlates with the solubility of permeants. This equation shows that a membrane crossing is a rare event not only when the membrane forms a large free energy barrier but also when the membrane forms a deep free energy well that traps permeants. Such a permeant trap has a high permeability; yet, the counting method suffers from poor statistics. To illustrate this, coarse-grained MD was run for 16 systems of dipalmitoylphosphatidylcholine bilayer membranes with different permeant types. The composition rule for permeability is shown to also hold for fluxes, and it is highlighted that the considered thickness of the membrane causes uncertainty in the permeability calculation of highly permeable membranes. In conclusion, a high permeability in itself is not an effective indicator of the sampling efficiency of the counting method, and caution should be taken for permeants whose solubility varies greatly over the simulation box. A practical consequence relevant in, e.g., drug design is that a drug with high membrane permeability might get trapped by membranes thus reducing its efficacy.

Prediction of the Blood-Brain Barrier (BBB) Permeability of Chemicals Based on Machine-Learning and Ensemble Methods

The ability of chemicals to enter the blood-brain barrier (BBB) is a key factor for central nervous system (CNS) drug development. Although many models for BBB permeability prediction have been developed, they have insufficient accuracy (ACC) and sensitivity (SEN). To improve performance, ensemble models were built to predict the BBB permeability of compounds. In this study, in silico ensemble-learning models were developed using 3 machine-learning algorithms and 9 molecular fingerprints from 1757 chemicals (integrated from 2 published data sets) to predict BBB permeability. The best prediction performance of the base classifier models was achieved by a prediction model based on an random forest (RF) and a MACCS molecular fingerprint with an ACC of 0.910, an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.957, a SEN of 0.927, and a specificity of 0.867 in 5-fold cross-validation. The prediction performance of the ensemble models is better than that of most of the base classifiers. The final ensemble model has also demonstrated good accuracy for an external validation and can be used for the early screening of CNS drugs.