Drug impurity profiling strategies

A general scheme is set up for the estimation of the impurity profile of bulk drug substances by the complex use of chromatographic, spectroscopic and hyphenated techniques. Several examples are presented as illustrations to the scheme from the authors' laboratory involving the use of chromatographic methods such as thin-layer-(TLC), gas-(GC), analytical and preparative high-performance liquid chromatography (HPLC), spectroscopic methods such as mass spectrometry (MS) and NMR spectroscopy as well as hyphenated techniques (HPLC/diode-array UV, GC/MS and HPLC/MS). In addition to summarizing earlier work, new examples are also presented: identification of an impurity (propyl 4-[diethylcarbamoyl(methoxy)]-3-methoxy phenylglyoxylate, II) in propanidid (I) and two unsaturated impurities in allylstrenol (VII) by GC/MS and HPLC/diode-array UV as well as estimation of the impurity profile of mazipredone (III) by HPLC/MS and HPLC/diode-array UV.     

Drug profiling using planar microelectrode arrays

Microelectrode arrays (MEAs) with evenly distributed multiple sensor spots have been designed for specific applications. Using the MEAs, we determined the relative profiles of potassium channel openers (KCOs) on cultured embryonic Sprague-Dawley rat cardiac myocytes. KCO, pinacidil (PIN), cromakalim (CROM), SDZ PCO400 (SDZ), or its vehicle, was added to the myocytes cumulatively. The action potential signal shapes in the presence of PIN and SDZ show that the changes in voltage over time and the magnitudes of the associated voltage change were reduced concentration-dependently. CROM affected sodium influx more than PIN and SDZ. The comparisons of changes in the rate of beating and propagation speed in the presence of KCOs were made using their corresponding pD(2) values (the negative log of EC(50)). All KCOs caused concentration-dependent reductions in the rate of beating and propagation speed, with SDZ being the most potent. In addition to the signal shapes, rate of beating, and propagation speed, the origin of excitation and the excitation pattern inside the culture can be also extracted. The results show that the present system can differentiate the effects of different KCOs on myocytes. It might be possible to utilise the MEA as a means to classify drug action based upon a combined interpretation of the three different datasets gained from the extracellular recordings. The combination of these observations might be used as 'drug signatures' when profiling drugs in the future.     

Ligand binding affinity prediction by linear interaction energy methods

A recent method for estimating ligand binding affinities is extended. This method employs averages of interaction potential energy terms from molecular dynamics simulations or other thermal conformational sampling techniques. Incorporation of systematic deviations from electrostatic linear response, derived from free energy perturbation studies, into the absolute binding free energy expression significantly enhances the accuracy of the approach. This type of method may be useful for computational prediction of ligand binding strengths, e.g., in drug design applications.     

Kernel-based data fusion improves the drug-protein interaction prediction

Proteins are involved in almost every action of every organism by interacting with other small molecules including drugs. Computationally predicting the drug-protein interactions is particularly important in speeding up the process of developing novel drugs. To borrow the information from existing drug-protein interactions, we need to define the similarity among proteins and the similarity among drugs. Usually these similarities are defined based on one single data source and many methods have been proposed. However, the availability of many genomic and chemogenomic data sources allows us to integrate these useful data sources to improve the predictions. Thus a great challenge is how to integrate these heterogeneous data sources. Here, we propose a kernel-based method to predict drug-protein interactions by integrating multiple types of data. Specially, we collect drug pharmacological and therapeutic effects, drug chemical structures, and protein genomic information to characterize the drug-target interactions, then integrate them by a kernel function within a support vector machine (SVM)-based predictor. With this data fusion technology, we establish the drug-protein interactions from a collections of data sources. Our new method is validated on four classes of drug target proteins, including enzymes, ion channels (ICs), G-protein couple receptors (GPCRs), and nuclear receptors (NRs). We find that every single data source is predictive and integration of different data sources allows the improvement of accuracy, i.e., data integration can uncover more experimentally observed drug-target interactions upon the same levels of false positive rate than single data source based methods. The functional annotation analysis indicates that our new predictions are worthy of future experimental validation. In conclusion, our new method can efficiently integrate diverse data sources, and will promote the further research in drug discovery.     

Molecule-ion interaction and its effect on coordination interaction

The present work revealed the presence of the molecule-ion interaction between ethylenediaminetetraacetic acid disodium salt (Na(2)H(2)EDTA) and β-cyclodextrin (CD) on the basis of observable changes in crystal patterns and thermal behaviors before and after interaction. Results from electric conductivity measurements confirmed this presence and showed that the extent of the molecule-ion interaction was associated with the concentration of β-CD. More importantly, the molecule-ion interaction led to a decreased coordination interaction of Na(2)H(2)EDTA and copper chloride, and this decrease exhibited a concentration dependence of β-CD. Similar phenomena were also observed in the case of several analogs of Na(2)H(2)EDTA by UV-vis spectroscopy. A possible explanation was proposed on the basis of the hypothesis that there was a competitive relationship between the molecule-ion interaction and the coordination interaction. Further, nuclear magnetic resonance measurements provided important information on the difference in interaction modes of β-CD with H(2)EDTA(2-) and [Cu(EDTA)](2-). We are of the opinion that the results would provide a significant bridge between coordination chemistry and supramolecular chemistry and help us further understand factors related to different interactions in multicomponent systems.     

Proteomic dissection of biological pathways/processes through profiling protein-protein interaction networks

Cellular functions, either under the normal or pathological conditions or under different stresses, are the results of the coordinated action of multiple proteins interacting in macromolecular complexes or assemblies. The precise determination of the specific composition of protein complexes, especially using scalable and high-throughput methods, represents a systematic approach toward revealing particular cellular biological functions. In this regard, the direct profiling protein-protein interactions (PPIs...     

Metabolite profiling of sucrose effect on the metabolism of Melissa officinalis by gas chromatography-mass spectrometry

The effect of sugar on plant metabolism, which is known to be similar to hormone-like signaling, was metabolomically studied using Melissa officinalis (lemon balm). The metabolite profiles of M. officinalis treated with sucrose were analyzed by gas chromatography-mass spectrometry (GC-MS) and principal component analysis (PCA). A total of 64 metabolites from various chemical classes including alcohols, amines, amino acids, fatty acids, inorganic acids, organic acids, phosphates, and sugars were identified by GC-MS. Three groups treated with different sucrose concentrations were clearly separated by PCA of their metabolite profiles, indicating changes in the levels of many metabolites depending on the sucrose concentration. Metabolite profiling revealed that treatment with a higher sucrose level caused an increase in the levels of metabolites such as sugars, sugar alcohols, and sugar phosphates, which are related to the glycolytic pathway of M. officinalis. Furthermore, proline and succinic acid, which are associated with the proline-linked pentose phosphate pathway, the shikimic acid pathway, and the biosynthesis of phenylpropanoids, also increased with increasing sucrose concentration. Therefore, these metabolic changes induced by sucrose ultimately led to the increased production of flavonoids such as caffeic acid via the biosynthetic pathway of phenylpropanoids. This study demonstrated that the abundance changes in some primary and secondary metabolites were somewhat interlocked with each other in response to sucrose.     

Characterization of interaction kinetics between chiral solutes and human serum albumin by using high-performance affinity chromatography and peak profiling

Peak profiling and high-performance columns containing immobilized human serum albumin (HSA) were used to study the interaction kinetics of chiral solutes with this protein. This approach was tested using the phenytoin metabolites 5-(3-hydroxyphenyl)-5-phenylhydantoin (m-HPPH) and 5-(4-hydroxyphenyl)-5-phenylhydantoin (p-HPPH) as model analytes. HSA columns provided some resolution of the enantiomers for each phenytoin metabolite, which made it possible to simultaneously conduct kinetic studies on each chiral form. The dissociation rate constants for these interactions were determined by using both the single flow rate and multiple flow rate peak profiling methods. Corrections for non-specific interactions with the support were also considered. The final estimates obtained at pH 7.4 and 37°C for the dissociation rate constants of these interactions were 8.2-9.6 s(-1) for the two enantiomers of m-HPPH and 3.2-4.1 s(-1) for the enantiomers of p-HPPH. These rate constants agreed with previous values that have been reported for other drugs and solutes that have similar affinities and binding regions on HSA. The approach used in this report was not limited to phenytoin metabolites or HSA but could be applied to a variety of other chiral solutes and proteins. This method could also be adopted for use in the rapid screening of drug-protein interactions.     

Glycoprotein profiling by electrospray mass spectrometry

This work compares several different methods of site-specific analysis of glycoproteins using electrospray mass spectrometry. The glycoprotein, oLHalpha (ovine luteinizing hormone, alpha-subunit) was chosen as an appropriate example protein for these studies because of its biological relevance and extreme microheterogeneity. More than 20 unique glycoforms were detected for this glycoprotein at the Asn(56) site of oLHalpha. The carbohydrates present at this site affect receptor binding affinity, so understanding the great variety in the composition of these carbohydrates is important in studying ligand binding interactions. MS data was acquired on a quadrupole ion trap, a triple quadrupole, and a quadrupole time of flight mass spectrometer, and carbohydrate composition at the Asn(56) site of oLHalpha was determined using these instruments. Additionally, neutral loss and precursor ion scanning modes were also used to identify the glycoforms present, and these techniques were compared to the standard MS data. Of the three instruments compared in the study, the qTOF mass spectrometer achieved the lowest sample consumption, but all three instruments were useful in profiling the glycopeptide composition.     

Hydrophilic interaction ultra performance liquid chromatography retention prediction under gradient elution

The development and application of new separation mechanisms such as hydrophilic interaction chromatography (HILIC) is of high importance for the simultaneous analysis of polar molecules such as primary metabolites. However the retention mechanism in HILIC is not fully understood and as a result retention prediction tools are not at hand for this chromatographic approach. In the present report we study the utility of a simple algorithm, based on a simple linear and/or a simple logarithmic retention model, for retention prediction in HILIC gradient separation of a mixture of 23 selected compounds including (poly)amines, amino acids, saccharides, and other molecules. Utilizing two types of gradient elution programs with or without an isocratic part, retention data were collected in order to build prediction models. Starting from at least three gradient runs the prediction of analyte retention was very satisfactory for all gradient programs tested, providing useful evidence of the value of such retention time prediction methodologies.     

Morphological evolution of aggregates induced by the hydrophobic effect and hydrogen bonding interaction

The aggregation behavior of poly(ethylene oxide)-block-poly(methylmethacrylate) (PEO-b-PMMA) in toluene without and with the addition of polar small-molecules has been characterized using transmission electron microscopy (TEM). The preparation method involved copolymer dissolution in toluene which is a selective solvent for polymethylmethacrylate at room temperature, followed by the addition of polar small-molecules. By increasing polarity of the small-molecules at the same copolymer concentrations, these aggregates were found to undergo morphological transformations from spherical aggregates to multiple morphologies, including bean-pod liked structures (the morphologies are biomimetic), spheres and vesicles. A possible mechanism for the formation of this aggregate is proposed.     

Theoretical prediction of S-H bond rupture in methanethiol upon interaction with gold

Organic thiols are known to react with gold surface to form self-assembled monolayers (SAMs), which can be used to produce materials with highly attractive properties. Although the structure of various SAMs is widely investigated, some aspects of their formation still represent a matter of debate. One of these aspects is the mechanism of S-H bond dissociation in thiols upon interaction with gold. This work presents a new suggestion for this mechanism on the basis of DFT study of methanethiol interaction with a single gold atom and a Au(20) cluster. The reaction path of dissociation is found to be qualitatively independent of the model employed. However, the highest activation barrier of S-H bond dissociation on the single gold atom (12.9 kcal/mol) is considerably lower than that on the Au(20) cluster (28.9 kcal/mol), which can be attributed to the higher extent of gold unsaturation. The energy barrier of S-H cleavage decreases by 4.6 kcal/mol in the presence of the second methanethiol molecule at the same adsorption site on the model gold atom. In the case of the Au(20) cluster we have observed the phenomenon of hydrogen transfer from one methanethiol molecule to another, which allows reducing the energy barrier of dissociation by 9.1 kcal/mol. This indicates the possibility of the "relay" hydrogen transfer to be the key step of the thiol adsorption observed for the SAMs systems.     

Protein profiling by protein imprinted polymer array

Six different protein-imprinted polymers using three template proteins with acidic or basic functional monomers resulted in unique fingerprints not only for the corresponding template but also for other proteins, allowing profiling of proteins for identification and classification.     

Depth profiling by ARXPS in surface analysis

A method of nondestructive depth profiling in near surface regions of solids is described. Models have been discussed from which algorithms for evaluation of measured data are obtained. The algorithms, based on standard profiles with free parameters, have been adjusted to the data resulting from angle resolved XPS (ARXPS) by means of least squares fits. Depth profile analyses and segregation studies were performed on Pt-Ni and Fe-S specimens.     

Impurity profiling of pharmaceuticals by thin-layer chromatography

Although there is a tendency in current pharmacopoeias for favouring HPLC, thin-layer chromatography (TLC) is still a very popular and frequently used analytical method in the pharmaceutical industry. This paper highlights the possibilities of this method in the different areas of pharmaceutical analysis like in-process and intermediate control, illustrated by impurity testing of active ingredients and final products, as well as its application in pharmaceutical research and development, based on some examples reported mainly in the last five years.     

Depth profiling by ARXPS in surface analysis

A method of nondestructive depth profiling in near surface regions of solids is described. Models have been discussed from which algorithms for evaluation of measured data are obtained. The algorithms, based on standard profiles with free parameters, have been adjusted to the data resulting from angle resolved XPS (ARXPS) by means of least squares fits. Depth profile analyses and segregation studies were performed on Pt–Ni and Fe–S specimens.     

Discovering disease-associated enzymes by proteome reactivity profiling

Proteomics aims to identify new markers and targets for the diagnosis and treatment of human disease. To realize this goal, methods and reagents are needed to profile proteins based on their functional properties, rather than mere abundance. Here, we describe a general strategy for synthesizing and evaluating structurally diverse libraries of activity-based proteomic probes. Quantitative screening of probe-proteome reactions coupled with bioinformatic analysis enabled the selection of a suite of probes that exhibit complementary protein reactivity profiles. This optimal probe set was applied to discover several enzyme activities differentially expressed in lean and obese (ob/ob) mice. Interestingly, one of these enzymes, hydroxypyruvate reductase, which was 6-fold upregulated in ob/ob livers, participates in the conversion of serine to glucose, suggesting that this unusual metabolic pathway may contribute to gluconeogenesis selectively in states of obesity.     

EDX depth profiling by means of effective layers

A new approach is described for depth profiling in stratified multilayer samples by recording energy dependent characteristic x-ray EDX(E ₀ ) curves in a scanning electron microscope. An effective layer technique replaces the x-ray excitation function of the heterogeneous target by an equivalent function of a homogeneous sample. First results of thickness determination are shown and compared to direct measurements of film thickness monitoring (FTM) and atomic force microscopy (AFM).