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

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.

Using membrane-water partition coefficients in a critical membrane burden approach to aid the identification of neutral and ionizable chemicals that induce acute toxicity below narcosis levels

The risk assessment of thousands of chemicals used in our society benefits from adequate grouping of chemicals based on the mode and mechanism of toxic action (MoA). We measure the phospholipid membrane-water distribution ratio (D_MLW) using a chromatographic assay (IAM-HPLC) for 121 neutral and ionized organic chemicals and screen other methods to derive D_MLW. We use IAM-HPLC based D_MLW as a chemical property to distinguish between baseline narcosis and specific MoA, for reported acute toxicity endpoints on two separate sets of chemicals. The first set comprised 94 chemicals of US EPA's acute fish toxicity database: 47 categorized as narcosis MoA, 27 with specific MoA, and 20 predominantly ionic chemicals with mostly unknown MoA. The narcosis MoA chemicals clustered around the median narcosis critical membrane burden (CMB_narc) of 140 mmol kg^-1 lipid, with a lower limit of 14 mmol kg^-1 lipid, including all chemicals labelled Narcosis_I and Narcosis_II. This maximum 'toxic ratio' (TR) between CMB_narc and the lower limit narcosis endpoint is thus 10. For 23/28 specific MoA chemicals a TR >10 was derived, indicative of a specific adverse effect pathway related to acute toxicity. For 10/12 cations categorized as "unsure amines", the TR <10 suggests that these affect fish via narcosis MoA. The second set comprised 29 herbicides, including 17 dissociated acids, and evaluated the TR for acute toxic effect concentrations to likely sensitive aquatic plant species (green algae and macrophytes Lemna and Myriophyllum), and non-target animal species (invertebrates and fish). For 21/29 herbicides, a TR >10 indicated a specific toxic mode of action other than narcosis for at least one of these aquatic primary producers. Fish and invertebrate TRs were mostly <10, particularly for neutral herbicides, but for acidic herbicides a TR >10 indicated specific adverse effects in non-target animals. The established critical membrane approach to derive the TR provides for useful contribution to the weight of evidence to bin a chemical as having a narcosis MoA or less likely to have acute toxicity caused by a more specific adverse effect pathway. After proper calibration, the chromatographic assay provides consistent and efficient experimental input for both neutral and ionizable chemicals to this approach.

Simultaneous effect of different chromatographic conditions on the chromatographic retention of pentapeptide derivatives (HGRFG and NPNPT)

Introduction: Oligopeptides exhibit great prospects for clinical application and its separation is of great importance in new drug development. Methods: To accurately predict the retention of pentapeptides with analogous structures in chromatography, the retention times of 57 pentapeptide derivatives in seven buffers at three temperatures and four mobile phase compositions were measured via reversed-phase high-performance liquid chromatography. The parameters ( k H A , k A , and p K a ) of the acid-base equilibrium were obtained by fitting the data corresponding to a sigmoidal function. We then studied the dependence of these parameters on the temperature (T), organic modifier composition (φ, methanol volume fraction), and polarity ( P m N parameter). Finally, we proposed two six-parameter models with (1) pH and T and (2) pH and φ or P m N as the independent variables. These models were validated for their prediction capacities by linearly fitting the predicted retention factor k-value and the experimental k-value. Results: The results showed that log k H A and log k A exhibited linear relationships with 1 / T , φ or P m N for all pentapeptides, especially for the acid pentapeptides. In the model of pH and T, the correlation coefficient (R²) of the acid pentapeptides was 0.8603, suggesting a certain prediction capability of chromatographic retention. Moreover, in the model of pH and φ or P m N , the R² values of the acid and neutral pentapeptides were greater than 0.93, and the average root mean squared error was approximately 0.3, indicating that the k-values could be effectively predicted. Discussion: In summary, the two six-parameter models were appropriate to characterize the chromatographic retention of amphoteric compounds, especially the acid or neutral pentapeptides, and could predict the chromatographic retention of pentapeptide compounds.

Determination of lipid-water partition coefficient of neutral and ionic drugs by liposome electrokinetic chromatography

Profiling of lipid-water partition coefficients (K_L/W ) of drugs is an essential issue during the early stage of drug development. In this study, two liposomes, including 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC) + cholesterol (Chol) (DSPC/Chol liposomes) and soybean lecithin (SPC) + Chol (SPC/Chol liposomes), were prepared for the liposome electrokinetic chromatography (LEKC) analysis, and the logarithm of lipid-water partition coefficients (log K_L/W ) of neutral and ionic drugs were determined based on an iterative method. The log K_L/W values determined by the SPC/Chol or DSPC/Chol liposomes LEKC were linearly fitted, which showed a good fitting coefficient (R² = 0.89). Furthermore, the linear relationship between the data obtained from LEKC system and octanol-water system, immobilized artificial membrane, Caco-2 cell model, and software prediction was analyzed, respectively. Results illustrated that DSPC/Chol liposomes or SPC/Chol liposomes had a good linear relationship with Caco-2 cell model, and R² was 0.81 and 0.72, respectively. Moreover, the linear free energy relationship analysis suggested that the solute volume, hydrogen bond basicity, and J^- were the main descriptors that drove the partition process of solutes in the SPC/Chol or DSPC/Chol LEKC system. In addition, the normalized properties of the SPC/Chol and DSPC/Chol LEKC systems through linear free energy relationship analysis were very close. In short, DSPC/Chol liposomes are more suitable for simulating cell membranes than SPC/Chol liposomes, and the developed LEKC is an effective partitioning model for measuring the log K_L/W of drugs.

Screening of cardioprotective diseases bioactive components from Danshen extracts and LC-MS analysis

A rapid and efficient analysis and screening method is adopted for cell affinity capture coupled with HPLC-MS (CAC-HPLC-MS) analysis of bioactive components that have possible efficiency against cardiovascular diseases. This method involves affinity capture, concentration, and separation of bioactive components from Danshen library using oxidatively damaged endothelial cells induced by H₂ O₂ , as well as analysis and identification of targeted compounds with HPLC and MS. It combines the specific interaction between cell membrane receptors and bioactive components with the powerful analysis and identification function of HPLC-MS. The CAC-HPLC-MS method was also used for analysis and screening of bioactive components from crude extracts of Danshen. A total of 19 components were found to be bound to oxidatively damaged endothelial cells with seven of these identified. Existing literature confirms that these seven components have many activities related to cardioprotective diseases. Therefore, the combination of biological affinity capture with HPLC-MS should be regarded as an attractive method with great potential for rapid and efficient screening of bioactive components related to anti-cardiovascular diseases from natural product libraries.

Recent applications of immobilized biomaterials in herbal analysis

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

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.