Molecular Dynamics of HIV1-Integrase in Complex with 93del - A Structural Perspective on the Mechanism of Inhibition

HIV1 integrase is an important target for the antiviral therapy. Guanine-rich quadruplex, such as 93del, have been shown to be potent inhibitors of this enzyme and thus representing a new class of antiviral agents. Although X-ray and NMR structures of HIV1 integrase and 93del have been reported, there is no structural information of the complex and the mechanism of inhibition still remains unexplored. A number of computational methods including automated protein-DNA docking and molecular dynamics simulation in explicit solvent were used to model the binding of 93del to HIV1 integrase. Analysis of the dynamic behaviour of the complex using principal components analysis and elastic network modelling techniques allow us to understand how the binding of 93del aptamer and its interactions with key residues affect the intrinsic motions of the catalytic loops by stabilising them in catalytically inactive conformations. Such insights into the structural mechanism of inhibition can aid in improving the design of anti-HIV aptamers.

Exploring statistical and population aspects of network complexity

The characterization and the definition of the complexity of objects is an important but very difficult problem that attracted much interest in many different fields. In this paper we introduce a new measure, called network diversity score (NDS), which allows us to quantify structural properties of networks. We demonstrate numerically that our diversity score is capable of distinguishing ordered, random and complex networks from each other and, hence, allowing us to categorize networks with respect to their structural complexity. We study 16 additional network complexity measures and find that none of these measures has similar good categorization capabilities. In contrast to many other measures suggested so far aiming for a characterization of the structural complexity of networks, our score is different for a variety of reasons. First, our score is multiplicatively composed of four individual scores, each assessing different structural properties of a network. That means our composite score reflects the structural diversity of a network. Second, our score is defined for a population of networks instead of individual networks. We will show that this removes an unwanted ambiguity, inherently present in measures that are based on single networks. In order to apply our measure practically, we provide a statistical estimator for the diversity score, which is based on a finite number of samples.

Regulatory network of lipopolysaccharide O-antigen biosynthesis in Yersinia enterocolitica includes cell envelope-dependent signals

Lipopolysaccharide (LPS) is a glycolipid present in the outer membrane of all Gram-negative bacteria, and it is one of the signature molecules recognized by the receptors of the innate immune system. In addition to its lipid A portion (the endotoxin), its O-chain polysaccharide (the O-antigen) plays a critical role in the bacterium-host interplay and, in a number of bacterial pathogens, it is a virulence factor. We present evidence that, in Yersinia enterocolitica serotype O:8, a complex signalling network regulates O-antigen expression in response to temperature. Northern blotting and reporter fusion analyses indicated that temperature regulates the O-antigen expression at the transcriptional level. Promoter cloning showed that the O-antigen gene cluster contains two transcriptional units under the control of promoters P(wb1) and P(wb2). The activity of both promoters is under temperature regulation and is repressed in bacteria grown at 37 degrees C. We demonstrate that the RosA/RosB efflux pump/potassium antiporter system and Wzz, the O-antigen chain length determinant, are indirectly involved in the regulation mainly affecting the activity of promoter P(wb2). The rosAB transcription, under the control of P(ros), is activated at 37 degrees C, and P(wb2) is repressed through the signals generated by the RosAB system activation, i.e. decreased [K+] and increased [H+]. The wzz transcription is under the control of P(wb2), and we show that, at 37 degrees C, overexpression of Wzz downregulates slightly the P(wb1) and P(wb2) activities and more strongly the P(ros) activity, with the net result that more O-antigen is produced. Finally, we demonstrate that overexpression of Wzz causes membrane stress that activates the CpxAR two-component signal transduction system.

Characteristics of the complex received signal in dynamic body area networks

This paper investigates the characteristics of the complex received signal in body area networks for two environments at the opposite ends of the multipath spectrum at 2.45 GHz. Important attributes of the complex channel such as the Gaussianity of the quadrature components and power imbalance, which form the basis of many popular fading models, are investigated. It is found that in anechoic environments the assumption of Gaussian distributed quadrature components will not always yield a satisfactory fit. Using a complex received signal model which considers a non-isotropic scattered signal contribution along with the presence of an optional dominant signal component, we use an autocorrelation function originally derived for mobile-to-mobile communications to model the temporal behavior of a range of dynamic body area network channels with considerable success. In reverberant environments, it was observed that the real part of the complex autocorrelation function for body area network channels decayed slightly quicker than that expected in traditional land mobile channels. © 2013 IEEE.

Complex organic molecules in protoplanetary disks

Context. Protoplanetary disks are vital objects in star and planet formation, possessing all the material, gas and dust, which may form a planetary system orbiting the new star. Small, simple molecules have traditionally been detected in protoplanetary disks; however, in the ALMA era, we expect the molecular inventory of protoplanetary disks to significantly increase.

Aims. We investigate the synthesis of complex organic molecules (COMs) in protoplanetary disks to put constraints on the achievable chemical complexity and to predict species and transitions which may be observable with ALMA.

Methods. We have coupled a 2D steady-state physical model of a protoplanetary disk around a typical T Tauri star with a large gas-grain chemical network including COMs. We compare the resulting column densities with those derived from observations and perform ray-tracing calculations to predict line spectra. We compare the synthesised line intensities with current observations and determine those COMs which may be observable in nearby objects. We also compare the predicted grain-surface abundances with those derived from cometary comae observations.

Results. We find COMs are efficiently formed in the disk midplane via grain-surface chemical reactions, reaching peak grain-surface fractional abundances similar to 10(-6)-10(-4) that of the H nuclei number density. COMs formed on grain surfaces are returned to the gas phase via non-thermal desorption; however, gas-phase species reach lower fractional abundances than their grain-surface equivalents, similar to 10(-12)-10(-7). Including the irradiation of grain mantle material helps build further complexity in the ice through the replenishment of grain-surface radicals which take part in further grain-surface reactions. There is reasonable agreement with several line transitions of H2CO observed towards T Tauri star-disk systems. There is poor agreement with HC3(N) lines observed towards LkCa 15 and GO Tau and we discuss possible explanations for these discrepancies. The synthesised line intensities for CH3OH are consistent with upper limits determined towards all sources. Our models suggest CH3OH should be readily observable in nearby protoplanetary disks with ALMA; however, detection of more complex species may prove challenging, even with ALMA "Full Science" capabilities. Our grain-surface abundances are consistent with those derived from cometary comae observations providing additional evidence for the hypothesis that comets (and other planetesimals) formed via the coagulation of icy grains in the Sun's natal disk.

Complex organic molecules along the accretion flow in isolated and externally irradiated protoplanetary disks

(Abridged) The birth environment of the Sun will have influenced the conditions in the pre-solar nebula, including the attainable chemical complexity, important for prebiotic chemistry. The formation and distribution of complex organic molecules (COMs) in a disk around a T Tauri star is investigated for two scenarios: (i) an isolated disk, and (ii) a disk irradiated externally by a nearby massive star. The chemistry is calculated along the accretion flow from the outer disk inwards using a comprehensive network. Two simulations are performed, one beginning with complex ices and one with simple ices only. For the isolated disk, COMs are transported without major alteration into the inner disk where they thermally desorb into the gas reaching an abundance representative of the initial assumed ice abundance. For simple ices, COMs efficiently form on grain surfaces under the conditions in the outer disk. Gas-phase COMs are released into the molecular layer via photodesorption. For the irradiated disk, complex ices are also transported inwards; however, they undergo thermal processing caused by the warmer conditions in the irradiated disk which tends to reduce their abundance along the accretion flow. For simple ices, grain-surface chemistry cannot synthesise COMs in the outer disk because the necessary grain-surface radicals, which tend to be particularly volatile, are not sufficiently abundant on the grain surfaces. Gas-phase COMs are formed in the inner region of the irradiated disk via gas-phase chemistry induced by the desorption of strongly bound molecules such as methanol; hence, the abundances are not representative of the initial molecular abundances injected into the outer disk. These results suggest that the composition of comets formed in isolated disks may differ from those formed in externally irradiated disks with the latter composed of more simple ices.

Genome-wide characterization reveals complex interplay between TP53 and TP63 in response to genotoxic stress

In response to genotoxic stress the TP53 tumour suppressor activates target gene expression to induce cell cycle arrest or apoptosis depending on the extent of DNA damage. These canonical activities can be repressed by TP63 in normal stratifying epithelia to maintain proliferative capacity or drive proliferation of squamous cell carcinomas, where TP63 is frequently overexpressed/amplified. Here we use ChIP-sequencing, integrated with microarray analysis, to define the genome-wide interplay between TP53 and TP63 in response to genotoxic stress in normal cells. We reveal that TP53 and TP63 bind to overlapping, but distinct cistromes of sites through utilization of distinctive consensus motifs and that TP53 is constitutively bound to a number of sites. We demonstrate that cisplatin and adriamycin elicit distinct effects on TP53 and TP63 binding events, through which TP53 can induce or repress transcription of an extensive network of genes by direct binding and/or modulation of TP63 activity. Collectively, this results in a global TP53-dependent repression of cell cycle progression, mitosis and DNA damage repair concomitant with activation of anti-proliferative and pro-apoptotic canonical target genes. Further analyses reveal that in the absence of genotoxic stress TP63 plays an important role in maintaining expression of DNA repair genes, loss of which results in defective repair.

Functional and genetic analysis of the colon cancer network

Cancer is a complex disease that has proven to be difficult to understand on the single-gene level. For this reason a functional elucidation needs to take interactions among genes on a systems-level into account. In this study, we infer a colon cancer network from a large-scale gene expression data set by using the method BC3Net. We provide a structural and a functional analysis of this network and also connect its molecular interaction structure with the chromosomal locations of the genes enabling the definition of cis- and trans-interactions. Furthermore, we investigate the interaction of genes that can be found in close neighborhoods on the chromosomes to gain insight into regulatory mechanisms. To our knowledge this is the first study analyzing the genome-scale colon cancer network.

Artificial Neural Network for Compositional Ionic Liquid Viscosity Prediction

Being a new generation of green solvents and high-tech reaction media of the future, ionic liquids have increasingly attracted much attention. Of particular interest in this context are room temperature ionic liquids (in short as ILs in this paper). Due to the relatively high viscosity, ILs is expected to be used in the form of solvent diluted mixture with reduced viscosity in industrial application, where predicting the viscosity of IL mixture has been an important research issue. Different IL mixture and many modelling approaches have been investigated. The objective of this study is to provide an alternative model approach using soft computing technique, i.e., artificial neural network (ANN) model, to predict the compositional viscosity of binary mixtures of ILs [C _n-mim][NTf ₂] with n=4, 6, 8, 10 in methanol and ethanol over the entire range of molar fraction at a broad range of temperatures from T=293.0-328.0K. The results show that the proposed ANN model provides alternative way to predict compositional viscosity successfully with highly improved accuracy and also show its potential to be extensively utilized to predict compositional viscosity taking account of IL alkyl chain length, as well as temperature and compositions simultaneously, i.e., more complex intermolecular interactions between components in which it would be hard or impossible to establish the analytical model. This illustrates the potential application of ANN in the case that the physical and thermodynamic properties are highly non-linear or too complex. © 2012 Copyright the authors.

Artificial neural network model to predict compositional viscosity over a broad range of temperatures

The objective of this study is to provide an alternative model approach, i.e., artificial neural network (ANN) model, to predict the compositional viscosity of binary mixtures of room temperature ionic liquids (in short as ILs) [C _n-mim] [NTf ₂] with n=4, 6, 8, 10 in methanol and ethanol over the entire range of molar fraction at a broad range of temperatures from T=293.0328.0K. The results show that the proposed ANN model provides alternative way to predict compositional viscosity successfully with highly improved accuracy and also show its potential to be extensively utilized to predict compositional viscosity over a wide range of temperatures and more complex viscosity compositions, i.e., more complex intermolecular interactions between components in which it would be hard or impossible to establish the analytical model. © 2010 IEEE.

Stability in a Network Economy: The Role of Institutions

We consider an economy in which agents are embedded in a network of potential value-generating relationships. Agents are assumed to be able to participate in three types of economic interactions: Autarkic self-provision; bilateral interaction; and multilateral collaboration through endogenously provided platforms.
We introduce two stability concepts and provide sufficient and necessary conditions on the network structure that guarantee existence, in cases of the absence of externalities, link-based externalities and crowding externalities. We show that institutional arrangements based on socioeconomic roles and leadership guarantee stability. In particular, the stability of more complex economic outcomes requires more strict and complex institutional rules to govern economic interactions. We investigate strict social hierarchies, tiered leadership structures and global market places.

“Paths for Action”: Leadership Theory and Practice in Complex Public Sector Systems

The nature and challenges of public sector leadership and management are examined in four case studies of project management in complex metropolitan environments. The cases selected by the authors as representative of contextual factors affecting decision-making processes and project outcomes. Drawing on recent theoretical work on complex leadership approaches (Uhl-Bein et al 2007, Hazy 2008, Lichtenstein & Plowman 2009), the authors assess leadership practices enacted and the circumstances that influence these practices. Leadership types theorized by Uhl-Bein et al (2007) are identified operating at different levels and across networks, with contextual factors outlined. The article concludes with a framework for leadership practice and management identifying network facilitation and complexity friendly tools as a practice within complex public sector systems.