Quantitative Retention-activity Relationship Models Research Articles

Drug affinity to human serum albumin prediction by retention of cetyltrimethylammonium bromide pseudostationary phase in micellar electrokinetic chromatography and chemically advanced template search descriptors

The development of high-throughput methods for the estimation of physicochemical and biological properties of drug candidates is highly desired in the pharmaceutical landscape. Affinity to plasma protein is one of the most important biological properties, which should be taken under concern during the design and assessment of future potential medicines. The main goal of this study was to develop a quantitative retention-activity relationship model, with rationalized in vivo and in silico approach to predict the affinity to human serum albumin (HSA), which is one of the most important plasma proteins. To achieve this goal, a set of 27 chemically diverse drugs with known affinity to HSA were analyzed by micellar electrokinetic chromatography (MEKC). The proposed model for HSA affinity assessment was based on retention in hexadecyltrimethylmonium bromide (CTAB) pseudostationary phase and chemically advanced template search (CATS) pharmacophore descriptors. The comparison of various regression methods, namely multiple linear regression (MLR), partial least squares regression (PLS), orthogonal partial least squares (OPLS), and support vector machine (SVM) were performed to develop a model with highest predictability. The obtained models are suitable for the prediction of drug affinity to human serum albumin using retention factor determined by MEKC and CATS descriptors, and only slightly differ in terms of coefficients of determination, Q2 value calculated using leave-one-out cross-validation technique and root-mean-squared error of cross-validation (RMSECV) as well as root-mean-square error in prediction (RMSEP) obtained by external validation.

Application of reversed-phase thin layer chromatography and QSRR modelling for prediction of protein binding of selected β-blockers

Chromatographic properties of sixteen β-blockers were studied using planar chromatography. The aim of presented study was to investigate influence of different organic solvents (acetonitrile, methanol, dioxin and tetrahydrofurane) on β-blockers’ retention on C18 bonded silica gel stationary phase. Group of sixteen, diverse in terms of structure, beta blockers was used as a model set. The main goal of this study was to compare chromatographically estimated lipophilicity parameters with values obtained with the use of computational methods. Furthermore, in order to understand molecular mechanisms of retention better, quantitative structure-retention relationships (QSRR) analysis was performed. The next step was focused on application of chromatographically obtained lipophilicity parameters for prediction of protein binding (PB), based on quantitative retention–activity relationships (QRAR) approach. The obtained results showed that reversed-phase thin layer chromatography (RP-TLC), especially with tetrafydrofurane used as an organic modifier of mobile phase, is a useful tool for lipophilicity estimation, as well as for prediction of β-blockers’ biological properties. The QRAR model included C0 parameters for tetrahydrofuran-water as a mobile phase, as well as maximal projection area, and can be easily applied for prediction of systematically synthesized β-blockers structures’ PB.

Establishment of quantitative retention-activity model by optimized microemulsion liquid chromatography

The effective permeability coefficient is of theoretical and practical importance in evaluation of the bioavailability of drug candidates. However, most methods currently used to measure this coefficient are expensive and time-consuming. In this paper, we addressed these problems by proposing a new measurement method which is based on the microemulsion liquid chromatography. First, the parallel artificial membrane permeability assays model was used to determine the effective permeability of drug so that quantitative retention-activity relationships could be established, which were used to optimize the microemulsion liquid chromatography. The most effective microemulsion system used a mobile phase of 6.0% (w/w) Brij35, 6.6% (w/w) butanol, 0.8% (w/w) octanol, and 86.6% (w/w) phosphate buffer (pH 7.4). Next, support vector machine and back-propagation neural networks are employed to develop a quantitative retention-activity relationships model associated with the optimal microemulsion system, and used to improve the prediction ability. Finally, an adequate correlation between experimental value and predicted value is computed to verify the performance of the optimal model. The results indicate that the microemulsion liquid chromatography can serve as a possible alternative to the PAMPA method for determination of high-throughput permeability and simulation of biological processes.

Fast profiling ecotoxicity and skin permeability of benzophenone ultraviolet filters using biopartitioning micellar chromatography based on penetrable silica spheres

Penetrable silica possesses hierarchical pores, mesopores and penetrable macropores, offering fast mass transfer, satisfactory mechanical strength as well as low column pressure. In the present study, penetrable octadecyl-bonded silica (ODS) was for the first time used as biopartitioning micellar chromatography (BMC) stationary phase to profile ecotoxicity and skin permeability of benzophenone UV-filters. Mobile phase (MP) pH and concentration of polyoxyethylene(23)lauryl ether in the MP were systematically studied. Quantitative retention–activity relationships (QRARs) model was established to correlate retention factors (k) on BMC with bioconcentration factor (BCF) and transdermal rate (TR) of UV-filters. Coefficient of determination (r2) of the QRARs model between log BCF and logk were 0.9398–0.9753, while r2 between TR and logk were 0.7569–0.8434, which demonstrated satisfactory predictive ability of the methodology. It was a powerful tool for fast screening by combining penetrable ODS with BMC, and avoiding column blockage often occurring in BMC.

Development of predictive quantitative retention–activity relationship models of alkaloids by mixed micellar liquid chromatography

The mixed micellar liquid chromatography is a mode that uses mixed micellar system of Brij35/SDS (85 : 15) as a mobile phase under adequate experimental conditions, can simulate the resting membrane potential and the conformation of the long hydrophilic polyoxyethylene chains remains unchanged. In this article, the applications of biopartitioning micellar chromatography, using mixed micellar system to describe and estimate bioactivities of alkaloids, has been focused. The BMC(Brij35/SDS)-QRAR models of half-life time, volume of distribution, plasma clearance and area under concentration-time curve were obtained using Brij35-SDS retention data. The aim is to take a look at the capability of the mixed micellar liquid chromatography model to describe and/or estimate the bioactivity of alkaloids.

Quantitative Retention‐Activity Relationship Studies by Liposome Electrokinetic Chromatography to Predict Skin Permeability

AbstractLiposome electrokinetic chromatography (LEKC) provides a simple and facile approach for drug membrane interactions using liposome as a pseudostationary phase. This study evaluated the potential of LEKC for high‐throughput skin permeability profiled as an in vitro technique. A quantitative retention‐activity relationship (QRAR) model for the estimation of skin permeability was proposed. For the 16 structurally diverse chemicals, lg k correlated well with permeability values (R2=0.886). The predictive ability of the model was evaluated by cross‐validation. The result was compared to traditional quantitative structure‐activity relationship, QSAR, models using some molecular descriptors and physicochemical parameters. Interestingly, a single LEKC retention parameter was capable of describing the skin permeability, while three variables in QSAR were needed to achieve a similar correlation (R2=0.704). The QRAR models developed in this paper may be a useful method to screening new chemicals and in the early stage of development and selection of chemicals.

The QRAR model study of β-lactam antibiotics by capillary coated with cell membrane

With the accelerating development of new drugs, there is a great need for rapid and simple screening technologies. In this paper, a new in vitro method, capillary coated with cell membrane, was presented for drug screening based on the real biomembrane–drugs interaction, in which the cell membrane was applied to chromatography as pseudo-stationary phase directly. As the cell membrane was coated on the bare-fused capillary via sol–gel technology in our present work, it will be shown to be superior to other pseudo-stationary phases mimicking biological environment. Meanwhile, the quantitative retention–activity relationships (QRAR) model of β-lactam antibiotics was studied through investigating the effect of the membrane coating amount and pH of running buffer on the retention behaviors of the drugs and the logarithm of octanol–water partition coefficient (log P) at pH 7.4 and pH 6.5 were also obtained for comparison. The results showed that the capillary coated with cell membrane could suit the study of QRAR model.

Biopartitioning micellar chromatography separation methods: modelling quantitative retention–activity relationships of cephalosporins

In this article, recent applications of chromatographic systems, particularly biopartitioning micellar chromatography (BMC) systems based on amphiphilic structures, have been reported. The aim is to take a look at the capability of quantitative retention-activity relationship (QRAR) models with BMC to describe and/or estimate the bioactivity of cephalosporins. Better qualification of BMC systems was obtained according to the octanol-water partition coefficient (log P); the bioactivity parameters (Lag-T, T(1/2beta), F%, T(1/a), P%, AUC and C(max)) were correlated with the retention factors of cephalosporins processed by Alltech-chromstation software, and the classical data were compared with the predictive values based on QRAR models. The results indicate that using only one descriptor (the retention factor, k) to explain the pharmacokinetic and pharmacodynamic properties of cephalosporins is adequate, and this in vitro approach is an advanced tool for pharmacodynamics research.

Quantitative retention–activity relationship models for quinolones using biopartitioning micellar chromatography

A simple and reproducible quantitative retention-activity relationship (QRAR) model utilizing biopartitioning micellar chromatography was developed for the biological parameter estimation of drugs. The correlation between retention factors of quinolones obtained in physiological conditions (pH, ionic strength) and biological activities was investigated using different second-order polynomial models. The predictive and interpretative ability of the chromatographic models was evaluated in terms of cross-validated data (RMSEC, RMSECV and RMSECVi). The aim was to obtain adequate QRAR models of half-life, clearance, volume of distribution, plasma protein combination rate, area under concentration-time curve and toxicity (LD50) of quinolones, and to elucidate the advantages and limitations of using a single parameter as independent variable for describing and estimating the activities.

Development of predictive quantitative retention-activity relationship models of HMG-CoA reductase inhibitors by biopartitioning micellar chromatography

Biological fluid cell membranes are barriers for the uptake of many kinds of drugs and their metabolites, along with passive transport across membranes and bioaccumulation. Biopartitioning micellar chromatography (BMC) is a mode of micellar liquid chromatography that uses micellar mobile phases of Brij35 under adequate experimental conditions and can be useful to simulate the drug's passive absorption and the transport in biological systems. The use of micellar aqueous solutions of Brij35 as mobile phases in reversed-phase liquid chromatography has proven to be valid to predict the biological activities of barbiturates, benzodiazepines, catecholamines, local anesthetics, non-steriodal anti-inflammatory drugs and tricyclic antidepressants. In this study, the relationships between the capacity factor in BMC and some pharmacokinetic and pharmacodynamic parameters of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors are studied. Predictive quantitative retention-activity relationship (QRAR) models describing some of the biological activities and pharmacokinetic properties of HMG-CoA reductase inhibitors are obtained. The results indicate that QRAR model may be a useful tool during the drug discovery process.

Biopartitioning micellar chromatography to predict skin permeability

Dermal absorption of chemicals is an area of increasing interest to the pharmaceutical and cosmetic industries, as well as in dermal exposure and risk assessment processes. In this paper the capability of biopartitioning micellar chromatography (BMC) as an in vitro technique to describe compound percutaneous absorption is evaluated. A multivariate study (principal component analysis, partial least squares) is performed in order to evaluate the importance of some physicochemical variables on the skin permeability constant values. From these results, a quantitative retention-activity relationship model for predicting the skin permeability constants that uses the BMC retention data and melting point as descriptor variables was obtained from a heterogeneous set of 43 compounds. The main advantage of the proposed methodology is that it allows the obtention of permeability constants of ionic compound and it can be very useful to predict the effect of pH of vehicle on the skin permeability of xenobiotics.

Development of predictive retention–activity relationship models of non-steroidal anti-inflammatory drugs by micellar liquid chromatography: comparison with immobilized artificial membrane columns

The predictive and interpretative capability of quantitative chromatographic retention–biological activity models is supported by the fact that under adequate experimental conditions the solute partitioning into chromatographic system can emulate the solute partitioning into lipid bilayers of biological membranes, which is the basis for drug and metabolite uptake, passive transport across membranes and bioaccumulation. The use of micellar solutions of Brij35 as mobile phases in reversed-phase liquid chromatography has proven to be valid to predict some biological activities of different kinds of drugs. In this study, quantitative retention–activity relationship (QRAR) models to describe some of the biological activities and pharmacokinetic properties of non-steroidal anti-inflammatory drugs (NSAIDs) with predictive and interpretative ability are obtained. These models are compared with those obtained using immobilized artificial membrane (IAM) column data taken from the literature. For NSAIDs, the statistical characteristics of the micellar liquid chromatography (MLC) QRAR models were better than or at least comparable to those of the IAM-QRAR models.