Synthesis, the complete 1H- and 13C-NMR assignments, and the long-range C,H coupling constants (nJC,H) of some hydrogen-deficient carbazolequinones, assessed by a J-HMBC experiment, are reported. In these molecules, the protons, used as entry points for assignments, are separated by several bonds with non-protonated atom carbons. Therefore, the use of long-range NMR experiments for the assignment of the spectra is mandatory; we used HSQC and HMBC. On the other hand, the measured heteronuclear (C,H) coupling constants 2J to 5J) allow us to choose the value of the long-range delay used in the HMBC experiment less arbitrarily in order to visualize a desired correlation in the spectrum. The chemical shifts and the coupling constant values can be used as input for assignments in related chemical structures.

A systematic study to include 3 JHH couplings into DP4 formalism ( J-DP4) led to the development of three alternative strategies. The d J-DP4 (direct) approach involves a new DP4-like equation including an additional probability term given by 3 JHH. The i J-DP4 (indirect) approach explores the original DP4 method with a restricted conformational search. Despite both strategies performing better than DP4, their combined use (i J/d J-DP4) provided the best results, with a 2.5-fold performance improvement at similar or lower computational cost.

E-selectin is an endothelial protein that participates in the adhesion of metastatic cancer cells, and is therefore a relevant target for antitumor therapeutic intervention. In this work, virtual screening was used to identify new E-selectin inhibitors from a subset of drug-like molecules retrieved from the ZINC database, including the physiological ligand sLe(x) as reference structure (PDB ID: 1G1T). Four hits were chosen and subjected to molecular dynamics simulations and fluorescence binding assays, which led to the determination of experimental dissociation constants between 333 and 1012 μm. The candidate with the highest affinity was studied by saturation transfer difference (STD) NMR experiments and complete relaxation and conformational exchange matrix analysis of saturation transfer (CORCEMA-ST), aimed at identifying the preferable binding mode with E-selectin. Our results revealed that this new inhibitor binds more strongly than sLe(x) in the E-selectin binding site, in good agreement with simulation predictions. These properties will prove valuable for the future design of drugs that target E-selectin.

The chemical study of the red alga Laurencia viridis has led to the isolation of four new polyether triterpenoids: 28-hydroxysaiyacenol B (2), saiyacenol C (3), 15,16-epoxythyrsiferol A (4), and 15,16-epoxythyrsiferol B (5). The structures of 2 and 3 were established mainly by NMR data analysis and comparison with the well-known metabolite dehydrothyrsiferol (1). However, due to the existence of a nonprotonated carbon within the epoxide functionality, stereochemical assignments in 4 and 5 required an in-depth structural study that included NOESY data, J-based configuration analysis, comparison with synthetic models, and DFT calculations. The biological activities of the new metabolites and other related oxasqualenoids were evaluated for the first time against a panel of relevant biofouling marine organisms, and structure-activity conclusions were obtained.

The cyclization of peptide side chains has been traditionally used to either induce or stabilize secondary structures (β-strands, helices, reverse turns) in short peptide sequences. So far, classic peptide coupling, nucleophilic substitution, olefin metathesis, and click reactions have been the methods of choice to fold synthetic peptides by means of macrocyclization. This article describes the utilization of the Ugi reaction for the side chain-to-side chain and side chain-to-termini macrocyclization of peptides, thus enabling not only access to stable folded structures but also the incorporation of exocyclic functionalities as N-substituents. Analysis of the NMR-derived structures revealed the formation of helical turns, β-bulges, and α-turns in cyclic peptides cross-linked at i, i + 3 and i, i + 4 positions, proving the folding effect of the multicomponent Ugi macrocyclization. Molecular dynamics simulation provided further insights on the stability and molecular motion of the side chain cross-linked peptides.

Fully atomistic molecular dynamics (MD) simulations and NMR spectroscopy were employed to get insights about the molecular details of drug-dendrimer supramolecular association phenomena, using piroxicam (PRX) and the third generation poly(amido amine) (PAMAM-G3) dendrimer as model systems. Theoretical results concerning the complex stoichiometry suggest that PRX forms drug-dendrimer complexes of the type 24:1 at pH 7.0. This result was validated with the experimental quantities obtained from aqueous solubility profiles, which led to an empiric stoichiometry of 23:1 for the PRX:PAMAM-G3 system. The predicted binding mode between PRX and PAMAM-G3 accounts for the preferred encapsulation of the drug inside dendrimer cavities, which is mainly driven by van der Waals and hydrogen bonding interactions, and to a lesser extent, for the external association of the guest through electrostatic contacts with the positively charged amino groups of PAMAM periphery. The binding mode obtained from MD simulations was confirmed with 2D-NOESY experiments, which evidence the preferred internal complexation of PRX with PAMAM-G3. The predominance of internal encapsulation over external contacts in the PRX:PAMAM-G3 system differs from the general behaviour expected for acidic anionic guests, for which external electrostatic interactions with the positively charged PAMAM surface have been postulated as the most relevant factor for drug association.

The complexation of mefenamic acid (MA) with poly(amido amine) dendrimers of the second and third generation (PAMAM‐G2 and PAMAM‐G3) at pH 7.0 is studied by aqueous solubility experiments, DOSY and 2D‐NOESY spectroscopy, and fully atomistic molecular dynamics (MD) simulations. Solubility profiles account for the formation of MA:PAMAM complexes of the type 10:1 and 15:1, for PAMAM‐G2 and PAMAM‐G3, respectively, with a maximum solubilization enhancement of 14.6 mol of MA per mol dendrimer. Diffusion ordered sepectroscopy (DOSY) and nuclear Overhauser effect spectroscopy (NOESY) experiments suggest that MA association occurs through both external electrostatic interactions with the PAMAM surface and internal encapsulation into the deep dendrimer cavities. MD simulations are consistent with these experimental findings and show that the internal drug encapsulation is enhanced as the dendrimer generation increases. The involvement of internal and external interactions in the complexation of MA with low‐generation PAMAM dendrimers differs from the general behavior expected for acidic anionic guests, for which external electrostatic contacts with the positively charged PAMAM surface have been postulated as the most relevant factor for drug association. image

Constraining small peptides into specific secondary structures has been a major challenge in peptide ligand design. So far, the major solution for decreasing the conformational flexibility in small peptides has been cyclization. An alternative is the use of topological templates, which are able to induce and/or stabilize peptide secondary structures by means of covalent attachment to the peptide. Herein a multicomponent strategy and structural analysis of a new type of peptidosteroid architecture having the steroid as N-substituent of an internal amide bond is reported. The approach comprises the one-pot conjugation of two peptide chains (or amino acid derivatives) to aminosteroids by means of the Ugi reaction to give a unique family of N-steroidal peptides. The conjugation efficiency of a variety of peptide sequences and steroidal amines, as well as their consecutive head-to-tail cyclization to produce chimeric cyclopeptide-steroid conjugates, that is, macrocyclic lipopeptides, was assessed. Determination of the three-dimensional structure of an acyclic N-steroidal peptide in solution proved that the bulky, rigid steroidal template is capable of both increasing significantly the conformational rigidity, even in a peptide sequence as short as five amino acid residues, and inducing a β-turn secondary structure even in the all-s-trans isomer. This report provides the first evidence of the steroid skeleton as β-turn inducer in linear peptide sequences.

New glycolipids that feature a carbohydrate/triazole/lipid hybrid architecture were readily produced by a combined multicomponent/click approach. The process comprises the use of the Ugi four-component reaction to construct double-lipidic scaffolds that have either alkyne or azide functionalities followed by conjugation to mono- and trisaccharides through a Cu-I-catalyzed 1,3-dipolar cycloaddition (click) process. The high chemical efficiency and feasibility of the over-all procedure provides new opportunities for the rapid creation and biological screening of libraries of this unique class of Ugi/click glycolipids. Dynamic NMR experiments were performed to evaluate the free energy of activation related to the isomerization of the cis/trans amide bond in these compounds. This is the first time that such multicomponent and cycloaddition processes have been combined for the synthesis of glycolipids.

Marine organisms are an increasingly important source of novel metabolites, some of which have already inspired or become new drugs. In addition, many of these molecules show a high degree of novelty from a structural and/or pharmacological point of view. Structure determination is generally achieved by the use of a variety of spectroscopic methods, among which NMR (nuclear magnetic resonance) plays a major role and determination of the stereochemical relationships within every new molecule is generally the most challenging part in structural determination. In this communication, we have chosen okadaic acid as a model compound to perform a computational chemistry study to predict 1H and 13C NMR chemical shifts. The effect of two different solvents and conformation on the ability of DFT (density functional theory) calculations to predict the correct stereoisomer has been studied.

The Growth Hormone Releasing Hexapeptide, GHRP‐6 was the first of a family of synthetic peptides that enhance the release of the Growth Hormone by the pituitary gland in a dose‐dependent manner. Since its discovery, it has been used as a benchmark and starting point in numerous researches aiming to obtain new drugs. Complete resonance assignment of GHRP‐6 NMR spectra in both open and cyclic forms are reported, showing some differences to random coil chemical shifts. Connectivities observed in the ROESY spectra indicate spatial proximity between the aromatic residues side‐chains in both molecules, as well as between residues DPhe5 and Lys6 sidechains. An ensemble of 10 structures was generated for each one of the molecules, showing RMSD values indicative of nonrandom structures. Molecular Dynamics simulations, both with and without explicit solvent, were carried out for GHRP‐6 and its cyclic analogue. Conformational analysis performed on the trajectories showed a nonrandom structure with a well preserved backbone. The presence of geometrical patterns resembling those typical of π‐π interactions in both peptides, suggest that this kind of interactions may be relevant for the biological activity of GHRP‐6. Same conclusion can be drawn from the spatial proximity of residues DPhe5 and Lys6 sidechains. Copyright © 2012 John Wiley & Sons, Ltd.

It has long been known that people with blood group O are more severely affected by El Tor cholera than those with blood groups A or B. Microcalorimetry and NMR spectroscopy are used to evaluate the ability of the B-subunits of cholera toxin and E. coli heat-labile toxin to bind to selected blood group oligosaccharides.

AboutSectionsPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Graphical Abstract Saturation transfer difference (STD) NMR spectroscopy was used to study the role of aromatic moieties in the inhibition of α-glucosidases by N-arylmethyl ent-conduramine F-1. STD epitope mapping and molecular docking simulations provide new insights into the structure-based design of drugs targeting this enzyme (see figure). Glucosidases are a group of enzymes responsible of the glycosidic bond cleavage with different specificities depending on the number of monosaccharides, the position of cleavage, and the configuration of the hydroxy groups in their substrates. In particular, inhibitors of α-1,4-glucosidases have generated great interest as potential therapeutic agents for the treatment of type II diabetes (e.g., miglitol (N-2-hydroxyethyl-1-deoxynojirimycin), Glyset, Diastabol, Glucobay),1, 2 obesity,3 hepatitis B and C4, 5 and other viral diseases,6 and cancer.7 Previously, we have shown that N-benzylation of (+)-ent-conduramine F-1 (1) significantly increases its inhibitory activity toward α-1,4-glucosidase from yeast.8 Because of their relatively high hydrophobicity, N-benzyl derivatives of 1 might represent α-1,4-glucosidase inhibitors with improved bioavailability and pharmacokinetics.9 So far, rational drug design has not been applied to inhibitors of α-1,4-glucosidases, because the structural information available is very scarce and only related to the free forms of the protein. The lack of structural information on the nature of the interactions between α-1,4-glucosidases and their inhibitors has made it a difficult task to discover good lead compounds. In this work, we have attempted to understand the role of the aryl moieties in improving the inhibitory activities of N-benzyl derivatives of 1 using saturation transfer difference (STD) NMR spectroscopy. The method allows the binding of a ligand to a receptor to be characterize by using small amounts of protein (micromolar range), and it is very useful for mapping the binding epitope of the ligand with atomic resolution. Ligand protons that are in close contact with the protein binding pocket experience a larger fraction of saturation transfer than protons further away.10 Thus, protons of ligand directly involved in binding show larger signal increments than other ligand protons in STD NMR spectra. α-1,4-Glucosidase from Saccharomyces cerevisiae was used in this study as a model system to evaluate the interactions of ligand 1 and its N-benzyl derivatives 2–4 with the enzyme by STD NMR spectroscopy (Figure 1). Significant STD effects were observed for all ligands in the presence of α-1,4-glucosidase, which indicated that they are bound to the enzyme under the test conditions. In addition, to validate the stability of the inhibitors, 1H NMR spectra of the complexes were acquired after being left in solution for several days, and hydrolysis products were not observed. Figure 1Open in figure viewerPowerPoint Chemical structures of compounds 1–4. The inhibitory activities are also shown as IC50 and Ki values.8 The size of the observed STD effect does not only depend on the proximity of the proton to the receptor. In fact, if the longitudinal relaxation times (T1) of individual ligand protons are quite different, there is a severe interference on the epitope map for ligand–receptor interactions derived from STD measurements.11 Therefore, it is essential to consider the importance of this circumstance on STD experiments performed for molecules that have protons with substantially different T1 values. Measurements of T1 values for individual ligand protons in complex with α-1,4-glucosidase were undertaken for all ligands (Table 1). In general, H4 and H5 showed longer T1 values in all inhibitors, and important relative differences were observed within each ligand, with the exception of 2 that showed T1 values of 0.4–0.6 s. Table 1. Longitudinal relaxation times (T1) calculated for ligands 1–4 in complex with α-1,4-glucosidase.[a] 1 T1 2 T1 3 T1 4 T1 H1 0.93 H1/H2 0.42 H1/H2 0.77 H1/H2 0.88 H2 1.05 H3 0.52 H3 0.81 H3 1.17 H3 1.14 H4 0.57 H4 1.09 H4 1.52 H4 1.41 H5 0.60 H5 1.05 H5 1.25 H5 1.78 H6 0.53 H6 0.81 H6 0.87 H6 1.28 H7 0.29 H7 0.46 H2′ 1.08 H2′/H6′ 0.58 H2′/H6′ 0.86 H5′ 1.99 H3′/H5′ 0.69 H3′/H5′ 0.89 H6′ 1.26 H2′′/H6′′ 0.77 H7′ 1.27 H3′′/H5′′ 0.29 H8′ 1.23 NAc 4.70 [a] T1 values for individual protons measured for each inhibitor in complex with α-1,4-glucosidase are noted in seconds (s). The use of saturation times shorter than T1 has been suggested for improving the accuracy of STD results. However, under these conditions, poor signal-to-noise ratios are usually obtained due to low magnetization transfer from the receptor.11 To overcome this problem, we decided to use STD initial growing rates (STD0), calculated from the fitting of the saturation time data to monoexponential Equation (1): ((1)) where STD stands for the STD signal intensity of a given proton at saturation time Tsat, STDmax is the maximal STD intensity obtainable, and ksat stands for the observed saturation rate constant.12 Therefore, STD data were acquired on samples containing each ligand in the presence of α-1,4-glucosidase (200:1 molar ratio) at a series of saturation times (Tsat=0.25, 0.5, 1, 2, 3, 5 s), as shown in Figure 2 a. As a representative example, STD build-up curves for ligand 3 can be seen in Figure 2 b. Figure 2Open in figure viewerPowerPoint a) STD build-up curves for all protons in ligand 3. Experimental data were fitted to a rising exponential to calculate Ksat and STD. b) Reference NMR spectrum of a mixture of compound 3 and 0.15 mM of α-1,4-glucosidase in a 200:1 molar ratio. STD NMR spectra obtained at increasing saturation times of 0.25, 0.5, 1, 2, 3, and 5 s (from bottom to top). Clearly, the signal enhancement for the protons with shorter T1 values (0.29 s for H3′′ and H5′′) have already reached a plateau after 1 s. A slightly longer time was observed for H7 that showed the second shorter T1 value (0.46 s). Conversely, the other protons still developed signal up to saturation times around 2 or 3 s depending on their T1 values (longer than 0.8 s in all cases). Similar results were obtained for the other ligands. We believe that when comparing ligands with similar structures that bind into the same binding site, the important point is to focus on the overall pattern, and but not on the individual values of each proton. For example, for inhibitors 2–4, the STD enhancements are larger for the aromatic protons than for the conduramine protons (Table 2). In addition, it should be noted that the relative differences observed are bigger for the ligand with a tryptophan moiety (4), followed by the ligand with a pyridine ring (3), and finally by the phenolic derivative (2), for which the differences are not so important. If the purpose of N-benzylation of 1 was to add a substituent that would simply expel water molecules from the α-1,4-glucosidase active site and thus increase the binding constant13, 14 because of more a favorable binding entropy,15 we would expect the opposite behavior: larger STD effects at the H1 to H4 positions due to specific interactions (hydrogen bond) between the conduramine and the enzyme.16 Thus, the role of the N-substituents in 2–4 should be to interact directly with the protein. We also observed that the conduramine protons are affected by N-benzylation, independent of the nature of the aromatic ring of the inhibitor following the same general trend: H1,2,3 always show the smallest STD effect, whereas the olefinic protons H5,6 show a slight enhancement of the signal intensity in 2–4 compared with the olefinic signals of 1. Table 2. Saturation transfer difference (STD) effects calculated for ligands 1–4 in complex with α-1,4-glucosidase.[a] 1 STDfit 2 STDfit 3 STDfit 4 STDfit H1 98 H1/H2 79 H1/H2 124 H1/H2 143 H2 41 H3 54 H3 94 H3 71 H3 64 H4 100 H4 100 H4 100 H4 100 H5 97 H5 127 H5 143 H5 71 H6 101 H6 133 H6 200 H6 65 H7 110 H7 97 H2′ 386 H2′/H6′ 121 H2′/H6′ 200 H5′ 1029 H3′/H5′ 147 H3′/H5′ 245 H6′ 1429 H2′′/H6′′ 303 H7′ 643 H3′′/H5′′ 273 H8′ 471 NAc 29 [a] STDfit corresponds to the relative STD intensity for each ligand calculated from fitting the data to monoexponential Equation (1). The enzyme used in our NMR spectroscopy experiments was α-1,4-glucosidase derived from the yeast, S. cerevisiae. Unfortunately, although it is well known that the MAL 12 gene regulates the expression of this enzyme, as yet, no experimental 3D information is available. However, a number of homologous sequences with 3D structures deposited at the Protein Data Bank (PDB) are available and were found by using a basic local alignment search tool program (BLASTP) search.17 Of these sequences, the oligo-1,6-glucosidases from S. cerevisiae (PDB: 3AJ7)18 and Bacillus cereus (PDB: 1UOK)19 showed the highest sequence identity (72 % and 38.5 %, respectively) compared with the sequence of α-1,4-glucosidase from S. cerevisiae (see Supporting Information). Therefore, taking into account the good sequence identity between the α-1,4-glucosidase and the oligo-1,6-glucosidase from S. cerevisiae, we decided to build a theoretical model of α-1,4-glucosidase using homology modeling techniques.20 In fact, in α-1,4-glucosidase, the catalytic triad D 215, E 277, D 352 characteristic of oligo-1,6-glucosidase is conserved (D 211, E 273, D 346 in α-1,4-glucosidase) together with the residues D 69, H 112, R 213, H 351, and R 442 (D 65, H 108, R 209, H 345, and R 436 in α-1,4-glucosidase), which have been found to participate in a hydrogen-bond network within the active site of oligo-1,6-glucosidase.18 Molecular docking simulations were then undertaken to gain further insight into the most probable binding mode of the studied ligands.21 Considering that the residues within the active site of several members of the glycoside hydrolase family are highly conserved, we defined the binding site of α-1,4-glucosidase around those residues. To validate our results, the docked conformations for each ligand were superimposed and compared with the crystal structure of oligo-1,6-glucosidase in complex with maltose (PDB: 3A4A).18 The simulation results predict that all ligands interact with the active site residues in a very similar way, which suggests that the docking protocol was reasonable in identifying the binding conformation accurately. The four ligands used in this study share the ent-conduramine moiety, although ligands 2–4 also include different aromatic moieties. The best docking solutions for all ligands show almost superimposable poses for their respective ent-conduramine moieties, although the aromatic rings are accommodated in slightly different positions. Therefore, as otherwise stated, our discussion is common to all ligands. A visual assessment and a ligplot22 analysis of the results suggested that an extensive hydrogen-bond network could be formed between the ent-conduramine and several residues within the active site. In fact, R 436 can form a hydrogen bond with the hydroxy groups at C2 and C4 (2.75–2.85 Å). In addition, the hydroxy group at C4 is also in a good position to form a hydrogen bond with D 65 (2.7 Å). The hydroxy group at C3 could form hydrogen bonds with the catalytic residues D 211 (2.9 Å) and D 346 (3.0–3.2 Å), or even with H 345, although this residue is located slightly further away (3.3–3.4 Å). Likewise, the amine group at C1 could be involved in a hydrogen bond with T 212, and the double bond at C5–C6 could potentially interact positively with F 174. With regard to the aromatic moieties of the studied ligands, our simulations predict that although the binding cavity is narrow, there is enough space to accommodate them. In fact, the aromatic rings of ligands 2 and 4 could be stabilized by several hydrophobic contacts with F 155 and A 275, and our model suggests they would essentially be sandwiched by F 154 and F 297, with each residue interacting with a different face of the ligand. For inhibitor 3, in addition to the previously mentioned contacts, modeling also predicts interactions with H 236 and H 276 due to its bigger size (see Figure 3 and the Supporting Information). Figure 3Open in figure viewerPowerPoint Docked conformation obtained for ligand 3 in the modeled α-1,4-glucosidase active site. Only those residues within a distance of 4 Å of the ligand are shown. The molecular surface of the binding cavity is shown in yellow. The ligand is depicted with green bonds for clarity. In conclusion, introduction of aromatic moieties on iminosugars and their analogues might decrease24, 25 or increase26 their inhibitory activity against different glycosidases. In the case of (+)-ent-conduramine F-1 (1), which is a moderate inhibitor of α-1,4-glucosidases, N-benzylation gives a derivative with significantly increased inhibitory activity. By applying STD NMR spectroscopy, we have demonstrated for the first time that the aromatic moieties of N-benzyl ent-conduramine F-1 derivatives interact strongly with α-1,4-glucosidase from S. cerevisiae—more strongly than the conduramine moiety. Interestingly, upon N-benzylation of 1, the olefinic protons experience enhanced interaction with the enzyme, but this is not true for the other protons in the ligand. Acknowledgements This research work was funded by the Ministerio de Ciencia y Tecnología (Spain) (CTQ 2006-13376), the Secrétariat d′Etat à l′Education et à la Recherche (SER) (Switzerland), the FP6 European TRIoH project (LSHB-2003-503480: OFES No. 03.07380FES), and the Swiss National Science Foundation. S.K.K. acknowledges the Gobierno de Canarias (Spain) for an “A. Gonzalez” PhD Scholarship and the University of Los Andes (Venezuela) for financial support. Supporting Information Detailed facts of importance to specialist readers are published as ”Supporting Information”. Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Filename Description open_201100004_sm_miscellaneous_information.pdf12.9 MB miscellaneous_information Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. References 1 1aX. Chen, Y. Zheng, Y. Shen, Curr. Med. Chem. 2006, 13, 109– 116; 1bD. M. Casirola, R. P. Ferraris, Metab. Clin. Exp. 2006, 55, 832– 841. 2 2aC. Levetan, Curr. Med. Res. Opin. 2007, 23, 945– 952; 2bD.-S. Lee, J.-M. Lee, S.-U. Kim, K.-T. Chang, S.-H. Lee, Int. J. Mol. Med. 2007, 20, 379– 383. 3D. E. Rosenberg, S. A. Jabbour, B. J. Goldstein, Diabetes Obes. Metab. 2005, 7, 642– 653. 4N. Zitzmann, A. S. Mehta, S. Carrouee, T. D. Butters, F. M. Platt, J. McCauley, B. S. Blumberg, R. A. Dwek, T. M. Block, Proc. Natl. Acad. Sci. USA 1999, 96, 11878– 11882. 5C. Lazar, D. Durantel, A. Macovei, N. Zitzmann, F. Zoulim, R. A. Dwek, N. Branza-Nichita, Antiviral Res. 2007, 76, 30– 37. 6 6aT. A. Houston, J. T. Blanchfield, Mini Rev. Med. Chem. 2003, 3, 669– 678; 6bY. Tanaka, J. Kato, M. Kohara, M. S. Galinski, Antiviral Res. 2006, 72, 1– 9. 7R. Pili, J. Chang, R. A. Partis, R. A. Mueller, F. J. Chrest, A. Passaniti, Cancer Res. 1995, 55, 2920– 2926. 8R. Lysek, C. Schutz, S. Favre, A. C. O’Sullivan, C. Pillonel, T. Kruelle, P. M. J. Jung, I. Clotet-Codina, J. A. Este, P. Vogel, Bioorg. Med. Chem. 2006, 14, 6255– 6282. 9D. Elstein, A. Dweck, D. Attias, I. Hadas-Halpern, S. Zevin, G. Altarescu, J. F. M. G. Aerts, S. van Weely, A. Zimran, Blood 2007, 110, 2296– 2301. 10 10aM. Mayer, B. Meyer, Angew. Chem. 1999, 111, 1902– 1906; Angew. Chem. Int. Ed. 1999, 38, 1784– 1788; 10bB. Meyer, T. Peters, Angew. Chem. 2003, 115, 890– 918; Angew. Chem. Int. Ed. 2003, 42, 864– 890. 11J. L. Yan, A. D. Kline, H. P. Mo, M. J. Shapiro, E. R. Zartler, J. Magn. Reson. 2003, 163, 270– 276. 12M. Mayer, T. L. James, J. Am. Chem. Soc. 2004, 126, 4453– 4460. 13R. Łysek, C. Schütz, P. Vogel, Bioorg. Med. Chem. Lett. 2005, 15, 3071– 3075. 14R. Łysek, S. Favre, P. Vogel, Tetrahedron 2007, 63, 6558– 6572. 15S. W. Homans, ChemBioChem 2005, 6, 1585– 1591. 16A. H. Daranas, H. Shimizu, S. W. Homans, J. Am. Chem. Soc. 2005, 126, 11870– 11876. 17H. M. Berman, J. Westbrook, Z. Feng, G. Gilliland, T. N. Bhat, H. Weissig, I. N. Shindyalov, P. E. Bourne, Nucleic Acids Res. 2000, 28, 235– 242. 18K. Yamamoto, H. Miyake, M. Kusunoki, S. Osaki, FEBS Journal 2010, 277, 4205– 4214. 19K. Watanabe, Y. Hata, H. Kizaki, Y. Katsube, Y. Suzuki, J. Mol. Biol. 1997, 269, 142– 153. 20 20aK. Arnold, L. Bordoli, J. Kopp, T. Schwede, Bioinformatics 2006, 22, 195– 201; 20bF. Kiefer, K. Arnold, M. Künzli, L. Bordoli, T. Schwede, Nucleic Acids Res. 2009, 37, D 387–D 392. 21 21aG. M. Morris, R. Huey, W. Lindstrom, M. F. Sanner, D. S. Goodsell, A. J. Olson, J. Comput. Chem. 2009, 30, 2785– 2791; 21bO. Trott, A. J. Olson, J. Comp. Chem. 2010, 31, 455– 461. 22A. C. Wallace, R. A. Laskowski, J. M. Thornton, Prot. Eng. 1995, 8, 127– 134. 23M. Böhm, E. Lorthiois, M. Meyyappan, A. Vasella, Helv. Chim. Acta 2003, 86, 3818– 3835. 24O. Lopez Lopez, M. Bols, ChemBioChem 2007, 8, 657– 661. 25M. I. García-Moreno, J. M. Benito, C. Ortiz Mellet, J. M. García Fernández, J. Org. Chem. 2001, 66, 7604– 7614. 26S. Gerber-Lemaire, F. Popowycz, E. Rodriguez-García, A. T. C. Asenjo, I. Robina, P. Vogel, ChemBioChem 2002, 3, 466– 470. Citing Literature Volume1, Issue1February 2012Pages 13-16 FiguresReferencesRelatedInformation

Five-membered rings are clearly among the most common structural motifs found in chemistry and biology. Nevertheless, the configuration of conformationally mobile five-membered rings is often difficult to assign from nuclear magnetic resonance (NMR) data. A simple, reliable, and efficient approach for the stereochemical analysis of five-membered rings based on the measurement of NMR coupling constants is presented. Density functional theory calculations using representative conformations of the full conformational space available to rings with different substitution patterns were used to identify differences between the accessible coupling constant values for cis and trans relative orientations of the substituents. The calculations were assessed experimentally using NMR data obtained from a number of models. This approach can be easily used to analyze different five-membered rings, such as oxolanes, cyclopentanes, furanosides and pyrrolidines, and their relative configuration can be determined without the need for making further conformational considerations.

The structure and diffusion behavior of the neutral and charged first-generation polyamidoamine (PAMAM-G1) dendrimer and its β-cyclodextrin (β-CD) conjugate in aqueous solutions were studied by molecular dynamics (MD) simulations. Diffusion coefficients were obtained from mean square displacement data, considering 500-ps intervals of normal diffusive regime within three simulation runs. Calculated diffusion coefficients were compared with experimental values obtained from diffusion ordered spectroscopy (DOSY) experiments for both neutral and charged dendrimer and conjugate structures. Our results show good agreement between calculated and experimental results, accounting for the reliability of our MD simulations.

Aqueous solution diffusion coefficients for G0–G3 PAMAM dendrimers were determined from DOSY-NMR spectroscopy at high and neutral pH. The study was performed in a dilute regime and diffusion coefficients at infinite dilution (D 0) were estimated from the variation of diffusion coefficients with dendrimer concentration. Hydrodynamic radii (R h) for each dendrimer were estimated from D 0 using the Stoke–Einstein relationship at both pH. According to D 0 and R h values, the structure of G0–G1 PAMAM dendrimers is almost insensitive to pH variations, whereas G2–G3 PAMAM dendrimers undergo swelling at neutral pH, due to surface amino groups protonation. Experimental diffusion coefficients show a scaling trend with the number of dendrimer atoms (N), with scaling laws of the type \( D_{0} \propto N^{\alpha } \), where α takes values of −0.39 and −0.50 at pH 12 and 7, respectively. For the first time, experimental data accounts for the scaling behavior of aqueous diffusion coefficients for low generation PAMAM dendrimers, as previously reported from molecular dynamics simulations.

In order for biodiesel to be commercialized as pure biofuel or blending stock for diesel fuels, it must meet a set of requirements defined in standard specifications for a safe and satisfactory engine operation, one of these specifications is the content of fatty acid methyl esters (FAME). Besides, this parameter indicates the performance of the transesterification reaction for biofuel production from vegetable oils. There are several methods to determinate FAME content in biodiesel samples (chromatography, nuclear magnetic resonance spectroscopy and FTIR spectroscopy); however, they take long times and high cost for FAME content determination. From a practical point of view, in industrial biodiesel production is usually necessary to estimate the FAME value quickly. This paper presents correlations experimentally obtained from different oil feedstocks in order to estimate the biodiesel FAME content from the biodiesel dynamic viscosity, a fast determination parameter.

abStract Two new dicationic ionic liquids 1,7-bis(3-methylimidazolium-1-yl)heptane bromide (I) and 1,8-bis(3-methylimidazolium-1-yl)octane bromide (II) have been synthesized and characterized by elemental analysis, FT-IR, 1 H and 13 C NMR, and TG-DSC techniques. The compound (I) is liquid at room temperature, whereas (II) is liquid at 42.7oC. Keywords : Dicationic Ionic liquids, thermal properties, synthesis. introduction Ionic liquids (ILs) have been recognized as potential new green alternatives to conventional organic solvents in a wide range of synthetic, catalytic, separation and electrochemical applications. They are characterized by their unique physicochemical properties, including low melting points, low inflammability, and tunable hydrophobicities. They are stable in a wide range of temperature, and have great chemical and electrochemical stability. In addition, they have negligible vapor pressures so there is no loss of solvent through evaporation, avoiding environmental problems due to volatilization

In the present study ozonized triolein with 739 mmol-equiv/kg peroxide index is characterized by NMR. The triolein and ozonized triolein show very similar H-1 NMR spectra except for the resonances at delta 9.74 ppm, which correspond to aldehydic protons and delta 5.14 ppm (ozonides methylic protons). Other new signal assignments are based on the connectivities provided by the proton scalar coupling constants delta 2.41 ppm (methylenic group allylic to aldehydic protons and ozonides methynic protons) and delta 1.67 ppm (methylenic protons in p position with respect to ozonides methylic protons). From the C-13 and H-1-C-13 spectrum of the ozonized triolein, the presence of ozonides was confirmed by the signals delta 104.2 and 104.3 ppm, respectively. Other new signals in delta 43.9 ppm confirm the presence of methylenic carbon ozonides. From the structural elucidation of ozonated triglycerides, relevant chemical information about ozonated vegetable oil can be found.