17β-carboxamide steroids – in vitro prediction of human skin permeability and retention using PAMPA technique

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.

Synthesis, Evaluation of Enzyme Inhibition and Redox Properties of Potential Dual COX-2 and 5-LOX Inhibitors

Various dual inhibitors of COX-2 and 5-LOX enzymes have been developed so far in order to obtain more effective and safer anti-inflammatory drugs. The aim of this study was to design and synthesize new dual COX-2 and 5-LOX inhibitors, and to evaluate their enzyme inhibition potential and redox properties. Thirteen compounds (1-13) were designed taking into account structural requirements for dual COX-2 and 5-LOX inhibition and antioxidant activity, synthesized, and structurally characterized. These compounds can be classified as N-hydroxyurea derivatives (1, 2 and 3), 3,5-di-tert-butylphenol derivatives (4, 5, 6, 7 and 13), urea derivatives (8, 9 and 10) and "type B hydroxamic acids" (11 and 12). COX-1, COX-2 and 5-LOX inhibitory activities were evaluated using fluorometric inhibitor screening kits. The evaluation of the redox activity of newly synthesized compounds was performed in vitro in the human serum pool using redox status tests. The prooxidative score, the antioxidative score and the oxy-score were calculated. Seven out of thirteen synthesized compounds (1, 2, 3, 5, 6, 11 and 12) proved to be dual COX-2 and 5-LOX inhibitors. These compounds expressed good COX-2/COX-1 selectivity. Moreover, dual inhibitors 1, 3, 5, 11 and 12 showed good antioxidant properties.

High-performance liquid chromatography evaluation of lipophilicity and QSRR modeling of a series of dual DNA gyrase and topoisomerase IV inhibitors

Bacterial DNA gyrase and topoisomerase IV control the topological state of DNA during replication and represent important antibacterial drug targets. To be successful as drug candidates, newly synthesized compounds must possess optimal lipophilicity, which enables efficient delivery to the site of action. In this study, retention behavior of twenty-three previously synthesized dual DNA gyrase and topoisomerase IV inhibitors was tested in RP-HPLC system, consisting of C8 column and acetonitrile/phosphate buffer (pH 5.5 and pH 7.4) mobile phase. logD was calculated at both pH values and the best correlation with logD was obtained for retention parameter φ0, indicating that this RP-HPLC system could be used as an alternative to the shake-flask determination of lipophilicity. Subsequent QSRR analysis revealed that intrinsic lipophilicity (logP) and molecular weight (bcutm13) have a positive, while solubility (bcutp3) has a negative influence on this retention parameter.

Skin models for dermal exposure assessment of phthalates

Phthalates are a class of compounds that have found widespread use in industrial applications, in particular in the polymer, cosmetics and pharmaceutical industries. While ingestion, and to a lesser degree inhalation, have been considered as the major exposure routes, especially for higher molecular weight phthalates, dermal exposure is an important route for lower weight phthalates such as diethyl phthalate (DEP). Assessing the dermal permeability of such compounds is of great importance for evaluating the impact and toxicity of such compounds in humans. While human skin is still the best model for studying dermal permeation, availability, cost and ethical concerns may preclude or restrict its use. A range of alternative models has been developed over time to substitute for human skin, especially in the early phases of research. These include ex vivo animal skin, human reconstructed skin and artificial skin models. While the results obtained using such alternative models correlate to a lesser or greater degree with those from in vivo human studies, the use of such models is nevertheless vital in dermal permeation research. This review discusses the alternative skin models that are available, their use in phthalate permeation studies and possible new avenues of phthalate research using skin models that have not been used so far.

Revisiting techniques to evaluate drug permeation through skin

INTRODUCTION

Investigating the transportation of a drug molecule through various layers of skin and determining the amount of drug retention in skin layers is of prime importance in transdermal and topical drug delivery. The information regarding drug permeation and retention in skin layers aids in optimizing a formulation and provides insight into the therapeutic efficacy of a formulation.

AREAS COVERED

This perspective covers various methods that have been explored to estimate drug/therapeutics in skin layers using in vitro, ex vivo, and in vivo conditions. In vitro methods such as diffusion techniques, ex vivo methods such as isolated perfused skin models and in vivo techniques including dermato-pharmacokinetics employing tape stripping, and microdialysis are discussed. Application of all techniques at various stages of formulation development where various local and systemic effects need to be considered.

EXPERT OPINION

The void in the existing methodologies necessitates improvement in the field of dermatologic research. Standardization of protocols, experimental setups, regulatory guidelines, and further research provides information to select an alternative for human skin to perform skin permeation experiments to increase the reliability of data generated through the available techniques. There is a need to utilize multiple techniques for appropriate dermato-pharmacokinetics evaluation and formulation's efficacy.

Application of in vitro PAMPA technique and in silico computational methods for blood-brain barrier permeability prediction of novel CNS drug candidates

Permeability assessment of small molecules through the blood-brain barrier (BBB) plays a significant role in the development of effective central nervous system (CNS) drug candidates. Since in vivo methods for BBB permeability estimation require a lot of time and resources, in silico and in vitro approaches are becoming increasingly popular nowadays for faster and more economical predictions in early phases of drug discovery. In this work, through application of in vitro parallel artificial membrane permeability assay (PAMPA-BBB) and in silico computational methods we aimed to examine the passive permeability of eighteen compounds, which affect serotonin and dopamine levels in the CNS. The data set was consisted of novel six human dopamine transporter (hDAT) substrates that were previously identified as the most promising lead compounds for further optimisation to achieve neuroprotective effect, twelve approved CNS drugs, and their related compounds. Firstly, PAMPA methods was used to experimentally determine effective BBB permeability (P_e) for all studied compounds and obtained results were further submitted for quantitative structure permeability relationship (QSPR) analysis. QSPR models were built by using three different statistical methods: stepwise multiple linear regression (MLR), partial least square (PLS), and support-vector machine (SVM), while their predictive capability was tested through internal and external validation. Obtained statistical parameters (MLR- R²_pred=-0.10; PLS- R²_pred=0.64, r²_m=0.69, r^/2_m=0.44; SVM- R²_pred=0.57, r²_m=0.72, r^/2_m=0.55) indicated that the SVM model is superior over others. The most important molecular descriptors (H₀p and SolvEMt_3D) were identified and used to propose structural modifications of the examined compounds in order to improve their BBB permeability. Moreover, steered molecular dynamics (SMD) simulation was employed to comprehensively investigate the permeability pathway of compounds through a lipid bilayer. Taken together, the created QSPR model could be used as a reliable and fast pre-screening tool for BBB permeability prediction of structurally related CNS compounds, while performed MD simulations provide a good foundation for future in silico examination.

Charged aerosol detector response modeling for fatty acids based on experimental settings and molecular features: a machine learning approach

The charged aerosol detector (CAD) is the latest representative of aerosol-based detectors that generate a response independent of the analytes' chemical structure. This study was aimed at accurately predicting the CAD response of homologous fatty acids under varying experimental conditions. Fatty acids from C12 to C18 were used as model substances due to semivolatile characterics that caused non-uniform CAD behaviour. Considering both experimental conditions and molecular descriptors, a mixed quantitative structure-property relationship (QSPR) modeling was performed using Gradient Boosted Trees (GBT). The ensemble of 10 decisions trees (learning rate set at 0.55, the maximal depth set at 5, and the sample rate set at 1.0) was able to explain approximately 99% (Q²: 0.987, RMSE: 0.051) of the observed variance in CAD responses. Validation using an external test compound confirmed the high predictive ability of the model established (R²: 0.990, RMSEP: 0.050). With respect to the intrinsic attribute selection strategy, GBT used almost all independent variables during model building. Finally, it attributed the highest importance to the power function value, the flow rate of the mobile phase, evaporation temperature, the content of the organic solvent in the mobile phase and the molecular descriptors such as molecular weight (MW), Radial Distribution Function-080/weighted by mass (RDF080m) and average coefficient of the last eigenvector from distance/detour matrix (Ve2_D/Dt). The identification of the factors most relevant to the CAD responsiveness has contributed to a better understanding of the underlying mechanisms of signal generation. An increased CAD response that was obtained for acetone as organic modifier demonstrated its potential to replace the more expensive and environmentally harmful acetonitrile.

A comprehensive study on retention of selected model substances in β-cyclodextrin-modified high performance liquid chromatography

The quantitative structure-retention relationship (QSRR) models are not only employed in retention behaviour prediction, but also in an in-depth understanding of complex chromatographic systems. The goal of the present research is to enable the comprehensive understanding of retention underlying the separation in β-cyclodextrin (CD) modified reversed-phase high performance liquid chromatography (RP-HPLC) systems, through the development of mixed QSRR models. Moreover, the amount of β-CD adsorbed on the stationary phase surface (β-CD_A) is added as the model's input in order to evaluate its contribution to both model performances and retention. Nuclear magnetic resonance (NMR) experiments were conducted to confirm the predicted inclusion complex structures and support the application of in silico tools. The most significant descriptors revealed that retention is governed by the steric factors 7.5 Å distant from the geometrical centre of a molecule, 3D arrangement of atoms determining the molecular size and shape, lipophilicity indicated by topological distances, as well as the unbound system's energy, related to the inclusion complex formation. In addition, a notable effect of the pH of the aqueous phase on the retention of ionizable analytes was shown. In the case of pH of the aqueous phase and β-CD_A the change in retention behaviour of the studied analytes was observed only at the highest β-CD_A value (5.17 μM/m²), but it was not related to the ionization state of analytes. When the analytes did not change the ionization form across the investigated studied pH range, and the acetonitrile content in the mobile phase was 25% (v/v), the retention factor had low values regardless of the β-CD_A; under these circumstances the retention is probably acetonitrile driven.

Application of the human stratum corneum lipid-based mimetic model in assessment of drug-loaded nanoparticles for skin administration

A lipid-based permeation assay (PVPA_SC) with a lipid composition similar to Human stratum corneum layer has been previously reported. The aim of this study was to further characterize the PVPA_SC model in the presence of co-solvents and to determine its applicability to evaluate drug permeability with drug-loaded nanoparticles. Data obtained from PVPA_SC model were compared with results from isolated SC from pig ear skin. The characterization revealed that the PVPA_SC barriers retain integrity and calcein permeability when stored up to 12 weeks at -20 °C, in the presence of different co-solvents, and under a skin environment pH range. The permeation profile of calcein in the lipid-based barrier correlated well with data obtained for the isolated SC model and revealed higher reproducibility. Cyclosporine A (CsA) was selected as a model drug, given its relevance for skin-inflammatory diseases and two types of lipid nanoparticles were used to assess the permeability of the PVPA_SC model. It was possible to distinguish the permeability between free and nanoparticles' loaded cyclosporine. Data obtained with CsA-loaded nanoformulations indicated a higher permeation rate than the obtained for the solid lipid nanoparticles or the free drug. The PVPA_SC model could be applied as a cost-effective alternative for skin early drug development.

Human skin models: From healthy to disease-mimetic systems; characteristics and applications

Skin drug delivery is an emerging route in drug development, leading to an urgent need to understand the behaviour of active pharmaceutical ingredients within the skin. Given, As one of the body's first natural defences, the barrier properties of skin provide an obstacle to the successful outcome of any skin drug therapy. To elucidate the mechanisms underlying this barrier, reductionist strategies have designed several models with different levels of complexity, using non-biological and biological components. Besides the detail of information and resemblance to human skin in vivo, offered by each in vitro model, the technical and economic efforts involved must also be considered when selecting the most suitable model. This review provides an outline of the commonly used skin models, including healthy and diseased conditions, in-house developed and commercialized models, their advantages and limitations, and an overview of the new trends in skin-engineered models.

Versatile modelling of polyoxymethylene-water partition coefficients for hydrophobic organic contaminants using linear and nonlinear approaches

Environmental fate or transport of hydrophobic organic contaminants (HOCs) depends on the partitioning properties of compounds within various environmental phases. Due to the wide application of polyoxymethylene (POM) in the passive sampling technique, several in silico models were developed to predict POM-water partition coefficients (K_POM-w) in accordance with the guidelines of the Organization for Economic Cooperation and Development (OECD). It is an attempt to combine conventional linear method (multiple linear regression, MLR) and popular nonlinear algorithm (artificial neural network, ANN) for estimating partition coefficients of HOCs. All models were performed on a dataset of 210 chemicals from 13 different classes. The polyparameter linear free energy relationship (pp-LFER) model included 5 molecular descriptors, namely, E, S, A, B and V, and predicted log K_POM-w with R²_adj of 0.825. The values of statistical parameters including R²_adj, Q²_ext, RMSE_tra and RMSE_ext for quantitative structure-property relationship (QSPR)-MLR and QSPR-ANN models with four descriptors (ALOGP, MeanDD, E1m and Mor24s) were: (0.928, 0.877, 0.498 and 0.649) and (0.943, 0.905, 0.443 and 0.571), with high similarity for both models, which confirmed the robustness, significance, and remarkable prediction accuracy of the QSPR models. Moreover, the mechanism interpretation revealed that the molecular volume and hydrophobicity had a major impact on distribution procedure of HOCs. The models developed herein, with the broad applicability domain (AD), provide suitable tools to fill the experimental data gap for untested chemicals and help researchers better understand the mechanistic basis of adsorption behavior of POM.

Estimation of passive gastrointestinal absorption and membrane retention using PAMPA test, quantitative structure-permeability and quantitative structure-retention relationship analyses of ethylenediamine-N,N'-di-2-(3-cyclohexyl)propanoic acid and 1,3-propanediamine-N,N'-di-2-(3-cyclohexyl)propanoic acid derivatives

Passive gastrointestinal absorption and membrane retention of twelve esters of (S,S)-ethylenediamine-N,N'-di-2-(3-cyclohexyl)propanoic acid (EDCP) and (S,S)-1,3-propanediamine-N,N'-di-2-(3-cyclohexyl)propanoic acid (PDCP), as well as of these two non-esterified acids were estimated using PAMPA test. Artificial PAMPA membrane used in this study for the simulation of gastrointestinal barrier was solution of egg lecithin in dodecane (1 % w/v). All tested compounds belong to class III (high membrane retention and low permeation), whereas EDCP, dipentyl ester of PDCP (DPE-PDCP) and diisopentyl ester of PDCP (DIPE-PDCP) belong to class I (negligible membrane retention and low permeation). Finally, quantitative structure - permeability and structure - retention relationships models were created in order to find quantitative relationships between physico-chemical properties of tested compounds and PAMPA membrane permeability/membrane retention parameters. Statistically the most reliable models were analysed and used for the design of new compounds for which favourable membrane permeability and retention can be expected.

Investigation of metabolic properties and effects of 17β-carboxamide glucocorticoids on human peripheral blood leukocytes

The biological activity of three previously synthesized 17β-carboxamide glucocorticoids (BG, BEG, and MPEA) was tested in vitro on mitogen stimulated and non-stimulated peripheral blood mononuclear cells (MNCs) and granulocytes from human healthy donors, and the results were compared to the conventional glucocorticoid dexamethasone. The tested 17β-carboxamide glucocorticoids did not induce decreases in MNC viability and proliferation, while modulation of reactive oxygen species (ROS) synthesis in granulocytes was dependent on the cell donor. The obtained results indicate the possibility of avoidance of strong lymphocyte suppression, which is generally recognized during administration of conventional glucocorticoids. Furthermore, the metabolism of the tested derivatives was predicted in silico. The predicted metabolites were synthesized and the in silico results were confirmed by in vitro evaluation of the metabolism of BG, BEG, and MPEA in human serum and in cultures of peripheral blood MNCs. The results of the biological activity and metabolism evaluation and of previous in vivo evaluations of biological activity indicate the soft drug nature of BG, BEG, and MPEA. In order to be fully considered as soft glucocorticoids, further investigations on the toxicity and activity of the formed metabolites are required.

Evaluation of Biological Activity and Computer-Aided Design of New Soft Glucocorticoids

Soft glucocorticoids are compounds that are biotransformed to inactive and non-toxic metabolites and have fewer side effects than traditional glucocorticoids. A new class of 17β-carboxamide steroids has been recently introduced by our group. In this study, local anti-inflammatory activity of these derivatives was evaluated by use of the croton oil-induced ear edema test. Glucocorticoids with the highest maximal edema inhibition (MEI) were pointed out, and the systemic side effects of those with the lowest EC₅₀ values were significantly lower in comparison to dexamethasone. A 3D-QSAR model was created and employed for the design of 27 compounds. By use of the sequential combination of ligand-based and structure-based virtual screening, three compounds were selected from the ChEMBL library and used as a starting point for the design of 15 derivatives. Molecular docking analysis of the designed derivatives with the highest predicted MEI and relative glucocorticoid receptor binding affinity (20, 22, 24-1, 25-1, 27, VS7, VS13, and VS14) confirmed the presence of interactions with the glucocorticoid receptor that are important for the activity.

Application of biopartitioning micellar chromatography and QSRR modeling for prediction of gastrointestinal absorption and design of novel β-hydroxy-β-arylalkanoic acids

Gastrointestinal absorption of thirteen novel β-hydroxy-β-arylalkanoic acids (HAA) with anti-inflammatory activity was predicted by use of biopartitioning micellar chromatography and compared to ibuprofen. All tested HAA have lower retention factors (k) and lower expected gastrointestinal absorption than ibuprofen, whereas derivatives with the highest values of k are 1C, 2APTF and 2C. Quantitative structure-retention relationship (QSRR) analysis was performed in order to identify molecular descriptors with the highest influence on k and ANN(k) model was selected as optimal. Descriptors which form this model (nBM, P_VSA_LogP_8 and Eta_L) indicate that replacement of phenyl ring with a saturated or partially unsaturated one, as well as presence of halogens and nitro group should positively affect k values. On the basis of these conclusions, six novel HAA were designed and selected QSRR model was used for the prediction of their k values.

In vitro skin models as a tool in optimization of drug formulation

(Trans)dermal drug therapy is gaining increasing importance in the modern drug development. To fully utilize the potential of this route, it is important to optimize the delivery of active ingredient/drug into/through the skin. The optimal carrier/vehicle can enhance the desired outcome of the therapy therefore the optimization of skin formulations is often included in the early stages of the product development. A rational approach in designing and optimizing skin formulations requires well-defined skin models, able to identify and evaluate the intrinsic properties of the formulation. Most of the current optimization relies on the use of suitable ex vivo animal/human models. However, increasing restrictions in use and handling of animals and human skin stimulated the search for suitable artificial skin models. This review attempts to provide an unbiased overview of the most commonly used models, with emphasis on their limitations and advantages. The choice of the most applicable in vitro model for the particular purpose should be based on the interplay between the availability, easiness of the use, cost and the respective limitations.

Biopartitioning micellar chromatography as a predictive tool for skin and corneal permeability of newly synthesized 17β-carboxamide steroids

In this paper, human skin and corneal permeability of twenty-two newly synthesized 17β-carboxamide steroids was predicted using biopartitioning micellar chromatography (BMC). These compounds are potential soft glucocorticoids with local anti-inflammatory activity when applied to the skin or eye. BMC systems are used to simulate physicochemical properties of human skin (BMC-skin) and cornea (BMC-cornea). Micellar mobile phase, consisted of 0.04 M solution of polyoxyethylene (23) lauryl ether (Brij 35), was prepared at different pH values - 5.50 (BMC-skin) and 7.50 (BMC-cornea). Retention factors (k), obtained by use of BMC, were calculated for all newly synthesized 17β-carboxamide steroids as well as for parent glucocorticoids (hydrocortisone, prednisolone, methylprednisolone, dexamethasone and betamethasone). Good correlation was obtained between BMC-skin retention factors and permeability coefficients calculated by use of the artificial membrane that simulates stratum corneum of the human skin. Quantitative structure-retention relationship (QSRR) study was performed in order to explain retention factors of these compounds in the tested BMC systems. ANN-QSRR(k), PLS-QSRR(k) and MLR-QSRR(k) models, created by use of BMC-skin retention data, were compared and optimal model (PLS-QSRR(k)) was selected. Molecular descriptors of the selected model indicate that lipophilicity and number of short C-C fragments of tested compounds have the strongest influence on the retention in the BMC-skin system and presumably on their in vivo permeability through human skin. The same model can be applied to the BMC-cornea system and the same conclusion can be drawn for corneal permeability. This model could be used as a predictive tool for the synthesis of novel 17β-carboxamide steroids with desirable permeability through human skin or cornea, depending on their potential pharmacological application.