Retention of quinolones on human serum albumin and alpha1-acid glycoprotein HPLC columns: relationships with different scales of lipophilicity

QSRR modeling of the chromatographic retention behavior of some quinolone and sulfonamide antibacterial agents using firefly algorithm coupled to support vector machine

Quinolone and sulfonamide are two classes of antibacterial agents with an opulent history of medicinal chemistry features that contribute to their bacterial spectrum, efficacy, pharmacokinetics, and adverse effect profiles. The urgent need for their use, combined with the escalating rate of their resistance, necessitates the development of suitable analytical methods that accelerate and facilitate their analysis. In this study, the advanced firefly algorithm (FFA) coupled with support vector regression (SVR) was used to select the most significant descriptors and to construct two quantitative structure-retention relationship (QSRR) models using a series of 11 selected quinolone and 13 sulfonamide drugs, respectively, to predict their retention behavior in HPLC. Precisely, the effect of the pH value and acetonitrile composition in the mobile phase on the retention behavior of quinolones and sulfonamides, respectively, were studied. The obtained QSRR models performed well in both internal and external validations, demonstrating their robustness and predictive ability. Y-randomization validation demonstrated that the obtained models did not result by statistical chance. Moreover, the obtained results shed the light on the molecular features that influence the retention behavior of these two classes under the current chromatographic conditions.

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.

Binding Constants of Substituted Benzoic Acids with Bovine Serum Albumin

Experimental data on the affinity of various substances to albumin are essential for the development of empirical models to predict plasma binding of drug candidates. Binding of 24 substituted benzoic acid anions to bovine serum albumin was studied using spectrofluorimetric titration. The equilibrium constants of binding at 298 K were determined according to 1:1 complex formation model. The relationships between the ligand structure and albumin affinity are analyzed. The binding constant values for m- and p-monosubstituted acids show a good correlation with the Hammett constants of substituents. Two- and three-parameter quantitative structure–activity relationship (QSAR) models with theoretical molecular descriptors are able to satisfactorily describe the obtained values for the whole set of acids. It is shown that the electron-density distribution in the aromatic ring exerts crucial influence on the albumin affinity.

Scrutinizing the interactions between bisphenol analogues and plasma proteins: Insights from biomimetic liquid chromatography, molecular docking simulations and in silico predictions

The interactions between human serum albumin (HSA) and α₁- acid glycoprotein (AGP), the main plasma proteins binding drugs/xenobiotics, and some endocrine disrupting chemicals (EDCs), such as bisphenol A (BPA) and some of its structural analogues, bisphenol S (BPS), bisphenol F (BPF), bisphenol E (BPE), bisphenol B (BPB), bisphenol AF (BPAF), bisphenol A diglycidyl ether (BADGE) and bisphenol M (BPM), were characterized by biomimetic liquid chromatography (LC). The interactions between bisphenols (BPs) and either HSA or AGP protein was found to be non-specific and essentially lipophilicity-driven. To get more information on the binding of BPs and plasma proteins, in silico predictions and molecular docking simulations were exploited, and the results achieved in silico were compared to those observed in vitro. BPM was the one exhibiting the highest affinity on both plasma proteins according to these data. Our findings clarified the binding of these EDCs to plasma proteins and offered insights into the biodistribution and bioaccumulation processes underlying their toxicity.

HPLC-DAD Determination of Iodide in Mineral Waters on Phosphatidylcholine Column

Iodine is an essential nutrient necessary for the production of thyroid hormones. A valuable source of iodide, which is the bio-available iodine form could be mineral waters offered by different spas. In this work, the method capable of direct determination of iodide in mineral water samples based on IAM liquid chromatography on the phosphatidylcholine column (IAM.PC.DD2 Regis HPLC) with DAD detection without sample pretreatment or any pre-concentration steps is presented. The calibration graph for iodide was linear in the range of 0.5–10.0 mg L⁻¹ with a correlation coefficient of 0.9996. The limit of detection was 22.84 ng mL⁻¹. The relative recoveries were in the interval of 98.5–100.2% and the repeatability, expressed as a relative standard deviation (RSD) was less than 5%. The RSA (Response Surface Analysis) investigated the effect of the sample concentration and the injection volume. The iodide concentrations in the mineral water samples ranged from 0.58 to 2.88 mg L⁻¹. The accuracy of the method was assessed through independent analysis by ICP-MS. Iodide levels measured by these two procedures did not significantly differ. The effects of interfering ions like HCO₃⁻, Cl⁻, SO₄²⁻, F⁻, and Br⁻ were also tested. The analysis has shown insignificant differences in the values of the iodide peak area and its height measured in multicomponent mixtures with an error smaller than 5%.

Structural properties governing drug-plasma protein binding determined by high-performance liquid chromatography method

The high-performance liquid chromatography (HPLC) method employing stationary phases immobilized with plasma proteins was used for this study to investigate the structural properties governing drug-plasma protein binding. A set of 65 compounds with a broad range of structural diversity (in terms of volume, hydrogen-bonding, polarity and electrostatic force) were selected for this purpose. The Abraham linear free energy relationship (LFER) analyses of the retention factors on the immobilized HSA (human serum albumin) and AGP (α₁-acid glycoprotein) stationary phases showed that McGowan's characteristic molecular volume (V), dipolarity/polarizability (S) and hydrogen bond basicity (B) are the three significant molecular descriptors of solutes determining the interaction with immobilized plasma proteins, whereas excess molar refraction (E) is less important and hydrogen bond acidity (A) is not of statistical significance in both systems, for electrically neutral compounds. It was shown that ionised acids, as carboxylate anions, bind very strongly to the immobilized HSA stationary phase and that ionised bases, as cations bind strongly to the AGP stationary phase. This is the first time that the effect of ionised species on plasma protein binding has been determined quantitatively; the increased binding of acids to HSA is due almost entirely to acids in their ionised form.

In vitro, in silico and integrated strategies for the estimation of plasma protein binding. A review

Plasma protein binding (PPB) strongly affects drug distribution and pharmacokinetic behavior with consequences in overall pharmacological action. Extended plasma protein binding may be associated with drug safety issues and several adverse effects, like low clearance, low brain penetration, drug-drug interactions, loss of efficacy, while influencing the fate of enantiomers and diastereoisomers by stereoselective binding within the body. Therefore in holistic drug design approaches, where ADME(T) properties are considered in parallel with target affinity, considerable efforts are focused in early estimation of PPB mainly in regard to human serum albumin (HSA), which is the most abundant and most important plasma protein. The second critical serum protein α1-acid glycoprotein (AGP), although often underscored, plays also an important and complicated role in clinical therapy and thus the last years it has been studied thoroughly too. In the present review, after an overview of the principles of HSA and AGP binding as well as the structure topology of the proteins, the current trends and perspectives in the field of PPB predictions are presented and discussed considering both HSA and AGP binding. Since however for the latter protein systematic studies have started only the last years, the review focuses mainly to HSA. One part of the review highlights the challenge to develop rapid techniques for HSA and AGP binding simulation and their performance in assessment of PPB. The second part focuses on in silico approaches to predict HSA and AGP binding, analyzing and evaluating structure-based and ligand-based methods, as well as combination of both methods in the aim to exploit the different information and overcome the limitations of each individual approach. Ligand-based methods use the Quantitative Structure-Activity Relationships (QSAR) methodology to establish quantitate models for the prediction of binding constants from molecular descriptors, while they provide only indirect information on binding mechanism. Efforts for the establishment of global models, automated workflows and web-based platforms for PPB predictions are presented and discussed. Structure-based methods relying on the crystal structures of drug-protein complexes provide detailed information on the underlying mechanism but are usually restricted to specific compounds. They are useful to identify the specific binding site while they may be important in investigating drug-drug interactions, related to PPB. Moreover, chemometrics or structure-based modeling may be supported by experimental data a promising integrated alternative strategy for ADME(T) properties optimization. In the case of PPB the use of molecular modeling combined with bioanalytical techniques is frequently used for the investigation of AGP binding.

Biomembrane models and drug-biomembrane interaction studies: Involvement in drug design and development

Contact with many different biological membranes goes along the destiny of a drug after its systemic administration. From the circulating macrophage cells to the vessel endothelium, to more complex absorption barriers, the interaction of a biomolecule with these membranes largely affects its rate and time of biodistribution in the body and at the target sites. Therefore, investigating the phenomena occurring on the cell membranes, as well as their different interaction with drugs in the physiological or pathological conditions, is important to exploit the molecular basis of many diseases and to identify new potential therapeutic strategies. Of course, the complexity of the structure and functions of biological and cell membranes, has pushed researchers toward the proposition and validation of simpler two- and three-dimensional membrane models, whose utility and drawbacks will be discussed. This review also describes the analytical methods used to look at the interactions among bioactive compounds with biological membrane models, with a particular accent on the calorimetric techniques. These studies can be considered as a powerful tool for medicinal chemistry and pharmaceutical technology, in the steps of designing new drugs and optimizing the activity and safety profile of compounds already used in the therapy.

Enantioselective retention of beta-blocking agents on human serum albumin and alpha 1-acid glycoprotein HPLC columns: relationships with different scales of lipophilicity

The enantioselective retention of thirteen beta-blockers on HPLC stationary phases supporting human serum albumin (HSA) or alpha(1)-acid glycoprotein (AGP) was investigated. Eight beta-blockers were enantiomerically resolved on the AGP column whereas only four beta-blockers were resolved on the HSA column. Moreover, interactions between beta-blockers and AGP were much stronger than those with HSA. Retention values on both HSA and AGP for less retained enantiomers related well with various lipophilicity parameters, with the best relationships found with log k(w)(IAM) values obtained on HPLC stationary phases supporting phospholipids, i.e. the so-called Immobilized Artificial Membrane (IAM). Differently from n-octanol lipophilicity values, these values encode both lipophilic. Electrostatic intermolecular recognition forces which may be involved in the interaction between ionized analytes, such as beta-blockers, and proteins. However, their effectiveness to describe non-specific interactions with serum-proteins for other classes of drugs needs further investigations. Analyses performed on AGP with eluent containing dimethyloctylamine (DMOA) as the displacer demonstrated that enantioselective sites bind to both (-)-forms and (+)-forms, but the binding to (-)-forms is stronger. The enantiomer competition to bind to a same site may be relevant from a pharmacokinetic point of view when racemic mixtures are administered. Finally, in contrast to previously reported data in the literature, we found that AGP can bind enantioselectively not only the more lipophilic congeners but also the less lipophilic ones.

Characterization of drug-protein interactions in blood using high-performance affinity chromatography

The binding of drugs with proteins in blood, serum, or plasma is an important process in determining the activity, distribution, rate of excretion, and toxicity of drugs in the body. High-performance affinity chromatography (HPAC) has received a great deal of interest as a means for studying these interactions. This review examines the various techniques that have been used in HPAC to examine drug-protein binding and discusses the types of information that can be obtained through this approach. A comparison of these techniques with traditional methods for binding studies (e.g., equilibrium dialysis and ultrafiltration) will also be presented. The use of HPAC with specific serum proteins and binding agents will then be discussed, including HSA and alpha(1)-acid glycoprotein (AGP). Several examples from the literature are provided to illustrate the applications of such research. Recent developments in this field are also described, such as the use of improved immobilization techniques, new data analysis methods, techniques for working directly with complex biological samples, and work with immobilized lipoproteins. The relative advantages and limitations of the methods that are described will be considered and the possible use of these techniques in the high-throughput screening or characterization of drug-protein binding will be discussed.

Alternative measures of lipophilicity: from octanol-water partitioning to IAM retention

This review describes lipophilicity parameters currently used in drug design and QSAR studies. After a short historical overview, the complex nature of lipophilicity as the outcome of polar/nonpolar inter- and intramolecular interactions is analysed and considered as the background for the discussion of the different lipophilicity descriptors. The first part focuses on octanol-water partitioning of neutral and ionisable compounds, evaluates the efficiency of predictions and provides a short description of the experimental methods for the determination of distribution coefficients. A next part is dedicated to reversed-phase chromatographic techniques, HPLC and TLC in lipophilicity assessment. The two methods are evaluated for their efficiency to simulate octanol-water and the progress achieved in the refinement of suitable chromatographic conditions, in particular in the field of HPLC, is outlined. Liposomes as direct models of biological membranes are examined and phospolipophilicity is compared to the traditional lipophilicity concept. Difficulties associated with liposome-water partitioning are discussed. The last part focuses on Immobilised Artificial Membrane (IAM) chromatography as an alternative which combines membrane simulation with rapid measurements. IAM chromatographic retention is compared to octanol-water and liposome-water partitioning as well as to reversed-phase retention and its potential to predict biopartitioning and biological activities is discussed.

Comparison between immobilized artificial membrane (IAM) HPLC data and lipophilicity in n-octanol for quinolone antibacterial agents

The membrane phospholipid affinity of ten quinolone antibacterial agents, including both acidic and zwitterionic compounds, was measured by HPLC on two different immobilized artificial membrane (IAM) stationary phases, namely IAM.PC.MG and IAM.PC.DD2; it is expressed as the logarithm of the retention factor measured with (or extrapolated to) 100% aqueous eluent at pH 7.0, logk(w)(IAM). Quinolones are a class of highly potent, orally active, broad-spectrum antibacterial agents. For these compounds, lipophilicity values in n-octanol found in the literature, either calculated or measured, are not consistent with each other and are too low to be compatible with their pharmacokinetic properties. The logk(w)(IAM) values obtained in this study showed no relation with any of the lipophilicity values in the literature (clogP(a), clogP(b), MLP, logD(7.4)). In contrast, they were collinear with a new lipophilicity scale we had previously obtained by an original ion-pair reversed-phase HPLC method set up to estimate the lipophilicity of the neutral forms, logP(N). Moreover, when comparing the retention of quinolones on IAM to the retention of structurally unrelated neutral compounds, we observed that they interact with phospholipids with the same affinity as neutral isolipophilic compounds. The use of an eluent at pH 5.5, instead of pH 7.0, increased the retention on IAM not only for acidic, but also for zwitterionic congeners, indicating that phospholipid affinity is enhanced in the experimental conditions that depress the ionization of the acidic function, even when the ionization of the amino function increases simultaneously. To gain an insight into the mechanism of quinolones/serum-protein interactions, we investigated about possible relationships between quinolones affinity data for serum proteins and IAM data. Quinolone affinity for both HSA and AGP was already demonstrated poorly related to n-octanol lipophilicity values, probably due to the occurrence of electrostatic interactions. Only poor relationships were found between IAM and HSA affinity data, whereas quite good relationships were found with AGP affinity data. However, IAM.PC.DD2 data correlated better than those on IAM.PC.MG with quinolone affinity for both serum-proteins, mainly due to the fact that IAM.PC.MG phase is scarcely discriminative for the compounds with the highest retention values. The results suggest that IAM retention can produce a lipophilicity scale that, unlike solvent/water partition coefficients, is consistent with the pharmacokinetic behaviour of zwitterionic quinolones.