Biomimetic chromatography-A novel application of the chromatographic principles

Liquid chromatography in determination of pharmacokinetic properties of compounds in drug discovery process

Liquid chromatography plays a pivotal role in the determination of pharmacokinetic properties during drug discovery, particularly through the evaluation of lipophilicity. This parameter is essential in drug development, significantly influencing pharmacokinetic and pharmacodynamic behavior of potential drugs. It affects membrane permeability, solubility, distribution, and interaction with biological targets, making it a central focus in the early stages of drug design. Poor lipophilicity-related characteristics are often associated with drug failures, inefficacy, toxicity, and increased development costs. Experimental and computational methods, such as chromatographic techniques and theoretical calculations, are vital for accurately determining lipophilicity. These approaches enable the simulation of biological processes, providing insights into how lipophilicity impacts ADME (absorption, distribution, metabolism, and excretion) properties and supporting the optimization of drug candidates. In silico tools further enhance the efficiency of ADME evaluations, reducing the risk of pharmacokinetic-related failures and streamlining the drug discovery process.

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.

Deriving Membrane-Water and Protein-Water Partition Coefficients from In Vitro Experiments for Per- and Polyfluoroalkyl Substances (PFAS)

The phospholipid membrane-water partition coefficients (KMW) and equilibrium binding affinities for human serum albumin (HSA) of 60 structurally diverse perfluoroalkyl and polyfluoroalkyl substances (PFAS) were evaluated through laboratory measurements and modeling to enhance our understanding of PFAS distribution in organisms. Per- and polyfluoroalkyl carboxylic acids exhibited a 0.36 ± 0.01 log-unit increase in KMW as the fluorinated carbon chain length increased from C4 to C16, while per- and polyfluoroalkyl sulfonates showed a 0.37 ± 0.02 log-unit increase. The highest HSA affinity range was observed between C6 and C10, with the following structural subclass order: per- and polyfluoroalkyl sulfonates ≈ ether sulfonic acids > polyfluoroalkyl carboxylic acids > fluorotelomer unsaturated carboxylic acids > phosphate diesters ≈ per- and polyfluoroether carboxylic acids. A comparison between association rate constants (KA) and HSA-PFAS molecular docking predictions with AutoDock Vina indicated that modeling could effectively predict the affinity of PFAS to HSA, especially for PFAS carbon chain lengths from C4 to C10. Based on in vitro results, exposure-dependent PFAS partitioning in organisms was modeled by comparing distribution coefficients between PFAS in phospholipid membranes and HSA at different PFAS concentrations and demonstrated that at lower concentrations, PFAS had higher partitioning in HSA, while with increasing concentration, the proportion of binding relative to the aqueous phase shifted toward the phospholipid membrane. Few studies have compared the bioaccumulation of PFAS in phospholipid membranes and HSA. This research reports that protein-water distribution coefficients are higher than membrane-water partitioning coefficients at lower PFAS concentrations, which may have implications for interpreting exposure data and toxicity experiments.

Rivastigmine structure-based hybrids as potential multi-target anti-Alzheimer's drug candidates

In recent years, an increasing amount of work has been carried out regarding the study of the etiopathology of Alzheimer's Disease (AD). This neurodegenerative disease is characterized by several organic and molecular correlates, which paint a complex picture that also reflects the historic challenge faced by the worldwide scientific community in finding an effective cure for it. In this paper, we describe the synthesis of novel rivastigmine derivatives and their characterization as wide-spectrum enzyme (AChE, BChE, FAAH, MAO-A and MAO-B) inhibitors with potential application in the therapy of AD following the paradigm of multi-target design. 5 (ROS151) and 23 show similar inhibitory profile compared to donepezil on cholinesterases, and ca. two hundred twenty-three and eighty-seven times more active than rivastigmine on AChE. Moreover, ROS151 was found to be a potential metal chelator. Compounds 6 and 8 are very interesting and original multi-functional promising hybrids, with comparable potency on distinct panels of enzymes. All these promising rivastigmine-like hybrids were assayed for their pharmacokinetic properties by using different bio-analytical techniques, showing interesting applicability profiles. Moreover, cytotoxicity assays displayed a safety profile on three different cell lines.

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.

Predicting the acute aquatic toxicity of organic UV filters used in cosmetic formulations

Background and purpose

Organic UV filters are commonly used in sunscreen and cosmetic formulations to protect against harmful UV radiation. However, concerns have emerged over their potential toxic effects on aquatic organisms. This study aims to investigate the acute aquatic toxicity of 13 organic UV filters and determine whether phospholipid binding, measured through biomimetic chromatographic methods, is a better predictor of toxicity than the traditionally used octanol-water partition coefficient (log P).

Experimental approach

The chromatographic retention of the 13 UV filters was measured on an immobilized artificial membrane (IAM) stationary phase to assess phospholipid binding. These measurements were then applied to previously established predictive models, originally developed for pharmaceutical compounds, to estimate acute aquatic toxicity endpoints of 48-hour LC50 for fish and the 48-hour EC50 (immobilization) for Daphnia magna.

Key results

Phospholipid binding was found to be a more reliable predictor of the acute aquatic toxicity of UV filters compared to log P. The toxicity was primarily driven by lipophilicity and charge, with negatively charged compounds exhibiting lower toxicity.

Conclusion

The study demonstrates that phospholipid binding is a better descriptor of UV filter toxicity than log P, providing a more accurate method for predicting the environmental risk of these compounds. This insight can guide the development of more environmentally friendly sunscreens by reducing the use of highly lipophilic and positively charged compounds, thus lowering their aquatic toxicity.

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.

Mechanistic Insights into the Neurotoxicity of 2,5-Dimethoxyphenethylamines (2C) and Corresponding N-(2-methoxybenzyl)phenethylamine (NBOMe) Drugs

Substituted phenethylamines including 2C (2,5-dimethoxyphenethylamines) and NBOMe (N-(2-methoxybenzyl)phenethylamines) drugs are potent psychoactive substances with little to no knowledge available on their toxicity. In the present in vitro study, we explored the mechanisms underlying the neurotoxicity of six substituted phenethylamines: 2C-T-2, 2C-T-4, 2C-T-7 and their corresponding NBOMes. These drugs were synthesized and chemically characterized, and their cytotoxicity (0-1000 μM) was evaluated in differentiated SH-SY5Y cells and primary rat cortical cultures, by the NR uptake and MTT reduction assays. In differentiated SH-SY5Y cells, mitochondrial membrane potential, intracellular ATP and calcium levels, reactive oxygen species production, and intracellular total glutathione levels were also evaluated. All the tested drugs exhibited concentration-dependent cytotoxic effects towards differentiated SH-SY5Y cells and primary rat cortical cultures. The NBOMe drugs presented higher cytotoxicity than their counterparts, which correlates with the drug's lipophilicity. These cytotoxic effects were associated with mitochondrial dysfunction, evident through mitochondrial membrane depolarization and lowered intracellular ATP levels. Intracellular calcium imbalance was observed for 2C-T-7 and 25T7-NBOMe, implying a disrupted calcium regulation. Although reactive species levels remained unchanged, a reduction in intracellular total GSH content was observed. Overall, these findings contribute to a deeper understanding of these drugs, shedding light on the mechanisms underpinning their neurotoxicity.

Evaluation of Physicochemical Properties of Ipsapirone Derivatives Based on Chromatographic and Chemometric Approaches

Drug discovery is a challenging process, with many compounds failing to progress due to unmet pharmacokinetic criteria. Lipophilicity is an important physicochemical parameter that affects various pharmacokinetic processes, including absorption, metabolism, and excretion. This study evaluated the lipophilic properties of a library of ipsapirone derivatives that were previously synthesized to affect dopamine and serotonin receptors. Lipophilicity indices were determined using computational and chromatographic approaches. In addition, the affinity to human serum albumin (HSA) and phospholipids was assessed using biomimetic chromatography protocols. Quantitative Structure-Retention Relationship (QSRR) methodologies were used to determine the impact of theoretical descriptors on experimentally determined properties. A multiple linear regression (MLR) model was calculated to identify the most important features, and genetic algorithms (GAs) were used to assist in the selection of features. The resultant models showed commendable predictive accuracy, minimal error, and good concordance correlation coefficient values of 0.876, 0.149, and 0.930 for the validation group, respectively.

Modification of gradient HPLC method for determination of small molecules' affinity to human serum albumin under column safety conditions: Robustness and chemometrics study

In the early stages of drug discovery, beyond the biological activity screening, determining the physicochemical properties that affect the distribution of molecules in the human body is an essential step. Plasma protein binding (PPB) is one of the most important investigated endpoints. Nevertheless, the methodology for measuring %PPB is significantly less popular and standardized than other physicochemical properties, like lipophilicity. Here, we proposed how to modify protocols presented by Valko into column safety conditions and evaluated their robustness using fractional factorial design. For robustness testing, four factors were selected: column temperature, mobile phase flow rate, maximum isopropanol concentration in the mobile phase, and buffer pH. Elaborate methods have been applied for the analysis of HSA affinity for three groups of antibiotic-oriented substances that vary in chemical structure: fluoroquinolones, sulfonamides, and tetrazole derivatives. Furthermore, based on the reversed-phase chromatography the workflow of pilot studies was proposed to select molecules that have high affinity to HSA and can not be eluted from the HSA column using the concentration of organic modifier recommended by the column manufacturer.

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.

Biomimetic Dispersive Solid-Phase Microextraction: A Novel Concept for High-Throughput Estimation of Human Oral Absorption of Organic Compounds

There is a quest for a novel in vitro analytical methodology that is properly validated for the prediction of human oral absorption and bioaccumulation of organic compounds with no need of animal models. The traditional log P parameter might not serve to predict bioparameters accurately inasmuch as it merely accounts for the hydrophobicity of the compound, but the actual interaction with the components of eukaryotic cells is neglected. This contribution proposes for the first time a novel biomimetic microextraction approach capitalized on immobilized phosphatidylcholine as a plasma membrane surrogate onto organic polymeric sorptive phases for the estimation of human intestinal effective permeability of a number of pharmaceuticals that are also deemed contaminants of emerging concern in environmental settings. A comprehensive exploration of the conformation of the lipid structure onto the surfaces is undertaken so as to discriminate the generation of either lipid monolayers or bilayers or the attachment of lipid nanovesicles. The experimentally obtained biomimetic extraction data is proven to be a superb parameter against other molecular descriptors for the development of reliable prediction models of human jejunum permeability with R2 = 0.76, but the incorporation of log D and the number of aromatic rings in multiple linear regression equations enabled improved correlations up to R2 = 0.88. This work is expected to open new avenues for expeditious in vitro screening methods for oral absorption of organic contaminants of emerging concern in human exposomics.

Immobilized Keratin HPLC Stationary Phase-A Forgotten Model of Transdermal Absorption: To What Molecular and Biological Properties Is It Relevant?

Chromatographic retention data collected on immobilized keratin (KER) or immobilized artificial membrane (IAM) stationary phases were used to predict skin permeability coefficient (log Kp) and bioconcentration factor (log BCF) of structurally unrelated compounds. Models of both properties contained, apart from chromatographic descriptors, calculated physico-chemical parameters. The log Kp model, containing keratin-based retention factor, has slightly better statistical parameters and is in a better agreement with experimental log Kp data than the model derived from IAM chromatography; both models are applicable primarily to non-ionized compounds.Based on the multiple linear regression (MLR) analyses conducted in this study, it was concluded that immobilized keratin chromatographic support is a moderately useful tool for skin permeability assessment.However, chromatography on immobilized keratin may also be of use for a different purpose-in studies of compounds' bioconcentration in aquatic organisms.

Prediction of peptides retention behavior in reversed-phase liquid chromatography based on their hydrophobicity

Hydrophobicity is an important physicochemical property of peptides and proteins. It is responsible for their conformational changes, stability, as well as various chemical intramolecular and intermolecular interactions. Enormous efforts have been invested to study the extent of hydrophobicity and how it could influence various biological processes, in addition to its crucial role in the separation and purification endeavor as well. Here, we have reviewed various studies that were carried out to determine the hydrophobicity starting from (i) simple amino acids solubility behavior, (ii) experimental approach that was undertaken in the reversed-phase liquid chromatography mode, and ending with (iii) some examples of more advanced computational and machine learning models.

Biomimetic chromatography-A novel application of the chromatographic principles

Biomimetic chromatography is the name of the High Performance Liquid Chromatography (HPLC) methods that apply stationary phases containing proteins and phospholipids that can mimic the biological environment where drug molecules distribute. The applied mobile phases are aqueous organic with a pH of 7.4 to imitate physiological conditions that would be encountered in the human body. The calibrated retention of molecules on biomimetic stationary phases reveals a compound's affinity to proteins and phospholipids, which can be used to model the biological and environmental fate of molecules. This technology, when standardised, enables the prediction of in vivo partition and distribution behaviour of compounds and aids the selection of the best compounds for further studies to become a drug molecule. Applying biomimetic chromatographic measurements helps reduce the number of animal experiments during the drug discovery process. New biomimetic stationary phases, such as sphingomyelin and phosphatidylethanolamine, widen the application to the modelling of blood-brain barrier distribution and lung tissue binding. Recently, the measured properties have also been used to predict toxicity, such as phospholipidosis and cardiotoxicity. The aquatic toxicity of drugs and pesticides can be predicted using biomimetic chromatographic data. Biomimetic chromatographic separation methods may also be extended in the future to predict protein and receptor binding kinetics. The development of new biomimetic stationary phases and new prediction models will further accelerate the widespread application of this analytical method.