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 quantum chemical study on a set of non-imidazole H(3) antihistamine molecules

Molecular orbital calculations were carried out on a set of 28 non-imidazole H(3) antihistamine compounds using the Hartree-Fock method in order to investigate the possible relationships between electronic structural properties and binding affinity for H3 receptors (pK(i)). It was observed that the frontier effective-for-reaction molecular orbital (FERMO) energies were better correlated with pK(i) values than highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy values. Exploratory data analysis through hierarchical cluster (HCA) and principal component analysis (PCA) showed a separation of the compounds in two sets, one grouping the molecules with high pK(i) values, the other gathering low pK(i) value compounds. This separation was obtained with the use of the following descriptors: FERMO energies (epsilon(FERMO)), charges derived from the electrostatic potential on the nitrogen atom (N(1)), electronic density indexes for FERMO on the N(1) atom (Sigma((FERMO))c(i)(2)). and electrophilicity (omega`). These electronic descriptors were used to construct a quantitative structure-activity relationship (QSAR) model through the partial least-squares (PLS) method with three principal components. This model generated Q(2) = 0.88 and R(2) = 0.927 values obtained from a training set and external validation of 23 and 5 molecules, respectively. After the analysis of the PLS regression equation and the values for the selected electronic descriptors, it is suggested that high values of FERMO energies and of Sigma((FERMO))c(i)(2), together with low values of electrophilicity and pronounced negative charges on N(1) appear as desirable properties for the conception of new molecules which might have high binding affinity. 2010 Elsevier Inc. 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.

A representação social de disciplinas didático-pedagógicas no contexto da formação inicial docente: um entremear de saberes

We seek, through this study, to analyze about social representation that the students of licentiate degree course of the Federal Institute of Education, Science and Technology of Rio Grande do Norte - IFRN - have about didactic-pedagogical subjects. We utilize the Social Representations Theory (MOSCOVICI, 2009; 2012; JODELET, 2001) as a theoretical and methodological contribution and as aim, we identify this social representation and understand how it is influenced by the formation of these undergraduates. So we developed the research under the seven undergraduate classroom courses offered by IFRN, namely: Biology, Spanish, Physics, Geography, Computer Science, Mathematics and Chemistry, covering units located both in the capital and in the countryside. While methodological approach we used the Procedure of Multiple Classification (PMC) - (ROAZZI, 1995), whose realization requires a set of words achieved through of Free Technique of Words Association - FTWA - (ABRIC, 1998). For this realization we have a total of one hundred twenty (120) participants, with thirty (30) in FTWA and other stage in the realization of free classification and directed that correspond to the MPR. Achieved the empirical data, we use the analysis of content (BARDIN, 2011; FRANCO, 2007) and multidimensional (ROAZZI, 1995) for the course of his interpretation. Finally, we identify the social representation of didactic and pedagogical subjects centered around the idea that it is through these subjects that can achieve the profile of "good professional" as one who gathers knowledge and attributes required for the full development of teaching involving capabilities it and characteristics that mark the sense of professionalism. Furthermore, we found that the anchoring social representation on the understanding that these disciplines "teach the teacher to be" in the image and its objectification of the "good teacher", ie, one that reaches through the training process and experiences, qualities that make it unique and able to carry full professional. Still see that the actions of the teacher trainer affects the way students perceive, assume and engage in the study of teaching and pedagogical subjects and it reflects significantly the social representation then created

SKPDB: A structural database of shikimate pathway enzymes

Background: The functional and structural characterisation of enzymes that belong to microbial metabolic pathways is very important for structure-based drug design. The main interest in studying shikimate pathway enzymes involves the fact that they are essential for bacteria but do not occur in humans, making them selective targets for design of drugs that do not directly impact humans.Description: The ShiKimate Pathway DataBase (SKPDB) is a relational database applied to the study of shikimate pathway enzymes in microorganisms and plants. The current database is updated regularly with the addition of new data; there are currently 8902 enzymes of the shikimate pathway from different sources. The database contains extensive information on each enzyme, including detailed descriptions about sequence, references, and structural and functional studies. All files (primary sequence, atomic coordinates and quality scores) are available for downloading. The modeled structures can be viewed using the Jmol program.Conclusions: The SKPDB provides a large number of structural models to be used in docking simulations, virtual screening initiatives and drug design. It is freely accessible at http://lsbzix.rc.unesp.br/skpdb/. © 2010 Arcuri et al; licensee BioMed Central Ltd.

Predição computacional de promotores em Xanthomonas axonopodis pv. citri

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

DNA for nano-bio scale computation of chemical formalisms using Higher Order Logic (HOL) and analysis using an interdisciplinary approach

Bio-molecular computing, 'computations performed by bio-molecules', is already challenging traditional approaches to computation both theoretically and technologically. Often placed within the wider context of ´bio-inspired' or 'natural' or even 'unconventional' computing, the study of natural and artificial molecular computations is adding to our understanding of biology, physical sciences and computer science well beyond the framework of existing design and implementation paradigms. In this introduction, We wish to outline the current scope of the field and assemble some basic arguments that, bio-molecular computation is of central importance to computer science, physical sciences and biology using HOL - Higher Order Logic. HOL is used as the computational tool in our R&D work. DNA was analyzed as a chemical computing engine, in our effort to develop novel formalisms to understand the molecular scale bio-chemical computing behavior using HOL. In our view, our focus is one of the pioneering efforts in this promising domain of nano-bio scale chemical information processing dynamics.

Smart histogram analysis applied to the skull-stripping problem in T1-weighted MRI

In this paper we address the "skull-stripping" problem in 3D MR images. We propose a new method that employs an efficient and unique histogram analysis. A fundamental component of this analysis is an algorithm for partitioning a histogram based on the position of the maximum deviation from a Gaussian fit. In our experiments we use a comprehensive image database, including both synthetic and real MRI. and compare our method with other two well-known methods, namely BSE and BET. For all datasets we achieved superior results. Our method is also highly independent of parameter tuning and very robust across considerable variations of noise ratio.

The basic antioxidant structure for flavonoid derivatives

An antioxidant structure-activity study is carried out in this work with ten flavonoid compounds using quantum chemistry calculations with the functional of density theory method. According to the geometry obtained by using the B3LYP/6-31G(d) method, the HOMO, ionization potential, stabilization energies, and spin density distribution showed that the flavonol is the more antioxidant nucleus. The spin density contribution is determinant for the stability of the free radical. The number of resonance structures is related to the pi-type electron system. 3-hydroxyflavone is the basic antioxidant structure for the simplified flavonoids studied here. The electron abstraction is more favored in the molecules where ether group and 3-hydroxyl are present, nonetheless 2,3-double bond and carbonyl moiety are facultative.

First- and second-row transition metal oxa-aza macrocyclic complexes: a DFT study of an octahedral conformation

A theoretical study of structures of the 1,7,1 l,17-tetraoxa-2,6,12,16-tetraaza-cycloeicosane ligand ([20]AneN(4)O(4)) coordinated to Fe2+, Co2+, Ni2+, Ru2+, Rh2+, and Pd2+ transition metals ions was carried out with the DFT/B3LYP method. Complexes were fully optimized in C-s symmetry with the metal ions coordinated either to nitrogen (1a) or oxygen atoms (1b). For all the cases performed in this work, 1a was always more stable than 1b. Considering each row it is possible to see that the binding energy increases with the atomic number. The M2+ cation binding energies increase in the following order: Fe2+ < Ru2+ < Co2+ < Ni2+ < Rh2+ < Pd2+. In addition, it was observed the preference of Pd2+ and Rh2+ complexes for a tetrahedral arrangement, while Fe2+, Ru2+, Co2+, Ni2+ complexes had a preference for the octahedral arrangement. From the orbital representation results, it was seen that 1b unsymmetrical orbitals may influence the susceptibility over metal ions orientation toward heteroatoms orbitals.

Effect of the thermostat in the molecular dynamics simulation on the folding of the model protein chignolin

Molecular dynamics simulations of the model protein chignolin with explicit solvent were carried out, in order to analyze the influence of the Berendsen thermostat on the evolution and folding of the peptide. The dependence of the peptide behavior on temperature was tested with the commonly employed thermostat scheme consisting of one thermostat for the protein and another for the solvent. The thermostat coupling time of the protein was increased to infinity, when the protein is not in direct contact with the thermal bath, a situation known as minimally invasive thermostat. In agreement with other works, it was observed that only in the last situation the instantaneous temperature of the model protein obeys a canonical distribution. As for the folding studies, it was shown that, in the applications of the commonly utilized thermostat schemes, the systems are trapped in local minima regions from which it has difficulty escaping. With the minimally invasive thermostat the time that the protein needs to fold was reduced by two to three times. These results show that the obstacles to the evolution of the extended peptide to the folded structure can be overcome when the temperature of the peptide is not directly controlled.

Conformation analysis of a surface loop that controls active site access in the GH11 xylanase A from Bacillus subtilis

Xylanases (EC 3.2.1.8 endo-1,4-glycosyl hydrolase) catalyze the hydrolysis of xylan, an abundant hemicellulose of plant cell walls. Access to the catalytic site of GH11 xylanases is regulated by movement of a short beta-hairpin, the so-called thumb region, which can adopt open or closed conformations. A crystallographic study has shown that the D11F/R122D mutant of the GH11 xylanase A from Bacillus subtilis (BsXA) displays a stable "open" conformation, and here we report a molecular dynamics simulation study comparing this mutant with the native enzyme over a range of temperatures. The mutant open conformation was stable at 300 and 328 K, however it showed a transition to the closed state at 338 K. Analysis of dihedral angles identified thumb region residues Y113 and T123 as key hinge points which determine the open-closed transition at 338 K. Although the D11F/R122D mutations result in a reduction in local inter-intramolecular hydrogen bonding, the global energies of the open and closed conformations in the native enzyme are equivalent, suggesting that the two conformations are equally accessible. These results indicate that the thumb region shows a broader degree of energetically permissible conformations which regulate the access to the active site region. The R122D mutation contributes to the stability of the open conformation, but is not essential for thumb dynamics, i.e., the wild type enzyme can also adapt to the open conformation.

A fragment-based approach for ligand binding affinity and selectivity for the liver X receptor beta

Selective modulation of liver X receptor beta (LXR beta) has been recognized as an important approach to prevent or reverse the atherosclerotic process. In the present work, we have developed robust conformation-independent fragment-based quantitative structure-activity and structure-selectivity relationship models for a series of quinolines and cinnolines as potent modulators of the two LXR sub-types. The generated models were then used to predict the potency of an external test set and the predicted values were in good agreement with the experimental results, indicating the potential of the models for untested compounds. The final 2D molecular recognition patterns obtained were integrated to 3D structure-based molecular modeling studies to provide useful insights into the chemical and structural determinants for increased LXR beta binding affinity and selectivity. (C) 2011 Elsevier Inc. All rights reserved.

Microscopic Modeling on complex networks

The field of complex systems is a growing body of knowledge, It can be applied to countless different topics, from physics to computer science, biology, information theory and sociology. The main focus of this work is the use of microscopic models to study the behavior of urban mobility, which characteristics make it a paradigmatic example of complexity. In particular, simulations are used to investigate phase changes in a finite size open Manhattan-like urban road network under different traffic conditions, in search for the parameters to identify phase transitions, equilibrium and non-equilibrium conditions . It is shown how the flow-density macroscopic fundamental diagram of the simulation shows,like real traffic, hysteresis behavior in the transition from the congested phase to the free flow phase, and how the different regimes can be identified studying the statistics of road occupancy.

A parallel community detection algorithm

Complex networks analysis is a very popular topic in computer science. Unfortunately this networks, extracted from different contexts, are usually very large and the analysis may be very complicated: computation of metrics on these structures could be very complex. Among all metrics we analyse the extraction of subnetworks called communities: they are groups of nodes that probably play the same role within the whole structure. Communities extraction is an interesting operation in many different fields (biology, economics,...). In this work we present a parallel community detection algorithm that can operate on networks with huge number of nodes and edges. After an introduction to graph theory and high performance computing, we will explain our design strategies and our implementation. Then, we will show some performance evaluation made on a distributed memory architectures i.e. the supercomputer IBM-BlueGene/Q "Fermi" at the CINECA supercomputing center, Italy, and we will comment our results.