Periodic density functional theory (DFT) calculations have been used to study the effect of doping a gold model surface with atoms of other transition metals on the catalysis of the reaction of oxygen dissociation. It was found that the doping of gold surfaces with atoms of Rh, Ir or Ni stabilizes the adsorbate-surface interactions with a concomitant decrease of the activation energy barriers for the oxygen dissociation to values that are smaller than the adsorption energies of molecular oxygen (O-2*) on those surfaces. These findings suggest that O-2 dissociation is possible at normal conditions on these bimetallic surfaces, which is very relevant not only for the oxidation of CO to CO2 but for other oxidation reactions. In the case of the most active bimetallic surface obtained by doping with Ni atoms, it is shown that the reaction of CO oxidation is more favorable than the reaction of CO dissociation, i.e., suggesting that CO methanation will be less likely. Finally, useful relationships relating the activation energy barrier for the reaction of O-2 dissociation with the Bader charge in the doping element, with the reaction energy, with the adsorption energy of the reaction products and with the adsorption energy of an oxygen atom were obtained.

Tamoxifen is a selective estrogen receptor modulator that is used as an adjuvant and/or chemotherapeutic agent for the treatment of all stages of hormone-dependent breast cancer. Currently there is a deep interest in the study of tamoxifen biotransformation and identification of metabolites since they can significantly contribute to the overall pharmacological or adverse effects of the drug. Accordingly, the study of the electrochemical behavior of tamoxifen in aqueous solution is reported. To clarify the occurring oxidative process and to assess the influence of the functional groups on the oxidation mechanism, the voltammetric assessment was extended to the study of tamoxifen's analogues (E)-tamoxifen and dihydrotamoxifen, and to its main phase I oxidative metabolite, N-desmethyl tamoxifen. The data found shows that the oxidative processes occurring in tamoxifen are essentially related with the two chemical moieties present in the molecule: the substituted aromatic nucleus and the tertiary amine group. Moreover, the results obtained suggest that the ethylenic linkage is not critical for tamoxifen's oxidation although it could play an important role in the course of the oxidation process. These results could contribute to highlight some remaining questions regarding tamoxifen's metabolic behavior and to the development of new analytical strategies, based on electrochemical approaches.

In this work we describe the electrochemical behavior of an ionic liquid formed between choline chloride (ChCl) and chromium chloride hexahidrated (CrCl3 center dot 6H(2)O) in the ratio of 2.5:1 containing 20 wt.% of added ultrapure water, using cyclic voltammetry and chronoamperometry. The reduction of Cr(III) occurs in two steps, Cr(III) to Cr(II) and Cr(II) to Cr(0), respectively. The first step is controlled by diffusion. For the first time a thorough study of the nucleation of chromium from Cr(III) ionic liquid solutions is described. Furthermore for less cathodic potentials there is a diffusion control of nuclei growth. For more cathodic potentials the lattice incorporation of adatoms to the growing nuclei is the limiting process. The additive free bright chromium deposit obtained is formed by semi-spherical nuclei. The effect of hydrogen evolution is only observed for E < - 1.90 V.

Resistance of bacteria to current antibiotics has increased worldwide, being one of the leading unresolved situations in public health. Due to negligence regarding the treatment of community-acquired diseases, even healthcare facilities have been highly impacted by an emerging problem: nosocomial infections. Moreover, infectious diseases, including nosocomial infections, have been found to depend on multiple pathogenicity factors, confirming the need to discover of multi-target antibacterial agents. Drug discovery is a very complex, expensive, and time-consuming process. In this sense, Quantitative Structure-Activity Relationships (QSAR) methods have become complementary tools for medicinal chemistry, permitting the efficient screening of potential drugs, and consequently, rationalizing the organic synthesis as well as the biological evaluation of compounds. In the consolidation of QSAR methods as important components of chemoinformatics, the use of mathematical chemistry, and more specifically, the use of graph-theoretical approaches has played a vital role. Here, we focus our attention on the evolution of QSAR methods, citing the most relevant works devoted to the development of promising graph-theoretical approaches in the last 8 years, and their applications to the prediction of antibacterial activities of chemicals against pathogens causing both community-acquired and nosocomial infections.

Aminopeptidase N (APN) inhibitors have been reported to be effective in treating of life threatening diseases including cancer. Validated ligand- and structure-based pharmacophore mapping approaches were combined with Bayesian modeling and recursive partitioning to identify structural and physicochemical requirements for highly active APN inhibitors. Based on the assumption that ligand- and structure-based pharmacophore models are complementary, the efficacy of 'multiple pharmacophore screening' for filtering true positive virtual hits was investigated. These multiple pharmacophore screening methods were utilized to search novel virtual hits for APN inhibition. The number of hits was refined and reduced by recursive partitioning, drug-likeliness, pharmacokinetic property prediction, and comparative molecular-docking studies. Four compounds were proposed as the potential virtual hits for APN enzyme inhibition. © 2013 Springer Science+Business Media Dordrecht.

Objectives and Methods Matrix metalloproteinase-2 (MMP-2) is a potential target in metastases. Regression (conventional 2D QSAR) and classification (recursive partitioning (RP), Bayesian modelling) QSAR, pharmacophore mapping and 3D QSAR (comparative molecular field analysis and comparative molecular similarity analysis) were performed on 202 MMP-2 inhibitors. Key findings Quality of the regression models was justified by internal (Q2) and external (R2Pred) cross-validation parameters. Stepwise regression was used to develop linear model (Q2 = 0.822, R 2Pred = 0.667). Genetic algorithm developed linear (Q 2 = 0.845, R2Pred = 0.638) and spline model (Q2 = 0.882, R2Pred = 0.644). The RP and Bayesian models showed cross-validated area under receiver operating characteristic curve (AUCROC-CV) of 0.805 and 0.979 respectively. QSAR models depicted importance of descriptors like five-membered rings, fractional positively charged surface area, lipophilocity and so on. Higher molecular volume was found to be detrimental. Pharmacophore mapping was performed with two tools - Hypogen and PHASE. Both models indicated that one hydrophobic and three hydrogen bond acceptor features are essential. The Pharmacophore-aligned structures were used for CoMFA (Q2 of 0.586 and R2Pred of 0.689) and CoMSIA (Q2 of 0.673 and R2Pred of 0.758), results of which complied with the other analyses. Conclusions All modelling techniques were compared to each other. The current study may help in designing novel MMP-2 inhibitors. © 2013 Royal Pharmaceutical Society.

Chloroquine resistance is nowadays a great problem in malaria. Aurone derivatives were effective against chloroquine resistant parasite. Validated density functional theory (DFT)-based chemometric modeling, hologram QSAR (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity analysis (CoMSIA) studies were conducted on 35 aurone derivatives having antimalarial activity. 2D-QSAR models were developed on the training sets by Y-based ranking method. This model was validated on 50 pairs of the test and the training sets by k-Means cluster analysis method. HQSAR, CoMFA, and CoMSIA models were validated by standard techniques and each method validates the DFT-based 2D-QSAR study and in turn validates the earlier observed structural activity relationship data as well as each other. DFT-based 2D-QSAR model suggests that the increase of Mulliken charge at C14 and HOMO density located on C11 may be conducive to antimalarial activity. Ethyl group attached to C14 and the increase of the value of chemical potential may be beneficial for antimalarial activity. Methoxy fragment is important for better antimalarial activity by HQSAR study. CoMFA analysis shows a favorable steric green region is located near C14 whereas the unfavorable yellow region is far away from C14. A large blue region located near C14 indicates the positively charged groups are favorable at this position. CoMSIA steric features correlates well with the CoMFA steric features. CoMSIA study suggests the bulky hydrophobic substitution at C14 is necessary for antimalarial activity. These results may be utilized to obtain potential antimalarial molecules. © 2013 Springer Science+Business Media New York.

Chloroquine resistance is nowadays a great problem. Aurone derivatives are effective against chloroquine resistant parasite. Ligand based validated comparative chemometric modeling through 2D-QSAR and kNN-MFA 3D-QSAR studies as well as common feature 3D pharmacophore mapping were done on thirtyfive aurone derivatives having antimalarial activity. Statistically significant 2D-QSAR models were generated on unsplitted as well as splitted dataset by MLR and PLS technique. The MLR model of the unsplitted method was validated by two-deep cross validation and 10 fold cross validation for determining the predictive ability. The PLS technique of the unsplitted method was done to compare the significance of these methods. In the splitted method, model was developed on the training set by Y-based ranking method by using the same descriptors and was validated on fifty pairs of the test and the training sets by k-MCA technique. These models generated by using the same descriptors were well validated irrespective of MLR as well as PLS analysis of unsplitted as well as splitted methods and are showing similar results. Therefore, these descriptors and model generated were reliable and robust. The kNN-MFA 3D-QSAR models were generated by three variable selection methods: genetic algorithm, simulated annealing and stepwise regression. The kNN-MFA 3D-QSAR results support the 2D QSAR data and in turn validate the earlier observed SAR results. Common feature 3D-pharmacophore generation was performed on these compounds to validate both 2D and 3D-QSAR studies as well as the earlier observed SAR data. The work highlights the required structural features for the higher antimalarial activity. © 2013 Bentham Science Publishers.