Screening therapeutics according to their uptake across the blood-brain barrier: A high throughput method based on immobilized artificial membrane liquid chromatography-diode-array-detection coupled to electrospray-time-of-flight mass spectrometry

Preparation of a Biomimetic Poly-Phosphatidylserine Monolithic Column for Immobilized Artificial Membrane Chromatography

The pharmacokinetic properties of drugs are significantly influenced by their interactions with cell membranes. Phosphatidylserine (PS) as one of the crucial membrane phospholipids is present abundantly in biological cells. In this study, a PS-mimicking phospholipid membrane polymer monolithic column was developed using the synthetic compound 2-methylacryloxydodecyl phosphatidylserine (MDPS). The physicochemical properties and chromatographic performance of the poly(MDPS-co-ethylene dimethacrylate (EDMA)) monolithic column were evaluated through scanning electron microscopy (SEM) and nano-high-performance liquid chromatography (HPLC). The retention mechanism was investigated by eluting the acidic, neutral, and basic compounds under the same gradient conditions, and the performance of the poly(MDPS-co-EDMA) monolithic column was compared with that of a poly(12-methacryloyl n-dodecylphosphocholine (MDPC)-co-EDMA) monolithic column. The poly(MDPS-co-EDMA) column demonstrated effective separation capabilities for small peptides, protein enzymatic hydrolysis polypeptides, and pharmaceutical compounds. Furthermore, the column was also employed to predict the blood-brain barrier (BBB) permeability of drugs, and the correlation coefficient of 0.73 indicates the promising potential of poly(MDPS-co-EDMA) monolithic column for predicting the ability of drugs to cross the BBB.

Is the potential for bioaccumulation of cannabinoids underestimated? Insights from biomimetic chromatography in cannabinoid exposure evaluation

The use of cannabis-related products is currently experiencing extraordinary growth in popularity in the European and US markets. A wide variety of cannabis-related products have emerged, including oils, tinctures, edibles, topicals, cosmetics, and even beverages and sweets, offering the purported medical benefits without the psychoactive effects associated with Cannabis sativa. However, there is a significant gap in our understanding of bioaccumulation processes and their long-term effects, particularly as cannabinoids are highly lipophilic molecules. In this study, we used a biochromatographic approach to experimentally determine the lipophilicity, binding to phospholipids and affinity to plasma protein of selected cannabinoids to comprehensively assess their bioaccumulation potential. The results obtained clearly indicated that cannabinoids, including the particularly popular cannabidiol, promote bioaccumulation. Importantly, a higher affinity for phospholipids indicated non-specific binding, which can lead to phospholipidosis. Cannabinoids exhibit a stronger binding affinity to human serum albumin (HSA) compared to diclofenac, which might affect the pharmacokinetics of regularly taken medications when co-administered.

Application of Biomimetic Chromatography and QSRR Approach for Characterizing Organophosphate Pesticides

Biomimetic chromatography is a powerful tool used in the pharmaceutical industry to characterize the physicochemical properties of molecules during early drug discovery. Some studies have indicated that biomimetic chromatography may also be useful for the evaluation of toxicologically relevant molecules. In this study, we evaluated the usefulness of the biomimetic chromatography approach for determining the lipophilicity, affinity to phospholipids, and bind to plasma proteins of selected organophosphate pesticides. Quantitative structure-retention relationship (QSRR) models were proposed to understand the structural features that influence the experimentally determined properties. ACD/labs, Chemicalize, and alvaDesc software were used to calculate theoretical descriptors. Multilinear regression was used as the regression type, and feature selection was supported by a genetic algorithm. The obtained QSRR models were validated internally and externally, and they demonstrated satisfactory performance with key statistical parameters ranged from 0.844 to 0.914 for R2 and 0.696-0.898 for R2ext, respectively, indicating good predictive ability.

Biomimetic separations in chemistry and life sciences

Since Otto Schmitt introduced the term "biomimetics" in 1957, the imitation of biological systems to develop separation methods and simulate biological processes has seen continuous growth, particularly over the past five decades. The biomimetic approach relies on the use of specific ligands-biospecific, biomimetic, or synthetic-which target biomolecules, such as proteins, antibodies, nucleic acids, enzymes, drugs, pesticides, and other bioactive analytes. This review highlights advances in biomimetic separations, focusing on biomimetic liquid chromatography (including immobilized artificial membrane chromatography, cell membrane chromatography, biomimetic affinity chromatography, weak affinity chromatography, micellar liquid chromatography, immobilized liposome chromatography, and liposome electrokinetic capillary chromatography) for the complex separation and purification of biomolecules and other important chemical compounds. It also explores their application in studying drug-receptor interactions, screening chemical permeability, absorption, distribution, toxicity, as well as predicting environmental risks. Additionally, this review discusses the application of biomimetic magnetic nanoparticles, which leverage biological membranes and proteins for drug discovery, protein purification, and diagnostics.

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.

Modeling of small molecule's affinity to phospholipids using IAM-HPLC and QSRR approach enhanced by similarity-based machine algorithms

Immobilized artificial membrane chromatography (IAM) has been proposed as a more biosimilar alternative to classical lipophilicity measurement. Determination of small molecule's affinity to phospholipids can be supported for predicting their behavior in the human body. Therefore, a better understanding of the molecular interaction mechanism between small xenobiotics and phospholipids can accelerate drug discovery. Here, the quantitative structure-retention relationships (QSRR) approach was integrated with mechanistic descriptors calculated using Chemicalize software to propose an easy-to-interpretation QSRR model. Considering the heterogeneous character of the data set, locally weighted least squares kernel regression belonging to similarity-based machine learning methods have been applied. The results showed that lipophilicity, charge, and maximum projection area determine molecule binding to phospholipids. Full validation of the obtained model based on OECD recommendations has been performed and the applicability domain was defined using the probability-oriented distance-based approach. The high values of predictive squared correlation coefficient (Q2), and small root mean square error of prediction (RMSEP), 0.812 and 6.739, respectively, confirmed that the obtained QSRR model is not well-fitted to the training data but also showed prediction power. Additionally, only 1.5% of molecules from the training set and 2.8% from the validation test are outside the applicability domain, confirming great predictive abilities.

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.

In Silico Analysis, Anticonvulsant Activity, and Toxicity Evaluation of Schisandrin B in Zebrafish Larvae and Mice

The aim of this study is to evaluate the anticonvulsant potential of schisandrin B, a main ingredient of Schisandra chinensis extracts. Schisandrin B showed anticonvulsant activity in the zebrafish larva pentylenetetrazole acute seizure assay but did not alter seizure thresholds in the intravenous pentylenetetrazole test in mice. Schisandrin B crosses the blood-brain barrier, which we confirmed in our in silico and in vivo analyses; however, the low level of its unbound fraction in the mouse brain tissue may explain the observed lack of anticonvulsant activity. Molecular docking revealed that the anticonvulsant activity of the compound in larval zebrafish might have been due to its binding to a benzodiazepine site within the GABAA receptor and/or the inhibition of the glutamate NMDA receptor. Although schisandrin B showed a beneficial anticonvulsant effect, toxicological studies revealed that it caused serious developmental impairment in zebrafish larvae, underscoring its teratogenic properties. Further detailed studies are needed to precisely identify the properties, pharmacological effects, and safety of schisandrin B.

Combined Micellar Liquid Chromatography Technique and QSARs Modeling in Predicting the Blood-Brain Barrier Permeation of Heterocyclic Drug-like Compounds

The quantitative structure-activity relationship (QSAR) methodology was used to predict the blood-brain permeability (log BB) for 65 synthetic heterocyclic compounds tested as promising drug candidates. The compounds were characterized by different descriptors: lipophilicity, parachor, polarizability, molecular weight, number of hydrogen bond acceptors, number of rotatable bonds, and polar surface area. Lipophilic properties of the compounds were evaluated experimentally by micellar liquid chromatography (MLC). In the experiments, sodium dodecyl sulfate (SDS) as the effluent component and the ODS-2 column were used. Using multiple linear regression and leave-one-out cross-validation, we derived the statistically significant and highly predictive quantitative structure-activity relationship models. Thus, this study provides valuable information on the expected properties of the substances that can be used as a support tool in the design of new therapeutic agents.

Quantitative Retention (Structure)–Activity Relationships in Predicting the Pharmaceutical and Toxic Properties of Potential Pesticides

The micellar liquid chromatography technique and quantitative retention (structure)–activity relationships method were used to predict properties of carbamic and phenoxyacetic acids derivatives, newly synthesized in our laboratory and considered as potential pesticides. Important properties of the test substances characterizing their potential significance as pesticides as well as threats to humans were considered: the volume of distribution, the unbonded fractions, the blood–brain distribution, the rate of skin and cell permeation, the dermal absorption, the binding to human serum albumin, partitioning between water and plants’ cuticles, and the lethal dose. Pharmacokinetic and toxicity parameters were predicted as functions of the solutes’ lipophilicities and the number of hydrogen bond donors, the number of hydrogen bond acceptors, and the number of rotatable bonds. The equations that were derived were evaluated statistically and cross-validated. Important features of the molecular structure influencing the properties of the tested substances were indicated. The QSAR models that were developed had high predictive ability and high reliability in modeling the properties of the molecules that were tested. The investigations highlighted the applicability of combined chromatographic technique and QS(R)ARs in modeling the important properties of potential pesticides and reducing unethical animal testing.

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.

Biomimetic Chromatographic Studies Combined with the Computational Approach to Investigate the Ability of Triterpenoid Saponins of Plant Origin to Cross the Blood-Brain Barrier

Biomimetic (non-cell based in vitro) and computational (in silico) studies are commonly used as screening tests in laboratory practice in the first stages of an experiment on biologically active compounds (potential drugs) and constitute an important step in the research on the drug design process. The main aim of this study was to evaluate the ability of triterpenoid saponins of plant origin to cross the blood-brain barrier (BBB) using both computational methods, including QSAR methodology, and biomimetic chromatographic methods, i.e., High Performance Liquid Chromatography (HPLC) with Immobilized Artificial Membrane (IAM) and cholesterol (CHOL) stationary phases, as well as Bio-partitioning Micellar Chromatography (BMC). The tested compounds were as follows: arjunic acid (Terminalia arjuna), akebia saponin D (Akebia quinata), bacoside A (Bacopa monnieri) and platycodin D (Platycodon grandiflorum). The pharmacokinetic BBB parameters calculated in silico show that three of the four substances, i.e., arjunic acid, akebia saponin D, and bacoside A exhibit similar values of brain/plasma equilibration rate expressed as logPSFubrain (the average logPSFubrain: -5.03), whereas the logPSFubrain value for platycodin D is -9.0. Platycodin D also shows the highest value of the unbound fraction in the brain obtained using the examined compounds (0.98). In these studies, it was found out for the first time that the logarithm of the analyte-micelle association constant (logKMA) calculated based on Foley's equation can describe the passage of substances through the BBB. The most similar logBB values were obtained for hydrophilic platycodin D, applying both biomimetic and computational methods. All of the obtained logBB values and physicochemical parameters of the molecule indicate that platycodin D does not cross the BBB (the average logBB: -1.681), even though the in silico estimated value of the fraction unbound in plasma is relatively high (0.52). As far as it is known, this is the first paper that shows the applicability of biomimetic chromatographic methods in predicting the penetration of triterpenoid saponins through the BBB.

Comprehensive two-dimensional liquid chromatography as a biomimetic screening platform for pharmacokinetic profiling of compound libraries in early drug development

A comprehensive two-dimensional liquid chromatography-based biomimetic platform (LCxLC) has been developed and validated for drug diffusion studies. Human serum albumin (HSA) and immobilized artificial membrane (IAM) were thereby used in the first (¹D) and second (²D) separation dimension, respectively. While the former was meant to emulate the blood, the latter was instead intended to mimic the intestinal mucosa epithelium. Therefore, the experimental conditions, i.e. pH, temperature and buffer composition, were modulated to reflect faithfully in vivo conditions. 30 compounds, whose effective intestinal permeability (P_eff) assayed in situ on humans by a validated technique was known from the literature, were used as model drugs. A good and orthogonal separation was achieved for the whole dataset, although for a better distribution of the most polar compounds in the elution window a segmented gradient elution program had to be employed. Interestingly, the passively uptaken compounds having the most favourable P_eff populated a specific area of the 2D plots, implying that the affinity for HSA and IAM has to lie in specific ranges in order for a compound to be satisfactorily absorbed from the intestinal lumen. Although these results should be regarded as preliminary, this work paves an entirely new and unprecedented way to profile pharmaceutically relevant compounds for their in vivo absorption and distribution potential.

Predicting the Blood-Brain Barrier Permeability of New Drug-Like Compounds via HPLC with Various Stationary Phases

The permeation of the blood-brain barrier is a very important consideration for new drug candidate molecules. In this research, the reversed-phase liquid chromatography with different columns (Purosphere RP-18e, IAM.PC.DD2 and Cosmosil Cholester) was used to predict the penetration of the blood-brain barrier by 65 newly-synthesized drug-like compounds. The linear free energy relationships (LFERs) model (log BB = c + eE + sS + aA + bB + vV) was established for a training set of 23 congeneric biologically active azole compounds with known experimental log BB (BB = C_blood/C_brain) values (R² = 0.9039). The reliability and predictive potency of the model were confirmed by leave-one-out cross validation as well as leave-50%-out cross validation. Multiple linear regression (MLR) was used to develop the quantitative structure-activity relationships (QSARs) to predict the log BB values of compounds that were tested, taking into account the chromatographic lipophilicity (log k_w), polarizability and topological polar surface area. The excellent statistics of the developed MLR equations (R² > 0.8 for all columns) showed that it is possible to use the HPLC technique and retention data to produce reliable blood-brain barrier permeability models and to predict the log BB values of our pharmaceutically important molecules.

Recent applications of immobilized biomaterials in herbal analysis

Immobilization of biomaterials developed rapidly due to the great promise in improving their stability, activity and even selectivity. In this review, the immobilization strategies of biomaterials, including physical adsorption, encapsulation, covalent attachment, cross-linking and affinity linkage, were briefly introduced. Then, the major emphasis was focused on the reported various types of immobilized biomaterials, including proteins, enzymes, cell membrane and artificial membrane, living cells, carbohydrates and bacteria, used in the herbal analysis for bioactive compound screening, drug-target interaction evaluation and chiral separation. In addition, a series of carrier materials applied in biomaterials immobilization, such as magnetic nanoparticles, metal-organic frameworks, silica capillary column, cellulose filter paper, cell membrane chromatography, immobilized artificial membrane chromatography and hollow fiber, were also discussed. Perspectives on further applications of immobilized biomaterials in herbal analysis were finally presented.

Application of separation methods for in vitro prediction of blood-brain barrier permeability-The state of the art

Despite many efforts, drug discovery pipeline is still a highly inefficient process. Nowadays, when combinatorial chemistry enables to synthesize hundreds of new drugs candidates, methods for rapid assessment of biopharmaceutical parameters of new compounds are highly desired. Over one-third of drugs candidates is rejected because of unsatisfactory pharmacokinetic properties. In the drug discovery process, the blood-brain barrier (BBB) permeability plays a critical role for central nervous system active drugs candidates as well as non-central nervous system active drugs. For this reason, knowledge on the BBB permeability of compounds is essential in the development of new medicines. The review was focused on the application of different separation methods for BBB permeability assessment. Both chromatographic and electrophoretic methods were described. In the article, the advantages and limitations of well-established chromatographic methods like immobilized artificial membrane chromatography or micellar liquid chromatography, and less common techniques were discussed. Special attention was devoted to methods were microemulsion is used as mobile or pseudostationary phases.