A neural networks study of quinone compounds with trypanocidal activity

This work investigates neural network models for predicting the trypanocidal activity of 28 quinone compounds. Artificial neural networks (ANN), such as multilayer perceptrons (MLP) and Kohonen models, were employed with the aim of modeling the nonlinear relationship between quantum and molecular descriptors and trypanocidal activity. The calculated descriptors and the principal components were used as input to train neural network models to verify the behavior of the nets. The best model for both network models (MLP and Kohonen) was obtained with four descriptors as input. The descriptors were T(5) (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors provide information on the kind of interaction that occurs between the compounds and the biological receptor. Both neural network models used here can predict the trypanocidal activity of the quinone compounds with good agreement, with low errors in the testing set and a high correctness rate. Thanks to the nonlinear model obtained from the neural network models, we can conclude that electronic and structural properties are important factors in the interaction between quinone compounds that exhibit trypanocidal activity and their biological receptors. The final ANN models should be useful in the design of novel trypanocidal quinones having improved potency.

A combined X-ray and theoretical study of flavonoid compounds with anti-inflammatory activity

The structure of 7,4`-dimethoxy-3`-acetylflavone (tithonin-Ac) has been determined by X-ray diffraction and its geometry is compared with optimized geometrical parameters obtained by means of density functional theory at the B3LYP/6-311++G(d,p) level of calculation. in addition, vertical ionization potential (IPv) and acidity for tithonin-Ac and two derivatives have been also calculated. Calculations of spin densities were also performed for the radical formed by the electron abstraction of other flavones. The unpaired electron is located on C3 carbon atom (21-25%). (C) 2008 Elsevier B.V. All rights reserved.

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.

An insight into the beginning stage of the aqueous ring opening metathesis polymerization of exo,exo-7-oxabicyclo[2.2.1]hept-5-ene-2,3-dicarboxylic acid with Ru(III) compounds: the consumption of Ru(III) species in the presence of carboxylic acids monitored by ESR spectroscopy

The presence of paramagnetic species in the aqueous ring opening metathesis polymerizations of the exo,exo-7-oxabicyclo[2.2.1]hept-5-ene-2,3-dicarboxylic acid monomer with RuCl(3) and K(2)[RuCl(5)H(2)O] compounds was studied using ESR techniques. It was observed that the intensities of the Ru(III) signals in the ESR spectra decrease on the time scale of the induction period so that the ROMP can take place. The intensity of the Ru(III) signal almost disappeared 50 min after reacting with K(2)[RuCl(5)H(2)O] and after 100 mm in the case of RuCl(3). Reactions of the cis-[Ru(NH(3))(4)(H(2)O)(2)](tfms)(3) and [Ru(NH(3))(5)H(2)O](tfms)(3) complexes with the monomer and different organic compounds representing the organic functions in the monomer (furan, norbornene, but-2-ene-1,4-diol and formic, acetic, oxalic and maleic acids) were also monitored by ESR and UV/vis spectra. It was deduced that the organic acids provide the disappearance of the Ru(III) signal. The proton NMR relaxation times of the residual water in D(2)O for reactions with oxalic acid suggested that the presence of paramagnetic ions in the solution decreases along with

Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid Compounds

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.

Synthesis and characterization of mono and polymeric cyclopalladated compounds: Crystal and molecular structure of [{Pd(dmba)(ONO(2))}(2)(mu-pz)] center dot H(2)O (pz = pyrazine)

In the treatment of cyclometallated dimer [Pd(dmba)(mu-Cl)](2) (dmba = N,N-dimethylbenzylamine) with AgNO(3) and acetonitrile the result was the monomeric cationic precursor [Pd(dmba)(NCMe)(2)](NO(3)) (NCMe=acetonitrile) (1). Compound 1 reacted with m-nitroaniline (m-NAN) and pirazine (pz), originating [Pd(dmba)(ONO(2))(m-NAN)] (2) and [{Pd(dmba)(ONO(2))}(2)(mu-pz)] center dot H(2)O (3), respectively. These compounds were characterized by elemental analysis, IR and NMR spectroscopy. The IR spectra of (2-3) display typical bands of monodentade O-bonded nitrate groups, whereas the NMR data of 3 are consistent with the presence of bridging pyrazine ligands. The structure of compound 3 was determined by Xray diffraction analysis. This packing consists of a supramolecular chain formed by hydrogen bonding between the water molecule and nitrato ligands of two consecutive [Pd(2)(dmba)(2)(ONO(2))2(mu-pz)] units. (c) 2008 Elsevier Ltd. All rights reserved.

Docking and molecular dynamics simulation of quinone compounds with trypanocidal activity

In this work, two different docking programs were used, AutoDock and FlexX, which use different types of scoring functions and searching methods. The docking poses of all quinone compounds studied stayed in the same region in the trypanothione reductase. This region is a hydrophobic pocket near to Phe396, Pro398 and Leu399 amino acid residues. The compounds studied displays a higher affinity in trypanothione reductase (TR) than glutathione reductase (GR), since only two out of 28 quinone compounds presented more favorable docking energy in the site of human enzyme. The interaction of quinone compounds with the TR enzyme is in agreement with other studies, which showed different binding sites from the ones formed by cysteines 52 and 58. To verify the results obtained by docking, we carried out a molecular dynamics simulation with the compounds that presented the highest and lowest docking energies. The results showed that the root mean square deviation (RMSD) between the initial and final pose were very small. In addition, the hydrogen bond pattern was conserved along the simulation. In the parasite enzyme, the amino acid residues Leu399, Met400 and Lys402 are replaced in the human enzyme by Met406, Tyr407 and Ala409, respectively. In view of the fact that Leu399 is an amino acid of the Z site, this difference could be explored to design selective inhibitors of TR.