Design of novel antituberculosis compounds using graph-theoretical and substructural approaches

The increasing resistance of Mycobacterium tuberculosis to the existing drugs has alarmed the worldwide scientific community. In an attempt to overcome this problem, two models for the design and prediction of new antituberculosis agents were obtained. The first used a mixed approach, containing descriptors based on fragments and the topological substructural molecular design approach (TOPS-MODE) descriptors. The other model used a combination of two-dimensional (2D) and three-dimensional (3D) descriptors. A data set of 167 compounds with great structural variability, 72 of them antituberculosis agents and 95 compounds belonging to other pharmaceutical categories, was analyzed. The first model showed sensitivity, specificity, and accuracy values above 80% and the second one showed values higher than 75% for these statistical indices. Subsequently, 12 structures of imidazoles not included in this study were designed, taking into account the two models. In both cases accuracy was 100%, showing that the methodology in silico developed by us is promising for the rational design of antituberculosis drugs.

Phenol-furfural resins to elaborate composites, reinforced with sisal fibers - Molecular analysis of resin and properties of composites

Resol type resins were prepared in alkaline conditions (potassium hydroxide or potassium carbonate) using furfural obtained by acid hydrolysis of abundant renewable resources from agricultural and forestry waste residues. The structures of the resins were fully determined by H-1, C-13, and 2D NMR spectrometries with the help of four models compounds synthesized specially for this study. MALDI-Tof mass spectrometry experiments indicated that a majority of linear oligomers and a minority of cyclic ones constituted them. Composites were prepared with furfural-phenol resins and sisal fibers. These fibers were chosen mainly because they came from natural lignocellulosic material and they presented excellent mechanical microscopy images indicated that the composites displayed excellent adhesion between resin and fibers. Impact strength measurement showed that mild conditions were more suitable to prepare thermosets. Nevertheless, mild conditions induced a high-diffusion coefficient for water absorption by composites. Composites with good properties could be prepared using high proportion of materials obtained from biomass without formaldehyde. (c) 2008 Wiley Periodicals, Inc.

A chemometric study of the 5-HT1A receptor affinities presented by arylpiperazine compounds

Arylpiperazine compounds are promising 5-HT1A receptor ligands that can contribute for accelerating the onset of therapeutic effect of selective serotonin reuptake inhibitors. In the present work, the chemometric methods HCA, PCA, KNN, SIMCA and PLS were employed in order to obtain SAR and QSAR models relating the structures of arylpiperazine compounds to their 5-HT1A receptor affinities. A training set of 52 compounds was used to construct the models and the best ones were obtained with nine topological descriptors. The classification and regression models were externally validated by means of predictions for a test set of 14 compounds and have presented good quality, as verified by the correctness of classifications, in the case of pattern recognition studies, and b, the high correlation coefficients (q(2) = 0.76, r(2) = 0.83) and small prediction errors for the PLS regression. Since the results are in good agreement with previous SAR studies, we can suggest that these findings can help in the search for 5-HT1A receptor ligands that are able to improve antidepressant treatment. (c) 2007 Elsevier Masson SAS. All rights reserved.