Capillary electrophoresis for the analysis of small-molecule pharmaceuticals

This paper reviews the application of CE to the analysis of small-molecule pharmaceuticals. The areas of pharmaceutical analysis covered are enantiomer separation, the analysis of small molecules such as amino acids or drug counter-ions, pharmaceutical assay, determination of related substances and physicochemical measurements such as log P and pK(a) of compounds. The different electrophoretic modes available and their advantages for pharmaceutical analysis are described. Recent applications of CE for each subject area are tabulated with electrolyte details.     

Computer-aided prediction of QT-prolongation

Drug-induced cardiac arrhythmia is acknowledged as a serious obstacle in successful development of new drugs. Several methods for in silico prediction of acquired long QT syndrome (LQTS) caused by the pharmacological blockade of human hERG K+ channels are discussed in literature. We propose to use the computer program PASS, which estimates the probabilities of about 3000 biological activities, not only for prediction of hERG blockade and QT-prolongation but also for the analysis of indirect mechanisms of these actions. After addition in the PASS training set of 163 compounds with data on QT-Prolongation and re-training, it was shown that accuracy of prediction was 87.1% and 81.8% for hERG blockade and QT-prolongation, respectively. Using computer program PharmaExpert we found that in the predicted biological activity spectra there was a certain correlation between the hERG blockade and some other molecular mechanisms of action. Possible role of 1-phosphatidylinositol-4-phospate 5-kinase, dimethylargininase and progesterone 11 alpha-monooxygenase inhibition in hERG blockade was discussed.     

Computer-aided prediction of QT-prolongation1

Drug-induced cardiac arrhythmia is acknowledged as a serious obstacle in successful development of new drugs. Several methods for in silico prediction of acquired long QT syndrome (LQTS) caused by the pharmacological blockade of human hERG K⁺ channels are discussed in literature. We propose to use the computer program PASS, which estimates the probabilities of about 3000 biological activities, not only for prediction of hERG blockade and QT-prolongation but also for the analysis of indirect mechanisms of these actions. After addition in the PASS training set of 163 compounds with data on QT-Prolongation and re-training, it was shown that accuracy of prediction was 87.1% and 81.8% for hERG blockade and QT-prolongation, respectively. Using computer program PharmaExpert we found that in the predicted biological activity spectra there was a certain correlation between the hERG blockade and some other molecular mechanisms of action. Possible role of 1-phosphatidylinositol-4-phospate 5-kinase, dimethylargininase and progesterone 11 alpha-monooxygenase inhibition in hERG blockade was discussed.     

Combined receptor and ligand-based approach to the universal pharmacophore model development for studies of drug blockade to the hERG1 pore domain

Long QT syndrome, LQTS, results in serious cardiovascular disorders, such as tachyarrhythmia and sudden cardiac death. A promiscuous binding of different drugs to the intracavitary binding site in the pore domain (PD) of human ether-a-go-go related gene (hERG) channels leads to a similar dysfunction, known as a drug-induced LQTS. Therefore, an assessment of the blocking ability for potent drugs is of great pragmatic value for molecular pharmacology and medicinal chemistry of hERGs. Thus, we attempted to create an in silico model aimed at blinded drug screening for their blocking ability to the hERG1 PD. Two distinct approaches to the drug blockage, ligand-based QSAR and receptor-based molecular docking methods, are combined for development of a universal pharmacophore model, which provides rapid assessment of drug blocking ability to the hERG1 channel. The best 3D-QSAR model (AAADR.7) from PHASE modeling was selected from a pool consisting of 44 initial candidates. The constructed model using 31 hERG blockers was validated with 9 test set compounds. The resulting model correctly predicted the pIC(50) values of test set compounds as true unknowns. To further evaluate the pharmacophore model, 14 hERG blockers with diverse hERG blocking potencies were selected from literature and they were used as additional external blind test sets. The resulting average deviation between in vitro and predicted pIC(50) values of external test set blockers is found as 0.29 suggesting that the model is able to accuretely predict the pIC(50) values as true unknowns. These pharmacophore models were merged with a previously developed atomistic receptor model for the hERG1 PD and exhibited a high consistency between ligand-based and receptor-based models. Therefore, the developed 3D-QSAR model provides a predictive tool for profiling candidate compounds before their synthesis. This model also indicated the key functional groups determining a high-affinity blockade of the hERG1 channel. To cross-validate consistency between the constructed hERG1 pore domain and the pharmacophore models, we performed docking studies using the homology model of hERG1. To understand how polar or nonpolar moieties of inhibitors stimulate channel inhibition, critical amino acid replacement (i.e., T623, S624, S649, Y652 and F656) at the hERG cavity was examined by in silico mutagenesis. The average docking score differences between wild type and mutated hERG channels was found to have the following order: F656A > Y652A > S624A > T623A > S649A. These results are in agreement with experimental data.     

Prediction of acidity in acetonitrile solution with COSMO-RS

The COSMO-RS method, a combination of the quantum chemical dielectric continuum solvation model COSMO with a statistical thermodynamics treatment for realistic solvation simulations, has been used for the prediction of pK(a) values in acetonitrile. For a variety of 93 organic acids, the directly calculated values of the free energies of dissociation in acetonitrile showed a very good correlation with the pK(a) values (r(2) = 0.97) in acetonitrile, corresponding to a standard deviation of 1.38 pK(a) units. Thus, we have a prediction method for acetonitrile pK(a) with the intercept and the slope as the only adjusted parameters. Furthermore, the pK(a) values of CH acids yielding large anions with delocalized charge can be predicted with a rmse of 1.12 pK(a) units using the theoretical values of slope and intercept resulting in truly ab initio pK(a) prediction. In contrast to our previous findings on aqueous acidity predictions the slope of the experimental pK(a) versus theoretical DeltaG(diss) was found to match the theoretical value 1/RT ln (10) very well. The predictivity of the presented method is general and is not restricted to certain compound classes. However, a systematic correction of -7.5 kcal mol(-1) is required for compounds that do not allow electron-delocalization in the dissociated anion. The prediction model was tested on a diverse test set of 129 complex multifunctional compounds from various sources, reaching a root mean square deviation of 2.10 pK(a) units.     

Accurate prediction of basicity in aqueous solution with COSMO-RS

The COSMO-RS method, a combination of the quantum chemical dielectric continuum solvation model COSMO with a statistical thermodynamics treatment for realistic solvation simulations, has been used for the prediction of base pK(a) constants. For a variety of 43 organic bases the directly calculated values of the free energies of dissociation in water showed a very good correlation with experimental base pK(a) values (r2 = 0.98), corresponding to a standard deviation of 0.56 pK(a) units. Thus, we have an a priori prediction method for base pK(a) with the regression constant and the slope as only adjusted parameters. In accord with recent findings for pK(a) acidity predictions, the slope of pK(a) vs. DeltaG(diss) was significantly smaller than the theoretically expected value of 1/RTln(10). The predictivity of the presented method is general and not restricted to certain compound classes, but systematic corrections of 1 and 2 pKa units for secondary and tertiary aliphatic amines are required, respectively. The pK(a) prediction method was validated on a set of 58 complex multifunctional drug-like compounds, yielding an RMS accuracy of 0.66 pK(a) units.     

Determination of the intrinsic site pK(a) value and cooperativity of the symmetrical hexadentate chelator N,N',N'-tris[2-(3-hydroxy-2-oxo-1,2-dihydropyridin-1-yl)acetamido]ethylamine

The three overlapping pK(a) values of N,N',N'-tris[2-(3-hydroxy-2-oxo-1,2-dihydropyridin-1-yl)acetamido]ethylamine, a tripodal hexadentate chelator formed from three 3-hydroxy-2(1H)-pyridinone moieties amide linked to tris-(2-aminoethyl)amine, were determined by simultaneous spectrophotometric and potentiometric titration. The data was analysed by non-linear regression with constraints to deal with (a) the highly correlated absorptivities and (b) the highly correlated pK(a) values. The three pK(a) values were optimized first from the spectrophotometric data (absorbance vs. pH) by non-linear regression to a model in which the molar absorptivity of the ith species ((i)) was constrained by the correlation equation (i) = epsilon (0) + (epsilon (3) - epsilon (0))i 3 with i = 0, 1, 2, 3, where (3) and (0) represent the molar absorptivities of the most protonated and least protonated species, respectively. The molar absorbitivity of the four species defined by three pK(a) values is, therefore, linearly related to proton stoichiometry. The pK(a) values were then optimized from the potentiometric data (pH vs. titrant volume) by non-linear regression to a model in which the three pK(a) values were constrained by the correlation equation pK(a(i)) = pK(a(int)) + b(i - 1) + (i - 2)log(3) where i = 1, 2 or 3. This expresses the three pK(a) values in terms of only two optimizable parameters, the intrinsic site pK(a) (pK(a(int))) and the interaction energy between sites (b). The fixed term (i - 2)log(3) accounts for the statistical effect on the pK(a) values of three equivalent ionizable sites. The modified analytical derivatives required for optimization of these parameters by the Gauss-Newton-Marquardt algorithm and the merits of optimizing pK(a) values with these two correlation equations are discussed. The optimized pK(a) values were 9.31 +/- 0.01, 8.75 +/- 0.01 and 8.19 +/- 0.01. The separation between pK(a) values is 0.58 comprising 0.477 for the statistical effect and 0.081 for the interaction energy while the intrinsic site pK(a) is 8.672 +/- 0.005. The tertiary amine at the centre of the tripodal backbone has a pK(a) of 5.88 +/- 0.03.     

Application of a polarity parameter model to the separation of fat-soluble vitamins by reversed-phase HPLC

The retention behavior of a series of fat-soluble vitamins has been established on the basis of a polarity retention model: log k = (log k)(0) + p (P(m) (N) - P(s) (N)), with p being the polarity of the solute, P(m) (N) the mobile phase polarity, and (log k)(0) and P(m) (N) two parameters for the characterization of the stationary phase. To estimate the p-values of solutes, two approaches have been considered. The first one is based on the application of a QSPR model, derived from the molecular structure of solutes and their log P(o/w), while in the second one, the p-values are obtained from several experimental measurements. The quality of prediction of both approaches has also been evaluated, with the second one giving more accurate results for the most lipophilic vitamins. This model allows establishing the best conditions to separate and determine simultaneously some fat-soluble vitamins in dairy foods.     

In silico predictions of hERG channel blockers in drug discovery: from ligand-based and target-based approaches to systems chemical biology

The risk for cardiotoxic side effects represents a major problem in clinical studies of drug candidates and regulatory agencies have explicitly recommended that all new drug candidates should be tested for blockage of the human Ether-a-go-go Related-Gene (hERG) potassium channel. Indeed, several drugs with different therapeutic indications and recognized as hERG blockers were recently withdrawn due to the risk of QT prolongation, arrhythmia and Torsade de Pointes. In silico techniques can provide a priori knowledge of hERG blockers, thus reducing the costs associated with screening assays. Significant progress has been made in structure-based and ligand-based drug design and a number of models have been developed to predict hERG blockage. Although approaches such as homology modeling in combination with docking and molecular dynamics bring us closer to understand the drug-channel interactions whereas QSAR and classification models provide a faster assessment and detection of hERG-related drug toxicity, limitation on the applicability domain of the current models and integration of data from diverse in vitro approaches are still issues to challenge. Therefore, this review will emphasize on current methods to predict hERG blockers and the need of consistent data to improve the quality and performance of the in silico models. Finally, integration of network-based analysis on drugs inducing potentially long-QT syndrome and arrhythmia will be discussed as a new perspective for a better understanding of the drug responses in systems chemical biology.     

IDSite: An accurate approach to predict P450-mediated drug metabolism

Accurate prediction of drug metabolism is crucial for drug design. Since a large majority of drugs metabolism involves P450 enzymes, we herein describe a computational approach, IDSite, to predict P450-mediated drug metabolism. To model induced-fit effects, IDSite samples the conformational space with flexible docking in Glide followed by two refinement stages using the Protein Local Optimization Program (PLOP). Sites of metabolism (SOMs) are predicted according to a physical-based score that evaluates the potential of atoms to react with the catalytic iron center. As a preliminary test, we present in this paper the prediction of hydroxylation and O-dealkylation sites mediated by CYP2D6 using two different models: a physical-based simulation model, and a modification of this model in which a small number of parameters are fit to a training set. Without fitting any parameters to experimental data, the Physical IDSite scoring recovers 83% of the experimental observations for 56 compounds with a very low false positive rate. With only 4 fitted parameters, the Fitted IDSite was trained with the subset of 36 compounds and successfully applied to the other 20 compounds, recovering 94% of the experimental observations with high sensitivity and specificity for both sets.     

Protonation studies of modified adenine and adenine nucleotides by theoretical calculations and (15)N NMR

The acid/base character of nucleobases affects phenomena such as self-association, interaction with metal ions, molecular recognition by proteins, and nucleic acid base-pairing. Therefore, the investigation of proton-transfer equilibria of natural and synthetic nucleos(t)ides is of great importance to obtain a deeper understanding of these phenomena. For this purpose, a set of ATP prototypes was investigated using (15)N NMR spectroscopy, and the corresponding adenine bases were investigated by theoretical calculations. (15)N NMR measurements provided not only acidity constants but also information on the protonation site(s) on the adenine ring and regarding the ratio of the singly protonated species in equilibrium. Substituents of different nature and position on the adenine ring did not change the preferred protonation site, which remained N1. However, for 2-thioether-ATP derivatives a mixed population of N1 and N7 singly protonated species was observed. Reduction of basicity of 0.4-1 pK(a) units relative to ATP was also observed for all evaluated ATP derivatives, except for 2-Cl-ATP, for which K(a) was ca. 10,000-fold lower. To explain the substitution-dependent variations in the experimental pK(a) values of the ATP analogues, gas-phase proton affinities (PA), Delta Delta G(hyd), and pK(a) values of the corresponding adenine bases were calculated using quantum mechanical methods. The computed PA and Delta Delta G(hyd) values successfully explained the experimental pK(a) values. A computational procedure for the prediction of accurate pK(a) values was developed using density functional theory and polarizable continuum model calculations. In this procedure, we developed a set of parameters for the polarizable continuum model that was fitted to reproduce experimental pK(a) values of nitrogen heterocycles. This method is proposed for the prediction of pK(a) values and protonation site(s) of purine analogues that have not been synthesized or analyzed.     

Quantitative structure-activity relationship of catechol derivatives inhibiting 5-lipoxygenase.

Various catechol derivatives (beta-substituted 3,4-dihydroxystyrenes, 1-substituted 3,4-dihydroxybenzenes, and 6-substituted 2,3-dihydroxynaphthalenes) were synthesized and their inhibition of 5-lipoxygenase was assayed. Their structure-activity relationships were examined quantitatively with substituent and structural parameters and regression analysis. The variations in the inhibitory activity were explained in bilinear hydrophobic parameter (log P) terms, and steric (molecular thickness) and electronic (proton nuclear magnetic resonance (1H-NMR) chemical shift of the proton adjacent to the catechol group) parameter terms. The hydrophobicity of the inhibitor molecule was important, and the optimum value of logP was about 4.3-4.6, beyond which inhibition did not increase further. A lower electron density of the aromatic ring containing the catechol group and the greater thickness of the lipophilic side chains were unfavorable to the activity. The results added a physicochemical basis for the selection of candidate compounds for developmental studies.