Determination of in Vitro and in Silico Indexes for the Modeling of Blood–Brain Barrier Partitioning of Drugs via Micellar and Immobilized Artificial Membrane Liquid Chromatography

Estimation of passive gastrointestinal absorption of new dual DNA gyrase and topoisomerase IV inhibitors using PAMPA and biopartitioning micellar chromatography and quantitative structure-retention relationship analysis

DNA gyrase and topoisomerase IV play significant role in maintaining the correct structure of DNA during replication and they have been identified as validated targets in antibacterial drug discovery. Inadequate pharmacokinetic properties are responsible for many failures during drug discovery and their estimation in the early phase of this process maximizes the chance of getting useful drug candidates. Passive gastrointestinal absorption of a selected group of thirteen dual DNA gyrase and topoisomerase IV inhibitors was estimated using two in vitro tests - parallel artificial membrane permeability assay (PAMPA) and biopartitioning micellar chromatography (BMC). Due to good correlation between obtained results, passive gastrointestinal absorption of remaining ten compounds was estimated using only BMC. With this experimental setup, it was possible to identify compounds with high values of retention factors (k) and highest expected passive gastrointestinal absorption, and compounds with low values of k for which low passive gastrointestinal absorption is predicted. Quantitative structure-retention relationship (QSRR) modelling was performed by creating multiple linear regression (MLR), partial least squares (PLS) and support vector machines (SVM) models. Descriptors with the highest influence on retention factor were identified and their interpretation can be used for the design of new compounds with improved passive gastrointestinal absorption.

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.

Recent advancements on in vitro blood-brain barrier model: A reliable and efficient screening approach for preclinical and clinical investigation

INTRODUCTION

The efficiency of brain therapeutics is greatly hindered by the blood-brain barrier (BBB). BBB's protective function, selective permeability, and dynamic functionality maintain the harmony between the brain and peripheral region. Thus, the design of any novel drug carrier system requires the complete study and investigation of BBB permeability, efflux transport, and the effect of associated cellular and non-vascular unit trafficking on BBB penetrability. The in vitro BBB models offer a most promising, and reliable mode of initial investigation of BBB permeability and associated factors as strong evidence for further preclinical and clinical investigation.

AREA COVERED

This review work covers the structure and functions of BBB components and different types of in vitro BBB models along with factors affecting BBB model development and model selection criteria.

EXPERT OPINION

In vivo models assume to reciprocate the physiological environment to the maximum extent. However, the interspecies variability, NVUs trafficking, dynamic behavior of BBB, etc., lead to non-reproducible results. The in vitro models are comparatively less complex, and flexible, as per the study design, could generate substantial evidence and help identify suitable in vivo animal model selection.

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 K_p) and bioconcentration factor (log BCF) of structurally unrelated compounds. Models of both properties contained, apart from chromatographic descriptors, calculated physico-chemical parameters. The log K_p model, containing keratin-based retention factor, has slightly better statistical parameters and is in a better agreement with experimental log K_p 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.

APPLICATION OF MICELLAR LIQUID CHROMATOGRAPHY TO MODEL ECOTOXICITY OF PESTICIDES. COMPARISON WITH IMMOBILIZED ARTIFICIAL MEMBRANE CHROMATOGRAPHY AND N-OCTANOL-WATER PARTITIONING

The potential of Micellar Liquid Chromatography (MLC) to model ecotoxicological endpoints for a series of pesticides was investigated. To exploit the flexibility in MLC conditions, different surfactants were employed and retention mechanism was tracked and compared to Immobilized Artificial Membrane (IAM) chromatographic retention and n-octanol- water partitioning, logP. Neutral polyoxyethylene (23) lauryl ether (Brij-35), anionic sodium dodecyl sulfate (SDS) and cationic cetyltrimethylammonium bromide (CTAB) were used in presence of PBS at pH=7.40 and acetonitrile as organic modifier when necessary. Similarities/ dissimilarities between MLC retention and IAM or logP were investigated by Principal Component Analysis (PCA) and Liner Solvation Energy Relationships (LSER). LSER revealed that hydrogen bonding acidity is the most important factor for differentiation between MLC and IAM or logP. The impact of hydrogen bonding is exemplified in the relationships of MLC retention factors with IAM or logP, which necessitate the inclusion of a relevant descriptor. PCA further revealed that MLC retention factors are clustered together with IAM indices and logP within a broader ellipse formed by ecotoxicological endpoints, involving LC₅₀/ EC₅₀ values of six aquatic organisms namely Rainbow Trout, Fathead Minnow, Bluegill Sunfish, Sheepshead Minnow, Eastern Oyster and Water Flea as well as LD₅₀ values of Honey Bee, thus justifying their use to construct relevant models. Satisfactory specific models for individual organisms, as well as general fish models, were obtained, in most cases, upon combination of MLC retention factors with Molecular Weight (MW) or/ and hydrogen bond parameters. All models were evaluated and compared to previously reported IAM and logP based models using an external validation data set. Predictions with Brij-35 and SDS based models were comparable, although slightly inferior than those obtained with IAM, while they were in all cases better than those obtained with logP. CTAB led to a satisfactory prediction model for Honey Bee, but it was found less suitable for aquatic organisms.

Understanding the Blood-Brain Barrier and Beyond: Challenges and Opportunities for Novel CNS Therapeutics

This review addresses questions on how to accomplish successful central nervous system (CNS) drug delivery (i.e., having the right concentration at the right CNS site, at the right time), by understanding the rate and extent of blood‐brain barrier (BBB) transport and intra‐CNS distribution in relation to CNS target site(s) exposure. To this end, we need to obtain and integrate quantitative and connected data on BBB using the Combinatory Mapping Approach that includes in vivo and ex vivo animal measurements, and the physiologically based comprehensive LEICNSPK3.0 mathematical model that can translate from animals to humans. For small molecules, slow diffusional BBB transport and active influx and efflux BBB transport determine the differences between plasma and CNS pharmacokinetics. Obviously, active efflux is important for limiting CNS drug delivery. Furthermore, liposomal formulations of small molecules may to a certain extent circumvent active influx and efflux at the BBB. Interestingly, for CNS pathologies, despite all reported disease associated BBB and CNS functional changes in animals and humans, integrative studies typically show a lack of changes on CNS drug delivery for the small molecules. In contrast, the understanding of the complex vesicle‐based BBB transport modes that are important for CNS delivery of large molecules is in progress, and their BBB transport seems to be significantly affected by CNS diseases. In conclusion, today, CNS drug delivery of small drugs can be well assessed and understood by integrative approaches, although there is still quite a long way to go to understand CNS drug delivery of large molecules.

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.

Multivariate assessment of anticancer oleanane triterpenoids lipophilicity

Naturally occurring molecules are excellent sources of lead compounds. A series of oleanolic acid (OA) derivatives previously synthesized in our laboratory, which show promising antitumor activity, have been analyzed in terms of lipophilicity evaluation applying chromatographic and computational approaches. Retention data obtained on three reversed-phase liquid chromatography stationary phases (RP-HPLC) and immobilized artificial membrane chromatography (IAM-HPLC) were compared with computational methods using chemometric tools such as cluster analysis, principal component analysis and sum of ranking differences. To investigate the molecular mechanism of retention quantitive structure retention relationship analysis was performed, based on the genetic algorithm coupled with multiple linear regression (GA-MLR). The obtained results suggested that the ionization potential of studied molecules significantly affects their retention in classical RP-HPLC. In IAM-HPLC additionally, polarizability-related descriptors also play an essential role in that process. The lipophilicity indices comparison shows significant differences between the computational lipophilicity and chromatographically determined ones.

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.

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.

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.

Permeability prediction for zwitterions via chromatographic indexes and classification into 'certain' and 'uncertain'

Background: The development of zwitterions to a drug is likely to be more challenging than compounds of other charge types. Results: Two chromatographic indexes (log k'80 PLRP-S and log K_W^IAM) can be successfully used as permeability classifiers of ampholytes. Moreover, a pragmatic classification into ordinary ampholytes; zwitterions 'certain' (i.e., the zwitterionic species is dominant in the physiological pH range); and zwitterions 'uncertain' (multiple species are present in the physiological pH range) enables to study the permeability of ampholytic compounds in relation to species distribution. Methodology: Potentiometry (pK_a), reversed-phase (RP)-chromatography, tri-layer parallel artificial membrane permeability assays, quantitative structure-property relationships (QSPR) and block relevance (BR) analysis, receiver operating characteristic (ROC) curves. Conclusion: Structures considered as poorly permeable like zwitterions can be integrated in drug discovery programs by applying ad hoc experimental and computational tools.

MLR, PLSR-BR Analysis and MBPLSR to Interpret Multivariate QSPR Models. The Case of a Micellar Liquid Chromatography Descriptor (log KW SDS )

Improving the interpretability of multivariate QSPR models is a major issue in modern drug discovery. In this study we applied three strategies to model and deconvolute the balance of intermolecular forces governing log K_W ^SDS , a chromatographic descriptor of potential relevance in the prediction of ADME phenomena. A dataset of 77 compounds was set-up and an ad hoc pool of VS+ descriptors calculated. The data matrix was firstly submitted to a PCA run for a preliminary analysis and outliers detection. To model and interpret log K_W ^SDS three chemoinformatic approaches implementing either variable selection or grouping tools were used: a) MLR and GA, b) PLSR combined with BR analysis and c) MBPLSR. Results provided by the three methods were largely superposable both in terms of prediction performances and mechanistic interpretation. Overall, they showed that log K_W ^SDS is a complex descriptor mainly governed by the dimension, polarity and HBD solutes' properties. Chemoinformatic strategies as those reported in this paper might be applied to any chromatographic system and thus represent a potent tool to exploit the full potential of chromatographic descriptors in pharmaceutical, toxicological and related sciences.

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

The Blood-Brain Barrier (BBB) plays an essential role in protecting the brain tissues against possible injurious substances. In the present work, 79 neutral, basic, acidic and amphoteric structurally unrelated analytes were considered and their chromatographic retention coefficients on immobilized artificial membrane (IAM) stationary phase were determined employing a mass spectrometry (MS)-compatible buffer based on ammonium acetate. Their BBB passage predictive strength was evaluated and the statistical models based on IAM indexes and in silico physico-chemical descriptors showed solid statistics (r² (n - 1) = 0.78). The predictive strength of the indexes achieved by the MS-compatible method was comparable to that achieved by employing the more "biomimetic" Dulbecco's phosphate buffered saline, even if some differences in the elution order were observed. The method was transferred to the MS, employing a diode-array-detection coupled to an electrospray ionization source and a time-of-flight analyzer. This setup allowed the simultaneous analysis of up to eight analytes, yielding a remarkable acceleration of the analysis time.

Learning how to use IAM chromatography for predicting permeability

The interest for IAM (Immobilized Artificial Membranes) chromatography in the prediction of drug permeability is increasing. Here we firstly set-up a dataset of 253 molecules including neutral and ionized drugs and few organic compounds for which we either measured or retrieved from the literature IAM.PC.DD2 log K_w^IAM data. Then we applied block relevance (BR) analysis to extract from PLS models the relative contribution of intermolecular forces governing log K_w^IAM and Δlog K_w^IAM (a combined descriptor calculated from log K_w^IAM). Finally, the relationship between log K_w^IAM, Δlog K_w^IAM and passive permeability determined in both PAMPA and MDCK-LE systems was looked for. Models provided the basis for a rational application of IAM chromatography in permeability prediction.

Lipophilicity and biomimetic properties to support drug discovery

INTRODUCTION

Lipophilicity, expressed as the octanol-water partition coefficient, constitutes the most important property in drug action, influencing both pharmacokinetic and pharmacodynamics processes as well as drug toxicity. On the other hand, biomimetic properties defined as the retention outcome on HPLC columns containing a biological relevant agent, provide a considerable advance for rapid experimental - based estimation of ADME properties in early drug discovery stages. Areas covered: This review highlights the paramount importance of lipophilicity in almost all aspects of drug action and safety. It outlines problems brought about by high lipophilicity and provides an overview of the drug-like metrics which incorporate lower limits or ranges of logP. The fundamental factors governing lipophilicity are compared to those involved in phospholipophilicity, assessed by Immobilized Artificial Membrane Chromatography (IAM). Finally, the contribution of biomimetic properties to assess plasma protein binding is evaluated. Expert opinion: Lipophilicity and biomimetic properties have important distinct and overlapping roles in supporting the drug discovery process. Lipophilicity is unique in early drug design for library screening and for the identification of the most promising compounds to start with, while biomimetic properties are useful for the experimentally-based evaluation of ADME properties for the synthesized novel compounds, supporting the prioritization of drug candidates and guiding further synthesis.