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This paper presents a simple, highly efficient method for analyzing single-walled carbon nanotube (SWNT) bundles based on (1) ultrasound-assisted solubilization/dispersion of SWNTs in the ionic liquid 1-butyl-3-methylimidazolium tetrafluoroborate, (2) encapsulation of the nanotubes in sodium dodecyl sulfate micelles, and (3) analysis by capillary electrophoresis. The process by which SWNTs disperse in the ionic liquid was studied by Raman spectroscopy. No degradation of SWNTs was observed under mild sonication conditions. The shape and position changes observed in the Raman spectral bands for the nanotubes are ascribed to debundling and interaction with the ionic liquid. Separation of solubilized SWNTs was accomplished by using a 50 mM formic acid solution at pH 2.0 as background electrolyte and a potential of -10 kV. Under these conditions, separation was completed within only 4 min. Eighteen peaks for SWNTs were identified in the analysis of commercial SWNT bundles. The two types of bundles studied exhibited distinct, highly characteristic electrophoretic profiles which could be used to control SWNTs purity.

The analysis of the conformational properties of the C-glycosyl analogue of the core trisaccharide alpha-D-Man-(1 --> 3)-[alpha-D-Man-(1 --> 6)]-D-Man in solution is presented by using a combination of NMR spectroscopy and timeaverage restrained molecular dynamics. It is found that both the alpha-1, 3-and the alpha-1, 6-glycosidic linkages show a major conformational averaging.

The binding of the nonsteroidal antiinflammatory drugs, flurbiprophen and ibuprophen, to hydroxypropyl-beta-cyclodextrin (HPBCD) were thermodynamically and structurally analyzed through pH potentiometric measurements, molecular mechanics and dynamics computations. The nonionic forms were found to have a higher affinity to HPBCD than their ionic counterparts. The complexes formed by the flurbiprophen species and HPBCD are enthalpy-driven, with a favorable enthalpic term and an unfavorable entropic term.

In this work, we have studied the interactions betweenthe water-soluble p-sulfonatocalix[6]arene and cationicsurfactants octyltrimethylammoniumbromide below the cmc and dodecyltrimethylammonium bromide above thecmc, by saturation transfer difference (STD) NMR spectroscopy. Fromthe STD build-up curves, we have obtained the T1 independent crossrelaxation rates, and the results show that the interactions establishedbetween the cationic headgroup of the surfactant and the OMe groupof the macrocycle play an important role in the stabilization of thecomplex, both below and above the cmc. [ABSTRACT FROM AUTHOR]

Provides information on a study which analyzed the binding of the flurbiprophen and ibuprophen nonsteroidal, antiinflammatory drugs, to hydroxypropyl-beta-cyclodextrin. Discussion on the therapeutic action of drugs; Measurement of the drugs' pH aqueous solutions; Methodology used to conduct the study; Results of the study.

The conformational properties of the C-glycosyl analogue of the core trisaccharide α-D-Man-(1 → 3)-[α-D-Man-(1 → 6)]-D-Man in solution have been carefully analyzed by a combination of NMR spectroscopy and time-averaged restrained molecular dynamics. It has been found that both the α-1,3and the α-1,6-glycosidic linkages show a major conformational averaging. Unusual φ ca. 60° orientations for both φ torsion angles are found. Moreover, a major conformational distinction between the natural compound and the glycomimetic affects to the behavior of the ω[sub 16] torsion angle around the α-1 → 6-linkage. Despite this increased flexibility, the C-glycosyl analogue is recognized by three mannose binding lectins, as shown by NMR (line broadening, TR-NOE, and STD) and surface plasmon resonance (SPR) methods. Moreover, a process of conformational selection takes place, so that these lectins probably bind the glycomimetic similarly to the way they recognize the natural analogue. Depending upon the architecture and extension of the binding site of the lectin, loss or gain of binding affinity with respect to the natural analogue is found. [ABSTRACT FROM AUTHOR]

Drug development involves the thorough assessment of the candidate's safety and efficacy. In silico toxicology (IST) methods can contribute to the assessment, complementing in vitro and in vivo experimental methods, since they have many advantages in terms of cost and time. Also, they are less demanding concerning the requirements of product and experimental animals. One of these methods, Quantitative Structure-Activity Relationships (QSAR), has been proven successful in predicting simple toxicity end points but has more difficulties in predicting end points involving more complex phenomena. We hypothesize that QSAR models can produce better predictions of these end points by combining multiple QSAR models describing simpler biological phenomena and incorporating pharmacokinetic (PK) information, using quantitative in vitro to in vivo extrapolation (QIVIVE) models. In this study, we applied our methodology to the prediction of cholestasis and compared it with direct QSAR models. Our results show a clear increase in sensitivity. The predictive quality of the models was further assessed to mimic realistic conditions where the query compounds show low similarity with the training series. Again, our methodology shows clear advantages over direct QSAR models in these situations. We conclude that the proposed methodology could improve existing methodologies and could be suitable for being applied to other toxicity end points.

Oxidative stress is the consequence of an abnormal increase of reactive oxygen species (ROS). ROS are generated mainly during the metabolism in both normal and pathological conditions as well as from exposure to xenobiotics. Xenobiotics can, on the one hand, disrupt molecular machinery involved in redox processes and, on the other hand, reduce the effectiveness of the antioxidant activity. Such dysregulation may lead to oxidative damage when combined with oxidative stress overpassing the cell capacity to detoxify ROS. In this work, a green fluorescent protein (GFP)-tagged nuclear factor erythroid 2-related factor 2 (NRF2)-regulated sulfiredoxin reporter (Srxn1-GFP) was used to measure the antioxidant response of HepG2 cells to a large series of drug and drug-like compounds (2230 compounds). These compounds were then classified as positive or negative depending on cellular response and distributed among different modeling groups to establish structure-activity relationship (SAR) models. A selection of models was used to prospectively predict oxidative stress induced by a new set of compounds subsequently experimentally tested to validate the model predictions. Altogether, this exercise exemplifies the different challenges of developing SAR models of a phenotypic cellular readout, model combination, chemical space selection, and results interpretation.

We report an unexpected rearrangement of 3-hydroxyoxindoles into benzoxazinones using electrochemistry. Our reaction employs mild and environmentally friendly conditions, and the benzoxazinone products are obtained in moderate to excellent yields. Mechanistic experiments suggest that a peroxide intermediate is likely involved.

Herein, we present a general electrochemical method to access unsymmetrical 3,3-disubstituted oxindoles by direct C-H functionalization where the oxindole fragment behaves as an electrophile. This Umpolung approach does not rely on stoichiometric oxidants and proceeds under mild, environmentally benign conditions. Importantly, it enables the functionalization of these scaffolds through C-O, and by extension to C-C or even C-N bond formation.

The observation of signals in solution NMR requires nuclei with sufficiently large transverse relaxation times ( T 2 ). Otherwise, broad signals embedded in the baseline afford an invisible fraction of nuclei (IF). Based on the STD (saturation transfer difference) sequence, IF-STD is presented as a quick tool to unveil IF in the 1 H NMR spectra of polymers. The saturation of a polymer in a region of the NMR spectrum with IF (very short 1 H T 2 ) results in an efficient propagation of the magnetization by spin diffusion through the network of protons to a visible-invisible interphase with larger 1 H T 2 (STD on ). Subtracting this spectrum from one recorded without saturation (STD off ) produces a difference spectrum (STD off-on ), with the nuclei at the visible-invisible interphase, that confirms the presence of an IF. Analysis of a wide collection of polymers by IF-STD reveals IF more common than previously thought, with relevant IF figures when STD > 0.4% at 750 MHz. A fundamental property of the IF-STD experiment is that the signal is generated within a single state comprising polymer domains with different dynamics, as opposed to several states in exchange with different degrees of aggregation. Contrary to a reductionist visible-invisible dichotomy, our results confirm a continuous distribution of nuclei with diverse dynamics. Since nuclei observed (edited) by IF-STD at the visible-invisible interphase are in close spatial proximity to the IF (tunable with the saturation time), they emerge as a privileged platform from which gaining an insight into the IF itself.

Rational design and development of a nanosystem usually relies on empirical approaches as well as a fair degree of serendipity. Understanding how nanosystems behave at the molecular level is of great importance for potential biomedical applications. In this work, we describe a nanosystem composed of two natural compounds, vitamin E and sphingomyelin, prepared by spontaneous emulsification (vitamin E-sphingomyelin nanosystems (VSNs)). Extensive characterization revealed suitable physicochemical properties, very high biocompatibility in vitro and in vivo , and colloidal stability during storage and in biological media, all relevant properties for clinical translation. We have additionally pursued a computational approach to gain an improved understanding of the assembling, structure, dynamics, and drug-loading capacity of VSNs, using both small molecules and biomolecules (resveratrol, curcumin, gemcitabine, and two peptides). The spontaneous formation of compartmentalized VSNs starting from completely disassembled molecules, observed here for the first time, was accurately assessed from the computational molecular dynamics trajectories. We describe here a synergistic in silico / in vitro approach showing the predictive power of computational simulations for VSNs' structural characterization and description of internal interaction mechanisms responsible for the association of bioactive molecules, representing a paradigm shift in the rational design of nanotechnologies as drug delivery systems for advanced personalized medicine.

This study describes the efficiency of a new coating material for preparing granulated potassium-fertilizers with a potassium release to the soil solution sensitive to rainfall intensity. The composite is prepared by reaction of an alkyd-resin with cement in the absence of water. The complementary use of diverse analytical techniques showed that the presence of the cement fraction induced alkyd resin reticulation and gradual cement-resin hardening. Scanning electron microscopy revealed the formation of micro and nanopores within cement-clusters, whose water permeability is affected by the resin reticulation and amphiphilic character. Potassium release was evaluated in water, soil-columns, and in soil-plant trials in pots and open-field. Agronomic results were consistent with potassium release rates obtained in water solution and soil columns. The composite-coated potassium fertilizer was more efficient than the noncoated one in providing plant available potassium, with this effect being dependent on water presence in soil.

Drug-induced proarrhythmicity is a major concern for regulators and pharmaceutical companies. For novel drug candidates, the standard assessment involves the evaluation of the potassium hERG channels block and the in vivo prolongation of the QT interval. However, this method is known to be too restrictive and to stop the development of potentially valuable therapeutic drugs. The aim of this work is to create an in silico tool for early detection of drug-induced proarrhythmic risk. The system is based on simulations of how different compounds affect the action potential duration (APD) of isolated endocardial, midmyocardial, and epicardial cells as well as the QT prolongation in a virtual tissue. Multiple channel-drug interactions and state-of-the-art human ventricular action potential models ( O'Hara , T. , PLos Comput. Biol. 2011 , 7 , e1002061 ) were used in our simulations. Specifically, 206.766 cellular and 7072 tissue simulations were performed by blocking the slow and the fast components of the delayed rectifier current ( I Ks and I Kr , respectively) and the L-type calcium current ( I CaL ) at different levels. The performance of our system was validated by classifying the proarrhythmic risk of 84 compounds, 40 of which present torsadogenic properties. On the basis of these results, we propose the use of a new index (Tx) for discriminating torsadogenic compounds, defined as the ratio of the drug concentrations producing 10% prolongation of the cellular endocardial, midmyocardial, and epicardial APDs and the QT interval, over the maximum effective free therapeutic plasma concentration (EFTPC). Our results show that the Tx index outperforms standard methods for early identification of torsadogenic compounds. Indeed, for the analyzed compounds, the Tx tests accuracy was in the range of 87-88% compared with a 73% accuracy of the hERG IC 50 based test.

The aim of this work was to prepare polypseudorotaxane-based supramolecular gels combining αCD with two temperature-responsive copolymers of different architecture (i.e., linear poloxamer P and X-shaped poloxamine T), at the lowest concentration as possible to form syringeable depots, and to shed light on the self-diffusion and spatial closeness of all components (including water) which in turn may determine the cooperative self-assembly phenomena and the performance of the gels at the macroscopic level. The exchange rate between bound water and bulk water was measured with a novel NMR experiment Water Diffusion Exchange-Diffusion Optimized Spectroscopy (WDE-DOSY). Polypseudorotaxane formation caused opposite effects on the mobility of αCD species (decreased) and internal water (increased) but did not affect PPO-water interaction. Consequently, designed ternary P/T/αCD supramolecular gels exhibited in situ gelling at body temperature could host large amounts of PLA/PLGA microspheres and behaved as porous 3D-scaffolds for mesenchymal stem cells (MSCs) supporting their osteogenic differentiation. Interestingly, the gels withstood freeze-drying and reconstitution with minor changes in inner structure and rheological properties. The gathered information may help to understand better the supramolecular gels and provide tools for the rational design of syringeable bone scaffolds that can simultaneously accommodate cells and drug microcarriers for efficient tissue regeneration.

Fluorescence behavior of 8-anilino-1-naphthalenesulfonate (ANS) reflects a blue-shift and fluorescence enhancement on decreasing solvent polarity, with both properties affected in a synchronous way in solvent mixtures where ANS senses a homogeneous solvation shell. ANS complexation by cyclodextrins or bovine serum albumin (BSA) results in a nonhomogeneous solvation shell that is reflected by nonsynchronous variation of fluorescence properties. Steady-state fluorescence and saturation transfer difference NMR experiments allow us to conclude the formation of 1:1 and 2:1 host/guest complexes through the aniline or naphthalene moieties of ANS with cyclodextrins. This nonhomogeneous solvation shell has been ignored in studies using ANS to sense the microenvironment of proteins, micelles, bilayers, and other organized systems. ANS interaction with BSA reflects the existence of a large number of binding pockets in the surface of the protein that can be classified into two well-differentiated categories.

In very complex mixtures, classification by chemometric methods may be limited by the difficulties to extract from the NMR or gas chromatography/mass spectrometry (GC/MS) experimental data information useful for a reliable classification. The joint analysis of both data has showed its superiority in the biomedical field but is scarcely used in foodstuffs and never in wine in spite of the complexity of their spectra and classification. In this article we show that univariate and multivariate principal component analysis-discriminant analysis (PCA-DA) statistics applied to the combined (1)H NMR and solid-phase microextraction-gas chromatography (SPME-GC) data of a collection of 270 wines from Galicia (northwest Spain) allows a discrimination and classification not attainable from the separate data, distinguishing wines from autochthonous and nonautochthonous grapes, mono- from the plurivarietals, and identifying, in part, the geographical subzone of origin of the albariño wines. A general and automatable protocol, based on the signal integration of selected ROIs (regions of interest), is proposed that allows the fast and reliable identification of the grape in Galician wines.

The effects of four fungicides commonly used for the control of fungal diseases in vines and grapes in the course of winemaking were tested. The concentration of fungicide residues was monitored throughout the process to establish their kinetics of dissipation. In all cases the percentages of dissipation were >68%, which shows the detoxificant effect of the winemaking process. On the other hand, the effect of the fungicide residues on the aroma composition of Tempranillo red wines was tested. To evaluate possible modifications on the aroma profile of wines, seven odorant series (ripe fruits, fresh fruits, lactic, floral, spicy, vinous, and herbaceous) were built from the odor activity values (OAVs) obtained for each volatile compound. Ripe fruits and fresh fruits were the major aromatic attributes in all Tempranillo red wines. These two odorant series registered the highest variations in their total OAVs with respect to the control wine, especially with the application of boscalid + kresoxim-methyl into vines, leading to a decrease in the ripe fruit and fresh fruit nuances of the resulting wines. Moreover, when the effect of these fungicides on the aroma of Tempranillo red wines was compared throughout two years (2012 and 2013), wines elaborated from grapes treated in the field with boscalid + kresoxim-methyl in 2013 displayed the highest variation in aroma profile with respect to control wine.

The intrinsic ability of albumin to bind active substances in the physiological fluids has been explored to endow hydrogels with improved capability to regulate drug release. To develop such biomimetic-functional hydrogels, it is critical that albumin conformation is not altered and that the protein remains retained inside the hydrogel keeping its conformational freedom, i.e., it should be not chemically cross-linked. Thus, the hydrogels were prepared with various proportions of albumin by physical cross-linking of anionic polysaccharides (gellan gum and chondroitin sulfate) with the cationic endogen polyamine spermidine under mild conditions in order to prevent albumin denaturation. Texture and swelling properties of hydrogels with various compositions were recorded, and the effect of the preparation variables was evaluated applying neurofuzzy logic tools for hydrogels prepared with and without albumin and associating the antibiotic cloxacillin. Developed hydrogel systems were extensively analyzed by means of nuclear magnetic resonance (NMR) to determine weak-to-medium and strong binding modes and the equilibrium constants of the albumin-cloxacillin association. NMR techniques were also employed to demonstrate the successful modulation of the cloxacillin release from the albumin-containing hydrogels. In vitro microbiological tests carried out with Staphylococcus aureus and Staphylococcus epidermidis confirmed the interest of the albumin-containing hydrogels as efficient platforms for cloxacillin release in its bioactive form.

We report a novel method called ADAN (Applicability Domain ANalysis) for assessing the reliability of drug property predictions obtained by in silico methods. The assessment provided by ADAN is based on the comparison of the query compound with the training set, using six diverse similarity criteria. For every criterion, the query compound is considered out of range when the similarity value obtained is larger than the 95th percentile of the values obtained for the training set. The final outcome is a number in the range of 0-6 that expresses the number of unmet similarity criteria and allows classifying the query compound within seven reliability categories. Such categories can be further exploited to assign simpler reliability classes using a traffic light schema, to assign approximate confidence intervals or to mark the predictions as unreliable. The entire methodology has been validated simulating realistic conditions, where query compounds are structurally diverse from those in the training set. The validation exercise involved the construction of more than 1000 models. These models were built using a combination of training set, molecular descriptors, and modeling methods representative of the real predictive tasks performed in the eTOX project (a project whose objective is to predict in vivo toxicological end points in drug development). Validation results confirm the robustness of the proposed assessment methodology, which compares favorably with other classical methods based solely on the structural similarity of the compounds. ADAN characteristics make the method well-suited for estimate the quality of drug predictions obtained in extremely unfavorable conditions, like the prediction of drug toxicity end points.

A 1D NMR singlet filtered experiment (s-filter) is presented for the clean editing of singlets peaks in crowded ¹H NMR spectra. The experiment affords a clean editing of singlet peaks and weak coupled signals ((n)JHH < 3 Hz), while the remaining multiplets peaks are strongly attenuated to a factor over 90% of its original intensity. The experiment provided a useful simplification of the typically congested ¹H NMR spectra of foodstuffs, and the edited signals retained most of the sensitivity and quantitativity. The versatility of the s-filter scheme permitted its easy incorporation as excitation building block into other 1D and 2D experiments, providing a further editing of the singlet responses. The combination of the 1D s-filter experiment and difference spectroscopy provided a 1D reverse singlet filtered experiment (s-filter(rev)) for the clean editing of multiplet peaks and strong suppression of singlets. The experiments proposed could be valuable to facilitate the detection and/or quantification of target compounds in complex mixtures of metabolites.

NMR is a powerful tool to study the dynamics of dendrimers. By analogy to linear polymers, shorter T(1) relaxation times have been traditionally associated to less mobile nuclei and hence, dendrimers described with reduced local motions at either the core or the periphery. Herein we report a NMR relaxation study [(1)H and (13)C T(1), T(2); (13)C{(1)H}NOE; various fields and temperatures] which reveals profound differences between the relaxation behavior of dendrimers and linear polymers. Dendrimers show slower dynamics at internal layers and on increasing generation and may display internal nuclei in the slow motional regime with larger T(1) values than the periphery. In contrast to the relaxation properties of linear polymers, these T(1) increments should not be interpreted as resulting from faster dynamics. Only the recording of T(1) data at various temperatures (alternatively, T(2) or NOE at one temperature) ensures the correct interpretation of dendrimer dynamics.

The self-aggregation of five amphiphilic p-sulfonatocalix[n]arenes bearing alkyl chains at the lower rim was investigated by NMR spectroscopy and electrical conductivity. The critical micelle concentration was determined, and the tendency of this special class of surfactants to self-aggregate in aqueous solution was analyzed as a function of the alkyl chain length and the number of aromatic units in the macrocyclic ring. The structure of the surfactants in the monomeric and micellized states was elucidated by means of (1)H NMR and, in the case of the calix[6]arene derivative, with 2D NMR experiments. While all amphiphilic calix[4]arenes studied here are blocked in the cone conformation, in the monomeric state the calix[6]arene adopts a pseudo-1,2,3-alternate conformation and the calix[8]arene is conformationally mobile. These calixarenes undergo an aggregation-induced conformational change, adopting the cone conformation in the micelles. The structure and size of the aggregates were studied by diffusion ordered spectroscopy (DOSY) experiments, and the results indicate that these surfactants self-assemble into ellipsoidal micelles.

In cyanobacteria, ammonium is incorporated into carbon skeletons by the sequential action of glutamine synthetase and glutamate synthase (GOGAT). The activity of Synechocystis sp. PCC 6803 glutamine synthetase type I (GS) is controlled by a post-transcriptional process involving protein-protein interactions with two inactivating factors: the 65-residue-long protein (IF7) and the 149-residue-long one (IF17). The sequence of the C terminus of IF17 is similar to IF7; IF7 is an intrinsically disordered protein (IDP). In this work, we study the structural propensities and affinity for GS of IF17 and a chimera protein, IF17N/IF7 (constructed by fusing the first 82 residues of IF17 with the whole IF7) by fluorescence, CD, and NMR. IF17 and IF17N/IF7 are IDPs with residual non-hydrogen-bonded structure, probably formed by α-helical, turn-like, and PPII conformations; several theoretical predictions support these experimental findings. IF17 seems to fold upon binding to GS, as suggested by CD thermal denaturations and steady-state far-UV spectra. The apparent affinity of IF17 for GS, as measured by fluorescence, is slightly smaller (K(D) ~1 μM) than that measured for IF7 (~0.3 μM). The K(D)s determined by CD are similar to those measured by fluorescence, but slightly larger, suggesting possible conformational rearrangements in the IFs and/or GS upon binding. Further, the results with IFN17/IF7 suggest that (i) binding of IF17 to the GS is modulated not only by its C-terminal region but also by its N-terminus and (ii) there are weakly structured (that is, "fuzzy") complexes in the ternary GS-IF system.

The preclinical assessment of drug-induced ventricular arrhythmia, a major concern for regulators, is typically based on experimental or computational models focused on the potassium channel hERG (human ether-a-go-go-related gene, K(v)11.1). Even if the role of this ion channel in the ventricular repolarization is of critical importance, the complexity of the events involved make the cardiac safety assessment based only on hERG has a high risk of producing either false positive or negative results. We introduce a multiscale simulation system aiming to produce a better cardiotoxicity assessment. At the molecular scale, the proposed system uses a combination of docking simulations on two potassium channels, hERG and KCNQ1, plus three-dimensional quantitative structure-activity relationship modeling for predicting how the tested compound will block the potassium currents IK(r) and IK(s). The obtained results have been introduced in electrophysiological models of the cardiomyocytes and the ventricular tissue, allowing the direct prediction of the drug effects on electrocardiogram simulations. The usefulness of the whole method is illustrated by predicting the cardiotoxic effect of several compounds, including some examples in which classic hERG-based models produce false positive or negative results, yielding correct predictions for all of them. These results can be considered a proof of concept, suggesting that multiscale prediction systems can be suitable for being used for preliminary screening in lead discovery, before the compound is physically available, or in early preclinical development when they can be fed with experimentally obtained data.

(23)Na relaxation NMR measurements and self-diffusion coefficients for sodium cations and p-sulfonatocalix[n]arenes (SCn) were obtained to confirm that monovalent inorganic cations are complexed by SC4. In the absence of added salts and at neutral pH, the cavity of p-sulfonatocalix[4]arene (SC4) fully binds an Na(+) counterion. Our results provide evidence that when investigating the complexation of inorganic cations by SC4 a competitive binding scheme must be considered if more than one cation is present in solution. Moreover, it has been shown for the first time that SC6 and SC8 can also complex monovalent inorganic (sodium) cations.

The information provided by the alignment-independent GRid Independent Descriptors (GRIND) can be condensed by the application of principal component analysis, obtaining a small number of principal properties (GRIND-PP), which is more suitable for describing molecular similarity. The objective of the present study is to optimize diverse parameters involved in the obtention of the GRIND-PP and validate their suitability for applications, requiring a biologically relevant description of the molecular similarity. With this aim, GRIND-PP computed with a collection of diverse settings were used to carry out ligand-based virtual screening (LBVS) on standard conditions. The quality of the results obtained was remarkable and comparable with other LBVS methods, and their detailed statistical analysis allowed to identify the method settings more determinant for the quality of the results and their optimum. Remarkably, some of these optimum settings differ significantly from those used in previously published applications, revealing their unexplored potential. Their applicability in large compound database was also explored by comparing the equivalence of the results obtained using either computed or projected principal properties. In general, the results of the study confirm the suitability of the GRIND-PP for practical applications and provide useful hints about how they should be computed for obtaining optimum results.

The complex etiology of schizophrenia has prompted researchers to develop clozapine-related multitarget strategies to combat its symptoms. Here we describe a series of new 6-aminomethylbenzofuranones in an effort to find new chemical structures with balanced affinities for 5-HT2 and dopamine receptors. Through biological and computational studies of 5-HT2A and D2 receptors, we identified the receptor serine residues S3.36 and S5.46 as the molecular keys to explaining the differences in affinity and selectivity between these new compounds for this group of receptors. Specifically, the ability of these compounds to establish one or two H-bonds with these key residues appears to explain their difference in affinity. In addition, we describe compound 2 (QF1004B) as a tool to elucidate the role of 5-HT2C receptors in mediating antipsychotic effects and metabolic adverse events. The compound 16a (QF1018B) showed moderate to high affinities for D2 and 5-HT2A receptors, and a 5-HT2A/D2 ratio was predictive of an atypical antipsychotic profile.

Descriptors based on Molecular Interaction Fields (MIF) are highly suitable for drug discovery, but their size (thousands of variables) often limits their application in practice. Here we describe a simple and fast computational method that extracts from a MIF a handful of highly informative points (hot spots) which summarize the most relevant information. The method was specifically developed for drug discovery, is fast, and does not require human supervision, being suitable for its application on very large series of compounds. The quality of the results has been tested by running the method on the ligand structure of a large number of ligand-receptor complexes and then comparing the position of the selected hot spots with actual atoms of the receptor. As an additional test, the hot spots obtained with the novel method were used to obtain GRIND-like molecular descriptors which were compared with the original GRIND. In both cases the results show that the novel method is highly suitable for describing ligand-receptor interactions and compares favorably with other state-of-the-art methods.

The present study is part of a long-term research project aiming to gain insight into the mechanism of action of atypical antipsychotics. Here we describe a 3D-QSAR study carried out on a series of butyrophenones with affinity for the serotonin-2A receptor, aligned by docking into the binding site of a receptor model. The series studied has two peculiarities: (i) all the compounds have a chiral center and can be represented by two enantiomeric structures, and (ii) many of the structures can bind the receptor in two alternative orientations, posing the problem of how to select a single representative structure for every compound. We have used an original solution consisting of the simultaneous use of multiple structures, representing different configurations, binding conformations, and positions. The final model showed good statistical quality (n = 426, r2 = 0.84, q2LOO = 0.81) and its interpretation provided useful information, not obtainable from the simple inspection of the ligand-receptor complexes.

Water and methanol associations in ionic liquids (ILs) have been studied by means of FTIR spectroscopy. Spectra at different concentrations of water or methanol in ILs were obtained by means of on-line dilution using a flow injection analysis system. Spectral features in the OH stretching region revealed that most of the water and methanol molecules tended to be isolated from each other and to interact with the anion of the IL via H bonding. By means of two-dimensional correlation spectroscopy, the formation of methanol and water dimers was also detected. Multivariate curve resolution was used to recover pure spectra and concentration profiles of the different species. Methanol dimers form at concentrations higher than 0.8% (w/w) in the three studied ILs, 1-ethyl-3-methylimidazolium tetrafluoroborate (emimBF4), 1-butyl-3-methylimidazolium tetrafluoroborate (bmimBF4), and 1-butyl-3-methylimidazolium hexafluorophosphate (bmimPF6). Self-association of water molecules takes place in emimBF4 and bmimBF4 at a molar ratio similar to that of methanol molecules; however, water dimers cannot be detected in bmimPF6, the most hydrophobic IL studied. No evidence was found that bigger water clusters are formed in these ILs at the studied cosolvent concentrations.

The aim of this work is to present the anchor-GRIND methodology. Anchor-GRIND efficiently combines a priori chemical and biological knowledge about the studied compounds with alignment-independent molecular descriptors derived from molecular interaction fields. Such descriptors are particularly useful for series of ligands sharing a common scaffold but with very diverse substituents. The method uses a specific position of the molecular structure (the "anchor point") to compare the spatial distribution of the molecular interaction fields of the substituents. The descriptors produced are more detailed and specific than the original GRIND while still avoiding the bias introduced by the alignment. Three data sets have been studied to demonstrate the usefulness of the anchor-GRIND methodology for 3D-QSAR modeling. The two first data sets respectively include congeneric series of the hepatitis C virus NS3 protease and of the acetylcholinesterase inhibitors. The third data set discriminates between factor Xa inhibitors of high and low affinity. In all the series presented, the models obtained with the anchor-GRIND are statistically sound and easy to interpret.

The conformational flexibility of lactose in solution has been investigated by residual dipolar couplings (RDCs). One-bond carbon-proton and proton-proton coupling constants have been measured in two oriented media and interpreted in combination with molecular dynamics simulations (MD). Two different approaches, known as PALES (Zweckstetter et al., J. Am. Chem. Soc. 2000, 122, 3791-3792) and TRAMITE (Azurmendi et al., J. Am. Chem. Soc. 2002, 124, 2426-2427), have been used to determine the alignment tensor from a shape-induced alignment model with the oriented medium. The steric alignment of the structures from several MD trajectories has provided ensemble averaged RDCs that have been compared with the experimental ones. The obtained results reveal the almost exclusive presence of a major low energy region defined as syn-phi/syn-psi (> 97%), for which sampling occurs in a dynamic manner. This result satisfactorily agrees with that determined by standard NOE-based methods.

The main purpose of the present work was to apply NMR techniques to characterize the nanostructural organization of a new drug nanocarrier composed of tripalmitin, lecithin, and poly(ethylene glycol) (PEG)-stearate. These nanocarriers were prepared by an emulsification-solvent evaporation technique and were characterized for their composition and nanostructural architecture. The results showed that tripalmitin, present in the core of the nanoparticles, is the main component of these systems, whereas PEG-stearate is firmly attached to the surface of the nanoparticles, forming a hydrated polymeric layer. Furthermore, the results indicate that, by selecting appropriately the composition of the lipid mixtures used for nanoparticle preparation, it was possible to modulate the PEG-coating density. This rigorous characterization by NMR provided very useful information about the architectural organization of this new colloidal drug carrier and showed the potential of modern NMR techniques for the characterization of core-coated nanostructures intended for drug delivery.

The recently introduced GRid-INdependent Descriptors (GRIND) were designed to provide a suitable description of a series of ligands for 3D-QSAR studies not requiring the spatial superimposition of their structures. Despite the proven usefulness of the method, it was recognized that the original GRIND failed to describe appropriately the shape of the ligand molecules, which in some cases plays a major role in ligand-receptor binding. For this reason, the original descriptors have been enhanced with the addition of a molecular shape description based on the local curvature of the molecular surface. The integration of this description into the GRIND allows the generation of 3D-QSAR models able to identify both favorable and unfavorable shape complementarity in a simple and alignment-independent way. The usefulness of the new GRIND-shape description in 3D-QSAR is illustrated using two structure-activity studies: one performed on a set of xanthine-like antagonists of the A(1) adenosine receptor; another performed on a series of Plasmodium falciparum plasmepsin II inhibitors.

Molecular descriptors calculated by the VolSurf program have been extensively used to model pharmacokinetic properties, e.g., passive permeability through the gastrointestinal tract or through the blood-brain barrier. These descriptors quantify steric, hydrophobic, and hydrogen bond interactions between model compounds and different environments. Since these interactions are the same as those involved in the ligand-receptor binding, VolSurf descriptors could potentially be relevant in modeling this process as well. We obtained a significant model (r(2) = 0.85, q(2) = 0.75) using VolSurf descriptors derived from the ligand, the protein, and the ligand-protein complex for a diverse set of 38 structures previously used in the VALIDATE (ref 23) training set. Furthermore, a statistically significant model (r(2) = 0.94, q(2) = 0.89) was obtained using the same type of descriptors for a homogeneous set of glycogen phosphorylase inhibitors (ref 25). Using the VolSurf computational framework, both ligand-receptor binding and the ligand's pharmacokinetic behavior can be modeled simultaneously during the preclinical aspects of drug discovery.

A new type of sugar-amino acid hybrid, which is comprised of a sugar unit (gluco-, galacto-, or mannopyranose) linked through a C-glycosidic linkage to the beta-position of an alpha-unsubstituted beta-amino acid unit, is presented. It is hypothesized that these new compounds, or the oligomeric peptides derived therefrom, might possess the structural features of beta-amino acid oligomers and the chemical and enzymatic resistance of C-glycosides to hydrolysis. The synthetic strategy is based on a new Mannich-type reaction between a chiral acetate enolate equivalent and alpha-amido sulfones derived from the corresponding sugar-C-glycoside aldehydes. While the sugar-C-glycoside aldehyde partner is prepared from well-established transformations on known sugar precursors, the lithium enolate derived from (1R)-endo-2-acetylisoborneol 3 is employed as the key element. This Mannich approach proceeds with essentially perfect diasteromeric control leading to the new beta-amino carbonyl adducts in good yields. Further, cleavage of the camphor auxiliary is smoothly performed by oxidative treatment with ammonium cerium nitrate (CAN). Complementarily, direct peptide-type coupling of the beta-amino carbonyl Mannich adducts with an alpha- or beta-amino acid residue and subsequent CAN-promoted detachment of the auxiliary yields dipeptide fragments bearing a sugar-containing aliphatic side chain and is a process that can be iterated. A preliminary conformational study based on the combination of experimental NMR data and molecular mechanics and molecular dynamics (MD) of one particular adduct is also provided.

Database mining methods rely on the molecular descriptors used to characterize a structural database. In the present investigation, five different types of descriptors (log P, UNITY fingerprints, ISIS keys, VolSurf, and GRIND) are applied to characterize various databases (n = 1007, 100, and 229) comprising drugs almost exclusively. The validity of the descriptors is comparatively analyzed via principal component analysis and its hierarchical variant, consensus principal component analysis. Both pharmacodynamic and pharmacokinetic aspects of database mining are treated. For pharmacodynamic aspects, clustering behavior achieved with the different descriptors is tested on the chemically homogeneous beta-blockers, benzodiazepines, and penicillins and on the chemically more diverse class I antiarrhythmics. The following ranking is observed: UNITY fingerprints > ISIS keys and GRIND > VolSurf > log P. Regarding information content, the CPCA superweight plot indicates similarity between fingerprints and ISIS keys as well as between VolSurf and log P, while GRIND differs from all the remaining descriptors. Solubility data and blood/brain barrier penetrating behavior serve as test cases for pharmacokinetic aspects. Comparison of the descriptors applied to these data reveals that VolSurf has the most realistic and consistent behavior, GRIND shows intermediate behavior, while UNITY fingerprints and ISIS keys are not well suited for pharmacokinetic profiling. From this comparative analysis, we conclude that VolSurf descriptors exhibit particular advantages in treating pharmacokinetic aspects; UNITY fingerprints, ISIS keys, and GRIND descriptors are of special value for tackling pharmacodynamic aspects of database mining. The parameter log P is of limited applicability in database mining because of rather poor reliability and lack of completeness of data.

Cocaine is one of the most widely abused drugs in the industrial world. Substantial evidence has accumulated that the dopamine transporter (DAT) is a key target for cocaine regarding its reinforcing effects. This work describes the application of chemometric methods to a data set of 54 N(1)-benzhydryl-oxy-alkyl-N(4)-phenyl-alk(en)yl-piperazines (GBR compounds) and chemically related mepyramines as putative candidates in cocaine abuse therapy. The aim of the study is to gain insight into the structural requirements that determine the affinity of the data set molecules to the DAT and the serotonin transporter (SERT) as well as their inhibitory potency on dopamine uptake. The compounds in the dataset are described using the recently developed GRID independent descriptors (GRIND), which allow one to obtain fast three-dimensional quantitative structure-activity relationship models without the need of aligning and superimposing the structures; the results are interpreted in a convenient pharmacophoric-like fashion. In the first part of the work, the selectivity of the database molecules for DAT binding vs dopamine reuptake inhibition is investigated. In the second part, the selectivity of the compounds for DAT binding vs SERT binding is studied. In both cases, significant models are obtained, which define the structural features responsible for the respective selectivity profiles. Moreover, the information has potential interest for the design of new derivatives with improved selectivity.

Traditional methods for performing 3D-QSAR rely upon an alignment step that is often time-consuming and can introduce user bias, the resultant model being dependent upon and sensitive to the alignment used. There are several methods which overcome this problem, but in general the necessary transformations prevent a simple interpretation of the resultant models in the original descriptor space (i.e. 3D molecular coordinates). Here we present a novel class of molecular descriptors which we have termed GRid-INdependent Descriptors (GRIND). They are derived in such a way as to be highly relevant for describing biological properties of compounds while being alignment-independent, chemically interpretable, and easy to compute. GRIND are obtained starting from a set of molecular interaction fields, computed by the program GRID or by other programs. The procedure for computing the descriptors involves a first step, in which the fields are simplified, and a second step, in which the results are encoded into alignment-independent variables using a particular type of autocorrelation transform. The molecular descriptors so obtained can be used to obtain graphical diagrams called "correlograms" and can be used in different chemometric analyses, such as principal component analysis or partial least-squares. An important feature of GRIND is that, with the use of appropriate software, the original descriptors (molecular interaction fields) can be regenerated from the autocorrelation transform and, thus, the results of the analysis represented graphically, together with the original molecular structures, in 3D plots. In this respect, the article introduces the program ALMOND, a software package developed in our group for the computation, analysis, and interpretation of GRIND. The use of the methodology is illustrated using some examples from the field of 3D-QSAR. Highly predictive and interpretable models are obtained showing the promising potential of the novel descriptors in drug design.

We present a computational procedure aimed at understanding enzyme selectivity and guiding the design of drugs with respect to selectivity. It starts from a set of 3D structures of the target proteins characterized by the program GRID. In the multivariate description proposed, the variables are organized and scaled in a different way than previously published methodologies. Then, consensus principal component analysis (CPCA) is used to analyze the GRID descriptors, allowing the straightforward identification of possible modifications in the ligand to improve its selectivity toward a chosen target. As an important new feature the computational method is able to work with more than two target proteins and with several 3D structures for each protein. Additionally, the use of a 'cutout tool' allows to focus on the important regions around the active site. The method is validated for a total number of nine structures of the three homologous serine proteases thrombin, trypsin, and factor Xa. The regions identified by the method as being important for selectivity are in excellent agreement with available experimental data and inhibitor structure-activity relationships.

1H-(13)C one-bond dipolar coupling values were measured for natural abundance samples of the human milk oligosaccharides "lacto-N-fucopentaose" (LNF-1 LNF-2, and LNF-3), "lacto-N-difucohexaose" (LND-1), "lacto-N-tetraose" (LNT), and "lacto-N-neo-tetraose" (LNnT), four of which have Lewis blood group epitopes. Each oligosaccharide was dissolved in a 7.5% solution of 1, 2-dimyristoyl-sn-glycero-3-phosphocholine/1, 2-dihexanoyl-sn-glycero-3-phosphocholine (DMPC/DHPC) bicelle liquid crystals oriented in the NMR magnetic field. The dipolar coupling data and NOE were fitted to conformational models with calculations of an optimum orientation tensor which best represents the dipolar coupling values for a fragment hypothesized to adopt a single conformation. In the case of LNF-1, LNF-2, LNF-3, and LND-1, the models confirm previous conformational models for the Lewis epitopes based on NOE and molecular dynamics simulations. Extensions of the model provided new structural data for the remaining residues. In all cases, upper limits for the errors in the glycosidic angles of the models were estimated. Since residual dipolar coupling provides information on long-range order, it is a valuable complement to other types of NMR data such as NOE and scalar coupling for exploring conformations of complex oligosaccharides.

For complex oligosaccharides, which are relatively rigid with modest excursions from a single minimum energy conformation, it is straightforward to build conformational models from NOE data. Other oligosaccharides are more flexible with transitions between distinct minima separated by substantial energy barriers. We show that modeling based on scalar coupling data is superior to NOE-based modeling for the latter case. Long range 13C-13C and 13C-1H coupling constants measured for the heptasaccharide repeating subunit of the cell wall polysaccharide from Streptococcus mitis J22 are correlated with individual glycosidic dihedral angles, effectively uncoupling the degrees of freedom of the oligosaccharide and allowing a search for combinations of dihedral angles which are energetically reasonable, i.e., with no bad van der Waals contacts, and which can be combined to satisfy all the measured J values. Allowed values of the individual angles can then be combined to search for overall oligosaccharide conformations which contribute to the ensemble. We show that while the polysaccharide from S. mitis J22 is flexible, requiring multiple conformations, most of the flexibility is localized to a few bonds and only a rather small number of conformations is required to reproduce the experimental NOE and scalar coupling data.

A comparative binding energy (COMBINE) analysis (Ortiz et al. J. Med. Chem. 1995, 38, 2681-2691) has been performed on a training set of 33 HIV-1 protease inhibitors, and the resulting regression models have been validated using an additional external set of 16 inhibitors. This data set was originally reported by Holloway et al. (J. Med. Chem. 1995, 38, 305-317), who showed the usefulness of molecular mechanics interaction energies for predicting the activity of novel HIV-1 protease inhibitors within the framework of the MM2X force field and linear regression techniques. We first used the AMBER force field on the same set of three-dimensional structures to check up on any possible force-field dependencies. In agreement with the previous findings, the calculated raw ligand-receptor interaction energies were highly correlated with the inhibitory activities (r2 = 0.81), and the linear regression model relating both magnitudes had an acceptable predictive ability both in internal validation tests (q2 = 0.79, SDEPcv = 0.61) and when applied to the external set of 16 different inhibitors (SDEPex = 1.08). When the interaction energies were further analyzed using the COMBINE formalism, the resulting PLS model showed improved fitting properties (r2 = 0.89) and provided better estimations for the activity of the compounds in the external data set (SDEPex = 0.83). Computation of the electrostatic part of the ligand-receptor interactions by numerically solving the Poisson-Boltzmann equation did not improve the quality of the linear regression model. On the contrary, incorporation of the solvent-screened residue-based electrostatic interactions and two additional descriptors representing the electrostatic energy contributions to the partial desolvation of both the ligands and the receptor resulted in a COMBINE model that achieved a remarkable predictive ability, as assessed by both internal (q2 = 0.73, SDEPcv = 0.69) and external validation tests (SDEPex = 0.59). Finally, when all the inhibitors studied were merged into a single expanded set, a new model was obtained that explained 91% of the variance in biological activity (r2 = 0.91), with very high predictive ability (q2 = 0.81, SDEPcv = 0.66). In addition, the COMBINE analysis provided valuable information about the relative importance of the contributions to the activity of individual residues that can be fruitfully used to design better inhibitors. All in all, COMBINE analysis is validated as a powerful methodology for predicting binding affinities and pharmacological activities of congeneric ligands that bind to a common receptor.

Water present in a ligand binding site of a protein has been recognized to play a major role in ligand-protein interactions. To date, rational drug design techniques do not usually incorporate the effect of these water molecules into the design strategy. This work represents a new strategy for including water molecules into a three-dimensional quantitative structure-activity relationship analysis using a set of glucose analogue inhibitors of glycogen phosphorylase (GP). In this series, the structures of the ligand-enzyme complexes have been solved by X-ray crystallography, and the positions of the ligands and the water molecules at the ligand binding site are known. For the structure-activity analysis, some water molecules adjacent to the ligands were included into an assembly which encompasses both the inhibitor and the water involved in the ligand-enzyme interaction. The mobility of some water molecules at the ligand binding site of GP gives rise to differences in the ligand-water assembly which have been accounted for using a simulation study involving force-field energy calculations. The assembly of ligand plus water was used in a GRID/GOLPE analysis, and the models obtained compare favorably with equivalent models when water was excluded. Both models were analyzed in detail and compared with the crystallographic structures of the ligand-enzyme complexes in order to evaluate their ability to reproduce the experimental observations. The results demonstrate that incorporation of water molecules into the analysis improves the predictive ability of the models and makes them easier to interpret. The information obtained from interpretation of the models is in good agreement with the conclusions derived from the structural analysis of the complexes and offers valuable insights into new characteristics of the ligands which may be exploited for the design of more potent inhibitors.