A Ligand predication tool based on modeling and reasoning with imprecise probabilistic knowledge

Ligand prediction has been driven by a fundamental desire to understand more about how biomolecules recognize their ligands and by the commercial imperative to develop new drugs. Most of the current available software systems are very complex and time-consuming to use. Therefore, developing simple and efficient tools to perform initial screening of interesting compounds is an appealing idea. In this paper, we introduce our tool for very rapid screening for likely ligands (either substrates or inhibitors) based on reasoning with imprecise probabilistic knowledge elicited from past experiments. Probabilistic knowledge is input to the system via a user-friendly interface showing a base compound structure. A prediction of whether a particular compound is a substrate is queried against the acquired probabilistic knowledge base and a probability is returned as an indication of the prediction. This tool will be particularly useful in situations where a number of similar compounds have been screened experimentally, but information is not available for all possible members of that group of compounds. We use two case studies to demonstrate how to use the tool.

Electron-impact excitation of Ni II: Collision strengths and effective collision strengths for low lying fine-structure forbidden transitions

Context. Considerable demand exists for electron excitation data for Ni ii, since lines from this abundant ion are observed in a wide variety of laboratory and astrophysical spectra. The accurate theoretical determination of these data can present a significant challenge however, due to complications arising from the presence of an open 3d-shell in the description of the target ion. Aims. In this work we present collision strengths and Maxwellian averaged effective collision strengths for the electron-impact ex- citation of Ni ii. Attention is concentrated on the 153 forbidden fine-structure transitions between the energetically lowest 18 levels of Ni ii. Effective collision strengths have been evaluated at 27 individual electron temperatures ranging from 30–100 000 K. To our knowledge this is the most extensive theoretical collisional study carried out on this ion to date.Methods. The parallel R-matrix package RMATRX II has recently been extended to allow for the inclusion of relativistic effects. This suite of codes has been utilised in the present work in conjunction with PSTGF to evaluate collision strengths and effective collision strengths for all of the low-lying forbidden fine-structure transitions. The following basis configurations were included in the target model – 3d9 , 3d8 4s, 3d8 4p, 3d7 4s2 and 3d7 4s4p – giving rise to a sophisticated 295 j j-level, 1930 coupled channel scattering problem. Results. Comprehensive comparisons are made between the present collisional data and those obtained from earlier theoretical evaluations. While the effective collision strengths agree well for some transitions, significant discrepancies exist for others.

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

Predicting community responses to perturbations in the face of imperfect knowledge and network complexity

How best to predict the effects of perturbations to ecological communities has been a long-standing goal for both applied and basic ecology. This quest has recently been revived by new empirical data, new analysis methods, and increased computing speed, with the promise that ecologically important insights may be obtainable from a limited knowledge of community interactions. We use empirically based and simulated networks of varying size and connectance to assess two limitations to predicting perturbation responses in multispecies communities: (1) the inaccuracy by which species interaction strengths are empirically quantified and (2) the indeterminacy of species responses due to indirect effects associated with network size and structure. We find that even modest levels of species richness and connectance (similar to 25 pairwise interactions) impose high requirements for interaction strength estimates because system indeterminacy rapidly overwhelms predictive insights. Nevertheless, even poorly estimated interaction strengths provide greater average predictive certainty than an approach that uses only the sign of each interaction. Our simulations provide guidance in dealing with the trade-offs involved in maximizing the utility of network approaches for predicting dynamics in multispecies communities.

Anatomy and physiology of the human eye: effects of mucopolysaccharidoses disease on structure and function - a review

P>The current paper provides an overview of current knowledge on the structure and function of the eye. It describes in depth the different parts of the eye that are involved in the ocular manifestations seen in the mucopolysaccharidoses (MPS). The MPS are a group of rare inheritable lysosomal storage disorders characterized by the accumulation of glycosaminoglycans (GAGs) in cells and tissues all over the body, leading to widespread tissue and organ dysfunction. GAGs also tend to accumulate in several tissues of the eye, leading to various ocular manifestations affecting both the anterior (cornea, conjunctiva) and the posterior parts (retina, sclera, optic nerve) of the eye.

Unraveling the Structure and Function of G Protein-Coupled Receptors Through NMR Spectroscopy

G protein-coupled receptors (GPCRs) are a large superfamily of signaling proteins expressed on the plasma membrane. They are involved in a wide range of physiological processes and, therefore, are exploited as drug targets in a multitude of therapeutic areas. In this extent, knowledge of structural and functional properties of GPCRs may greatly facilitate rational design of modulator compounds. Solution and solid-state nuclear magnetic resonance (NMR) spectroscopy represents a powerful method to gather atomistic insights into protein structure and dynamics. In spite of the difficulties inherent the solution of the structure of membrane proteins through NMR, these methods have been successfully applied, sometimes in combination with molecular modeling, to the determination of the structure of GPCR fragments, the mapping of receptor-ligand interactions, and the study of the conformational changes associated with the activation of the receptors. In this review, we provide a summary of the NMR contributions to the study of the structure and function of GPCRs, also in light of the published crystal structures.

Organizational structure and the periphery of the gene regulatory network in B-cell lymphoma

Background:
The physical periphery of a biological cell is mainly described by signaling pathways which are triggered by transmembrane proteins and receptors that are sentinels to control the whole gene regulatory network of a cell. However, our current knowledge about the gene regulatory mechanisms that are governed by extracellular signals is severely limited.Results: The purpose of this paper is three fold. First, we infer a gene regulatory network from a large-scale B-cell lymphoma expression data set using the C3NET algorithm. Second, we provide a functional and structural analysis of the largest connected component of this network, revealing that this network component corresponds to the peripheral region of a cell. Third, we analyze the hierarchical organization of network components of the whole inferred B-cell gene regulatory network by introducing a new approach which exploits the variability within the data as well as the inferential characteristics of C3NET. As a result, we find a functional bisection of the network corresponding to different cellular components.

Conclusions:
Overall, our study allows to highlight the peripheral gene regulatory network of B-cells and shows that it is centered around hub transmembrane proteins located at the physical periphery of the cell. In addition, we identify a variety of novel pathological transmembrane proteins such as ion channel complexes and signaling receptors in B-cell lymphoma. © 2012 Simoes et al.; licensee BioMed Central Ltd.

The phylogeny, structure and function of trematode cysteine proteases, with particular emphasis on the Fasciola hepatica cathepsin L family

Helminth parasites (nematodes, flatworms and cestodes) infect over 1 billion of the world's population causing high morbidity and mortality. The large tissue-dwelling worms express papain-like cysteine peptidases, termed cathepsins that play important roles in virulence including host entry, tissue migration and the suppression of host immune responses. Much of our knowledge of helminth cathepsins comes from studies using flatworms or trematode (fluke) parasites. The developmentally-regulated expression of these proteases correlates with the passage of parasites through host tissues and their encounters with different host macromolecules. Recent phylogenetic, biochemical and structural studies indicate that trematode cathepsins exhibit overlapping but distinct substrate specificities due to divergence within the protease active site. Here we provide an overview of the evolution, biochemistry and structure of these important enzymes and highlight how recent advances in proteomics and gene silencing techniques are allowing researchers to probe their biological functions. We focus mainly on members of the cathepsin L gene family of the animal and human pathogen, Fasciola hepatica, because of our deep understanding of their function, biochemistry and structure.

Photosynthetic pigments in soils from northern Victoria Land (continental Antarctica) as proxies for soil algal community structure and function

Although soil algae are among the main primary producers in most terrestrial ecosystems of continental Antarctica, there are very few quantitative studies on their relative proportion in the main algal groups and on how their distribution is affected by biotic and abiotic factors. Such knowledge is essential for understanding the functioning of Antarctic terrestrial ecosystems. We therefore analyzed biological soil crusts from northern Victoria Land to determine their pH, electrical conductivity (EC) water content (W), total and organic C (TC and TOC) and total N (TN) contents, and the presence and abundance of photosynthetic pigments. In particular, the latter were tested as proxies for biomass and coarse-resolution community structure. Soil samples were collected from five sites with known soil algal communities and the distribution of pigments was shown to reflect differences in the relative proportions of Chlorophyta, Cyanophyta and Bacillariophyta in these sites. Multivariate and univariate models strongly indicated that almost all soil variables (EC, W, TOC and TN) were important environmental correlates of pigment distribution. However, a significant amount of variation is independent of these soil variables and may be ascribed to local variability such as changes in microclimate at varying spatial and temporal scales. There are at least five possible sources of local variation: pigment preservation, temporal variations in water availability, temporal and spatial interactions among environmental and biological components, the local-scale patchiness of organism distribution, and biotic interactions. (C) 2009 Elsevier Ltd. All rights reserved.

Threats and knowledge gaps for ecosystem services provided by kelp forests: a northeast Atlantic perspective.

Kelp forests along temperate and polar coastlines represent some of most diverse and productive habitats on the Earth. Here, we synthesize information from >60 years of research on the structure and functioning of kelp forest habitats in European waters, with particular emphasis on the coasts of UK and Ireland, which represents an important biogeographic transition zone that is subjected to multiple threats and stressors. We collated existing data on kelp distribution and abundance and reanalyzed these data to describe the structure of kelp forests along a spatial gradient spanning more than 10° of latitude. We then examined ecological goods and services provided by kelp forests, including elevated secondary production, nutrient cycling, energy capture and flow, coastal defense, direct applications, and biodiversity repositories, before discussing current and future threats posed to kelp forests and identifying key knowledge gaps. Recent evidence unequivocally demonstrates that the structure of kelp forests in the NE Atlantic is changing in response to climate- and non-climate-related stressors, which will have major implications for the structure and functioning of coastal ecosystems. However, kelp-dominated habitats along much of the NE Atlantic coastline have been chronically understudied over recent decades in comparison with other regions such as Australasia and North America. The paucity of field-based research currently impedes our ability to conserve and manage these important ecosystems. Targeted observational and experimental research conducted over large spatial and temporal scales is urgently needed to address these knowledge gaps.

A latent feature analysis of the neural representation of conceptual knowledge

Bayesian probabilistic analysis offers a new approach to characterize semantic representations by inferring the most likely feature structure directly from the patterns of brain activity. In this study, infinite latent feature models [1] are used to recover the semantic features that give rise to the brain activation vectors when people think about properties associated with 60 concrete concepts. The semantic features recovered by ILFM are consistent with the human ratings of the shelter, manipulation, and eating factors that were recovered by a previous factor analysis. Furthermore, different areas of the brain encode different perceptual and conceptual features. This neurally-inspired semantic representation is consistent with some existing conjectures regarding the role of different brain areas in processing different semantic and perceptual properties. © 2012 Springer-Verlag.

Giving structure to the biofilm matrix: an overview of individual strategies and emerging common themes

Biofilms are communities of microbial cells that underpin diverse processes including sewage bioremediation, plant growth promotion, chronic infections and industrial biofouling. The cells resident in the biofilm are encased within a self-produced exopolymeric matrix that commonly comprises lipids, proteins that frequently exhibit amyloid-like properties, eDNA and exopolysaccharides. This matrix fulfils a variety of functions for the community, from providing structural rigidity and protection from the external environment to controlling gene regulation and nutrient adsorption. Critical to the development of novel strategies to control biofilm infections, or the capability to capitalize on the power of biofilm formation for industrial and biotechnological uses, is an in-depth knowledge of the biofilm matrix. This is with respect to the structure of the individual components, the nature of the interactions between the molecules and the three-dimensional spatial organization. We highlight recent advances in the understanding of the structural and functional role that carbohydrates and proteins play within the biofilm matrix to provide three-dimensional architectural integrity and functionality to the biofilm community. We highlight, where relevant, experimental techniques that are allowing the boundaries of our understanding of the biofilm matrix to be extended using Escherichia coli, Staphylococcus aureus, Vibrio cholerae, and Bacillus subtilis as exemplars.

Genetic structure of the lumpfish Cyclopterus lumpus across the North Atlantic

Lumpfish, or lumpsucker, Cyclopterus lumpus (Linnaeus, 1758) is widely distributed in the North Atlantic Ocean. It has a considerable economic value and substantial fisheries occur in several North Atlantic regions owing to the use of its fully ripe internal egg masses in the ovaries as an alternative to sturgeon caviar. Despite being intensively fished in several locations, biological knowledge is limited and no genetic structure information is available. In this study, the stock structure of C. lumpus was investigated across the North Atlantic using ten microsatellite loci. Out of ten loci, two exhibited higher level of differentiation but their inclusion/ exclusion from the analyses did not drastically change the observed genetic pattern. A total of three distinct genetic groups were detected: Maine-Canada-Greenland, Iceland-Norway and Baltic Sea. These results, discussed in terms of origin of differentiation, gene flow, and selection, showed that gene flow was rather limited among the detected groups, and also between Greenland and Maine-Canada.

Monitoring of a novel FlexiArchTM bridge system to investigate soil-structure interaction

Masonry arch bridges are one of the oldest forms of bridge construction and have been around for thousands of years. Brick and stone arch bridges have proven to be highly durable as most of them have remained serviceable after hundreds of years. In contrast, many bridges built of modern materials have required extensive repair and strengthening after being in service for a relatively short part of their design life. This paper describes the structural monitoring of a novel flexible concrete arch known as: FlexiArchTM. This is a bridge system that can be transported as a flat-pack system to form an arch in-situ by the use of a flexible polymeric membrane. The system has been developed under a Knowledge Transfer Partnership between Queen’s University Belfast (QUB) and Macrete Ltd. Tievenameena Bridge in Northern Ireland was a replacement bridge for the Northern Ireland Roads Service and was monitored under different axle loadings using a range of sensors including discrete fiber optic Bragg gratings to measure the change in strain in the arch ring under live loading. This paper discusses the results of a laboratory model study carried out at QUB. A scaled arch system was loaded with a simulated moving axle. Various techniques were used to monitor the arch under the moving axle load with particular emphasis on the interaction of the arch ring and engineered backfill.

Ocean bottom seismic noise : applications for the crust knowledge, interaction ocean-atmosphere and instrumental behaviour

Tese de doutoramento, Ciências Geofísicas e da Geoinformação (Geofisíca), Universidade de Lisboa, Faculdade de Ciências, 2014