Immobilized Artificial Membrane Chromatography Research Articles

Modeling the Blood-Brain Barrier Permeability of Potential Heterocyclic Drugs via Biomimetic IAM Chromatography Technique Combined with QSAR Methodology.

Penetration through the blood-brain barrier (BBB) is desirable in the case of potential pharmaceuticals acting on the central nervous system (CNS), but is undesirable in the case of drug candidates acting on the peripheral nervous system because it may cause CNS side effects. Therefore, modeling of the permeability across the blood-brain barrier (i.e., the logarithm of the brain to blood concentration ratio, log BB) of potential pharmaceuticals should be performed as early as possible in the preclinical phase of drug development. Biomimetic chromatography with immobilized artificial membrane (IAM) and the quantitative structure-activity relationship (QSAR) methodology were successful in modeling the blood-brain barrier permeability of 126 drug candidates, whose experimentally-derived lipophilicity indices and computationally-derived molecular descriptors (such as molecular weight (MW), number of rotatable bonds (NRB), number of hydrogen bond donors (HBD), number of hydrogen bond acceptors (HBA), topological polar surface area (TPSA), and polarizability (α)) varied by class. The QSARs model established by multiple linear regression showed a positive effect of the lipophilicity (log kw, IAM) and molecular weight of the compound, and a negative effect of the number of hydrogen bond donors and acceptors, on the log BB values. The model has been cross-validated, and all statistics indicate that it is very good and has high predictive ability. The simplicity of the developed model, and its usefulness in screening studies of novel drug candidates that are able to cross the BBB by passive diffusion, are emphasized.

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.

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.

Predicting Pharmacokinetic Properties of Potential Anticancer Agents via Their Chromatographic Behavior on Different Reversed Phase Materials.

The Quantitative Structure-Activity Relationship (QSAR) methodology was used to predict biological properties, i.e., the blood–brain distribution (log BB), fraction unbounded in the brain (fu,brain), water-skin permeation (log Kp), binding to human plasma proteins (log Ka,HSA), and intestinal permeability (Caco-2), for three classes of fused azaisocytosine-containing congeners that were considered and tested as promising drug candidates. The compounds were characterized by lipophilic, structural, and electronic descriptors, i.e., chromatographic retention, topological polar surface area, polarizability, and molecular weight. Different reversed-phase liquid chromatography techniques were used to determine the chromatographic lipophilicity of the compounds that were tested, i.e., micellar liquid chromatography (MLC) with the ODS-2 column and polyoxyethylene lauryl ether (Brij 35) as the effluent component, an immobilized artificial membrane (IAM) chromatography with phosphatidylcholine column (IAM.PC.DD2) and chromatography with end-capped octadecylsilyl (ODS) column using aqueous solutions of acetonitrile as the mobile phases. Using multiple linear regression, we derived the statistically significant quantitative structure-activity relationships. All these QSAR equations were validated and were found to be very good. The investigations highlight the significance and possibilities of liquid chromatographic techniques with three different reversed-phase materials and QSARs methods in predicting the pharmacokinetic properties of our important organic compounds and reducing unethical animal testing.

Affinity of Antifungal Isoxazolo[3,4-b]pyridine-3(1H)-Ones to Phospholipids in Immobilized Artificial Membrane (IAM) Chromatography.

Currently, rapid evaluation of the physicochemical parameters of drug candidates, such as lipophilicity, is in high demand owing to it enabling the approximation of the processes of absorption, distribution, metabolism, and elimination. Although the lipophilicity of drug candidates is determined using the shake flash method (n-octanol/water system) or reversed phase liquid chromatography (RP-LC), more biosimilar alternatives to classical lipophilicity measurement are currently available. One of the alternatives is immobilized artificial membrane (IAM) chromatography. The present study is a continuation of our research focused on physiochemical characterization of biologically active derivatives of isoxazolo[3,4-b]pyridine-3(1H)-ones. The main goal of this study was to assess the affinity of isoxazolones to phospholipids using IAM chromatography and compare it with the lipophilicity parameters established by reversed phase chromatography. Quantitative structure–retention relationship (QSRR) modeling of IAM retention using differential evolution coupled with partial least squares (DE-PLS) regression was performed. The results indicate that in the studied group of structurally related isoxazolone derivatives, discrepancies occur between the retention under IAM and RP-LC conditions. Although some correlation between these two chromatographic methods can be found, lipophilicity does not fully explain the affinities of the investigated molecules to phospholipids. QSRR analysis also shows common factors that contribute to retention under IAM and RP-LC conditions. In this context, the significant influences of WHIM and GETAWAY descriptors in all the obtained models should be highlighted.

Biopartitioning micellar chromatography under different conditions: Insight into the retention mechanism and the potential to model biological processes

In the present study, 88 structurally- diverse drugs were investigated by biopartitioning micellar chromatography (BMC) using Brij-35 as surfactant under different chromatographic conditions. It was found that temperature and presence of NaCl have only a minor effect in BMC retention. Correlation of BMC retention factors with octanol-water partitioning required the inclusion of fractions of ionized species as additional parameters, showing that there is a weaker effect of ionization in BMC environment. Compared to Immobilized Artificial Membrane (IAM) Chromatography, BMC retention factors cover a relatively narrow span, two-fold smaller than retention factors on IAM stationary phases as a result of the presence of micelles facilitating elution of lipophilic compounds and the absence of secondary attractive electrostatic interactions in the BMC environment. Similarities/dissimilarities between BMC, octanol-water partitioning and IAM Chromatography were investigated by Linear Free Energy Relationships (LSER). BMC retention factors were used to construct relationships with cell permeability,% Human Oral Absorption (%HOA) and Plasma Protein Binding (%PPB). Linear BMC models were obtained with Caco-2 cell lines and Parallel Artificial Membrane Permeability Assay (PAMPA). For %HOA, a hyperbolic model was established upon incorporation of topological polar surface area (tPSA) as additional parameter. A sigmoidal model was constructed for %PPB and a linear one for the corresponding thermodynamic binding constant logK. In both cases inclusion of the fraction of anionic species with a positive sign was required reflecting the preference of human albumin for acidic drugs.

The Limited Contribution of the Analyte Partition to the Water-Rich Layer in Immobilized Artificial Membrane Chromatography with an Acetonitrile-Rich Binary Mobile Phase

Drug-induced phospholipidosis, a side effect of drugs, is associated with drug–membrane binding. Hydrophobic interactions of the drug with the membrane and polar interactions of the drug with the membrane are involved. For risk predictions, membrane binding studies often give false results for strongly hydrophobic compounds and basic hydrophilic compounds because the effects of the hydrophobic interactions overshadow the effects of the polar interactions. Therefore, separate assessments of hydrophobic partitioning and polar interactions are needed. However, a screening method focusing on the polar interactions between drugs and membranes has not yet been reported. In the present study, the retention behavior of an immobilized artificial membrane (IAM) column using a binary mobile phase with a high acetonitrile content was studied to clarify the contribution of the analyte partition to the water-rich layer on the surface of the packed material, which may interfere with the assessment of the polar interactions with the membrane. For acetonitrile contents greater than 50%, the retention factor of propranolol increased as a result of the hydrophilic interactions. The Van’t Hoff plot suggested that the adsorptive retention of the analyte became dominant with high acetonitrile content in the mobile phase, in contrast to the hydrophobic partitioning that occurred for low acetonitrile content. Hydrophilic neutral compounds (e.g., thiourea and mesityl oxide) were not retained. The addition of salts to the mobile phase decreased the propranolol retention. Even with the addition of a kosmotropic salt, the decreased retention indicated that hydrophilic partitioning to the water-enriched layer was unlikely to be the major mechanism. In addition to ionic interactions, other polar interactions were presumed to be involved. The relationships between the retention factor and the log P or pKa values also supported this conclusion. The results of this study suggest that there is potential for IAM chromatography to be used as a tool to estimate the contribution of the polar interactions in overall drug–membrane interactions, which can aid in predicting the risk of phospholipidosis.

Immobilized artificial membrane chromatography as a tool for the prediction of ecotoxicity of pesticides

The potential of Immobilized Artificial Membrane (IAM) chromatography to predict ecotoxicological endpoints of pesticides was investigated. For this purpose, retention factors of 39 structurally-diverse pesticides were measured on an IAM stationary phase. A representative test set of 6 pesticides was carefully selected. The training set, involving the remaining pesticides for which experimental data were available, served to establish linear IAM models with LC50/EC50 values in a series of aquatic organisms involving Rainbow Trout, Fathead Minnow, Bluegill Sunfish, Sheepshead Minnow, Eastern Oyster and Water Flea as well as LD50 values in honey bee, compiled from literature sources. For reasons of comparison, corresponding models were derived by replacing IAM retention factors with octanol-water partition coefficients (logP). Considering the similar regression equations obtained for the 4 fish species, general models to predict toxicity in fish were established. Most models were improved upon inclusion of additional physicochemical parameters. The positive contribution of Molecular Weight to ecotoxicity along with the positive sign of hydrogen bond indices in most cases implies that toxic action is manifested mainly by accumulation on the membrane rather than through diffusion across them. IAM models are generally followed by better statistics and superior predictive performance than those based on experimental or computed logP. Predictions based on IAM chromatography were comparable or even superior with those performed by EPI Suite Software. Hence, IAM retention factors are suggested as promising indices in order to screen or rank chemicals with respect to their ecotoxicological risk, especially in the case of new entities.

Immobilized artificial membrane chromatography: from medicinal chemistry to environmental sciences

Immobilized Artificial Membrane (IAM) chromatography constitutes a valuable tool for medicinal chemists to prioritize drug candidates in early drug development. The retention on IAM stationary phases encodes lipophilicity, electrostatic and other secondary interactions contrary to traditional octanol-water partitioning. An increasing number of publications in recent years have suggested that IAM indices, including isocratic log k(IAM) or extrapolated log kw(IAM) retention factors, chromatographic hydrophobicity index CHI(IAM) or the polarity parameter Δlog kw(IAM) can successfully model the passage of xeniobiotics through biological membranes and barriers and predict pharmacokinetic properties, often in combination with additional descriptors. Examples referring to the modeling of human oral absorption, blood-brain penetration and skin partition are described. More recently, IAM chromatography has been applied to estimate toxicological endpoints in regard to drug safety, such as phospholipidosis potential, or in regard to chemical risk hazards including the bioconcentration factor and aquatic organisms’ toxicity. The promising results in both medicinal chemistry and in environmental science in combination with the speed, reproducibility and low analyte consumption suggest that a broader application of IAM chromatography in the early drug discovery process and in ecotoxicity may save time and money in initial drug candidate selection and will contribute to a reduced risk hazard of chemicals.

PH-dependent surface electrostatic effects in retention on immobilized artificial membrane chromatography: Determination of the intrinsic phospholipid-water sorption coefficients of diverse analytes

The passive membrane permeability of drugs may be potentially predicted by phospholipid-water sorption coefficient (KPLIPW) through immobilized artificial membrane (IAM) chromatography. However, for predominantly ionized compounds, unexpected confounding electrostatic interaction would influence the accurate determination of KPLIPW, accompanied by the mobile phase with varied pH and ionic strength. In order to measure the intrinsic phospholipid-water sorption coefficient (KIAM,intr) for diverse analytes, a mathematic model by characterizing the confounding electrostatic effects was developed in this study. Based on the developed electrostatic model, additional electrostatic repulsion/attraction interactions with the charged IAM surface were characterized for organic cations/anions. Considering that most of the IAM chromatography data was determined under physiological conditions, the KPLIPW values of all compounds were calculated with the ionic strength of 0.1 M and the pH value of 7. Generally, KPLIPW was hardly affected by the pH and ionic strength of mobile phase for those electroneutral compounds. KIAM,intr was 0.28 log units smaller than apparent phospholipid-water sorption coefficient (KIAM,app) for cations. In contrast, KIAM,intr was larger than KIAM,app by 0.28 log units for anions. Herein, KIAM,intr of diverse analytes can be easily calculated by the developed electrostatic model. For application, KIAM,intr was further compared with intrinsic Caco-2 permeability, and good sigmoidal correlations (R2 = 0.76) were established between them for organic cations and neutral compounds but not for organic anions.

Phospholipid-based Immobilized Artificial Membrane (IAM) Chromatography: A Powerful Tool to Model Drug Distribution Processes.

A review of applications of the Immobilized Artificial Membrane (IAM) chromatography in drug discovery is given. IAM chromatography is presented as a tool to predict the interactions of solutes with biomembranes, blood-brain barrier permeability, volume of distribution, oral and skin absorption of drugs and compared to other in vitro techniques used to study drug bioavailability (caco-2 cells, liposome partition). Unbound phosphatidylcholine based stationary phases are also discussed. Some new trends and ideas in the IAM chromatography are presented.

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 KwIAM data. Then we applied block relevance (BR) analysis to extract from PLS models the relative contribution of intermolecular forces governing log KwIAM and Δlog KwIAM (a combined descriptor calculated from log KwIAM). Finally, the relationship between log KwIAM, Δlog KwIAM 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.

Retention behavior of flavonoids on immobilized artificial membrane chromatography and correlation with cell-based permeability.

The aim of the study was to investigate the immobilized artificial membrane (IAM) retention mechanism for a set of flavonoids and to evaluate the potential of IAM chromatography to model Caco-2 permeability. For this purpose, the retention behavior of 41 flavonoid analogs on two IAM stationary phases, IAM.PC.MG and IAM.PC.DD2, was investigated. Correlations between retention factors, logkw(IAM) and octanol-water partitioning (logP) were established and the role of hydroxyl groups of flavonoids to the underlying retention mechanism was explored. IAM retention and logP values were used to establish sound linear models with Caco-2 permeability (logPapp ) taken from the literature. Both stepwise regression and multivariate analysis confirmed the contribution of hydrogen bond descriptors, as additional parameters in the either logkw(IAM) or logP models. Retention factors on both IAM stationary phases showed comparable performance with n-octanol-water partitioning towards Caco-2 permeability.

The use of immobilized artificial membrane chromatography to predict bioconcentration of pharmaceutical compounds

The potential of immobilized artificial membrane chromatography (IAM) to predict bioconcentration factors (BCF) of pharmaceutical compounds in aquatic organisms was studied. For this purpose, retention factors extrapolated to pure aqueous phase, logkw(IAM), of 27 drugs were measured on an IAM stationary phase, IAM.PC.MG type. The data were combined with retention factors on two IAM columns, IAM.PC.MG and IAM.PC.DD2 types, reported previously by our research group and correlated with logBCF values predicted by Estimation Program Interface (EPI Suite) Software. Linear models were established upon exclusion of ionic or highly hydrophilic nonionic drugs, for which a constant value of logBCF equal to 0.50 was arbitrarily assigned by EPI Suite Software. As additional physicochemical parameter BioWin5 proved to be statistically significant, expressing the decrease of bioaccumulation potential as a result of biodegradation in the aquatic environment. The constructed IAM model was successfully validated by application to a set of pharmaceuticals, whose experimental BCF values are available. Better predictions compared to EPI Suite Software were achieved for the dataset under study. Since bioconcentration process involves electrostatic interactions, IAM retention may be a better measure for BCF values, especially for ionic species, compared to octanol-water partition coefficients widely implemented in environmental sciences. The developed approach can be considered as a novel tool for the prediction of bioconcentration of pharmaceutical compounds in aquatic organisms in order to minimize further experimental assays in the future.

Quantitative structure–retention relationships of flavonoids unraveled by immobilized artificial membrane chromatography

The pharmacokinetic properties of flavonoids with differing degrees of lipophilicity were investigated using immobilized artificial membranes (IAMs) as the stationary phase in high performance liquid chromatography (HPLC). For each flavonoid compound, we investigated whether the type of column used affected the correlation between the retention factors and the calculated octanol/water partition (log Poct). Three-dimensional (3D) molecular descriptors were calculated from the molecular structure of each compound using i) VolSurf software, ii) the GRID method (computational procedure for determining energetically favorable binding sites in molecules of known structure using a probe for calculating the 3D molecular interaction fields, between the probe and the molecule), and iii) the relationship between partition and molecular structure, analyzed in terms of physicochemical descriptors. The VolSurf built-in Caco-2 model was used to estimate compound permeability. The extent to which the datasets obtained from different columns differ both from each other and from both the calculated log Poct and the predicted permeability in Caco-2 cells was examined by principal component analysis (PCA). The immobilized membrane partition coefficients (kIAM) were analyzed using molecular descriptors in partial least square regression (PLS) and a quantitative structure–retention relationship was generated for the chromatographic retention in the cholesterol column. The cholesterol column provided the best correlation with the permeability predicted by the Caco-2 cell model and a good fit model with great prediction power was obtained for its retention data (R2=0.96 and Q2=0.85 with four latent variables).

The potential of immobilized artificial membrane chromatography to predict human oral absorption

The potential of immobilized artificial membrane (IAM) chromatography to estimate human oral absorption (%HOA) was investigated. For this purpose, retention indices on IAM stationary phases reported previously by our group or measured by other authors under similar conditions were used to model %HOA data, compiled from literature sources. Considering the pH gradient in gastrointestinal tract, the highest logkw(IAM) values were considered, obtained either at pH7.4 or 5.5, defined as logkw(IAM)best. Non linear models were established upon introduction of additional parameters and after exclusion of drugs which are substrates either to efflux or uptake transporters. The best model included Abraham's hydrogen-bond acidity parameter, molecular weight as well as the positively and negatively charged molecular fractions. For reasons of comparison between IAM chromatography and traditional lipophilicity, corresponding models were derived by replacing IAM retention factors with octanol–water distribution coefficients (logD). An overexpression of electrostatic interactions with phosphate anions was observed in the case of IAM retention as expressed by the negative contribution of the positively charged fraction F+. The same parameter is statistically significant also in the logD model, but with a positive sign, indicating the attraction of basic drugs in the negatively charged inner membrane. To validate the obtained models a blind test set of 22 structurally diverse drugs was used, whose logkw(IAM)best values were determined and analyzed in the present study under similar conditions.IAM retention factors were further compared with MDCK cell lines permeability data taken from literature for a set of validation drugs. The overexpression of electrostatic interactions with phosphate anions on IAM surface was also evident in respect to MDCK permeability. In contrast to the clear classification between drugs with high and poor (or intermediate) absorption provided by MDCK permeability, %HOA plotted versus both IAM and logD data result in a saturation curve with a smoother ascending line.

Preparation and First Preclinical Evaluation of [18F]FE@SNAP: A Potential PET Tracer for the Melanin Concentrating Hormone Receptor 1 (MCHR1)

The melanin-concentrating hormone (MCH) system is a new target for the treatment of human disorders. Since the knowledge of the MCH system’s involvement in a variety of pathologies (obesity, diabetes, and deregulation of metabolic feedback mechanism) is based on in vitro or preclinical studies, a suitable positron emission tomography (PET) tracer needs to be developed. We herein present the preparation and first preclinical evaluation of [18F]FE@SNAP – a new PET tracer for MCH receptor-1 (MCHR1). The synthesis was performed using a microfluidic device. Preclinical evaluation included binding affinity, plasma stability, plasma free fraction, stability against the cytochrome P-450 (CYP450) system using liver microsomes, stability against carboxyl-esterase, and methods to assess the penetration of the blood-brain barrier (BBB) such as logD analysis and immobilized artificial membrane (IAM) chromatography. Levels at 374 ± 202 MBq [18F]FE@SNAP were obtained after purification. The obtained Kd value of [18F]FE@SNAP was 2.9 nM. [18F]FE@SNAP evinced high stability against carboxylesterase, CYP450 enzymes, and in human plasma. LogD (3.83) and IAM chromatography results (Pm=0.51) were in the same range as for known BBB-penetrating compounds. The synthesis of [18F]FE@SNAP was reliable and successful. Due to high binding affinity and stability, [18F]FE@SNAP is a promising tracer for MCHR1.

Drug–Membrane Interaction on Immobilized Liposome Chromatography Compared to Immobilized Artificial Membrane (IAM), Liposome/Water, and Octan‐1‐ol/Water Systems

AbstractThe objective of this study was to investigate drug–membrane interaction by immobilized liposome chromatography (ILC; expressed as lipophilicity index log Ks) and the comparison with lipophilicity indices obtained by liposome/H2O, octan‐1‐ol/H2O, and immobilized artificial membrane (IAM) systems. A set of structurally diverse monofunctional compounds and drugs (nonsteroidal anti‐inflammatory drugs and β‐blockers) were selected in this study. This set of solutes consists of basic or acidic functionalities which are positively or negatively charged at physiological pH 7.4. No correlation was found between log Ks from ILC and lipophilicity indices from any of the other membrane model systems for the whole set of compounds. For structurally related compounds, significant correlations could be established between log Ks from ILC and lipophilicity indices from IAM chromatography and octan‐1‐ol/H2O. However, ILC and liposome/H2O systems only yield parallel partitioning information for structurally related large molecules. For hydrophilic compounds, the balance between electrostatic and hydrophobic interactions dominating drug partitioning is different in these two systems.

Screening and Identification of Permeable Components of Radix et Rhizoma Rhei Extract by Use of Immobilized Artificial Membrane Chromatography

The objective of this work was to screen and identify permeable components of Radix et Rhizoma Rhei extract by use of immobilized artificial membrane chromatography (IAMC) then to investigate the intestinal absorption behavior of these components and the mechanism of absorption at three concentrations (0.3, 0.6, and 1.5 mg mL−1) by use of the in situ rat intestinal absorption model. The percentage absorption of permeable components was then correlated with their retention behavior by using mobile phases of three different pH (5.0, 6.0, and 7.0) containing buffers of two different ionic strength (10 and 50 mmol L−1). There was better correlation between percentage intestinal absorption and IAMC retention at pH 6.0 (r 2 = 0.82) than at pH 5.0 (r 2 = 0.64) or 7.0 (r 2 = 0.74). The correlation coefficients suggest that most of the permeable components of Radix et Rhizoma Rhei were mainly absorbed by a passive diffusion mechanism. The four main permeable components were identified as rhein, aloe-emodin, chrysophanol, and emodin by comparison of chromatographic and spectrometric behavior with those of reference standards. IAMC seems useful as a promising rapid screening technique for identification of bioactive components in complex systems, e.g. traditional Chinese medicines.

Toward an Optimal Blood−Brain Barrier Shuttle by Synthesis and Evaluation of Peptide Libraries

Several peptide families containing N-methylated amino acids were designed and synthesized using solid-phase peptide synthesis (SPPS). The permeability and phospholipophilicity of these compounds were studied by parallel artificial membrane permeability assay (PAMPA) and immobilized artificial membrane chromatography (IAMC) to select the best peptides in terms of length, terminal groups, and amino acid replacement to be used as carriers that pass through a model of the blood-brain barrier (BBB) by passive diffusion. Furthermore, the enzymatic stability of these peptides in human serum and their cell viability by MTT assay were tested. These peptide families showed great stability and nontoxicity. The three peptides that showed the greatest permeability were coupled to levodopa (a nonpassive permeating drug) and assessed. These peptides effectively transferred levodopa through an artificial membrane by means of passive diffusion.