The structural information content of chemical networks

We present an information-theoretic method to measure the structural information content of networks and apply it to chemical graphs. As a result, we find that our entropy measure is more general than classical information indices known in mathematical and computational chemistry. Further, we demonstrate that our measure reflects the essence of molecular branching meaningfully by determining the structural information content of some chemical graphs numerically.

Structural information content of networks: Graph entropy based on local vertex functionals

In this paper we define the structural information content of graphs as their corresponding graph entropy. This definition is based on local vertex functionals obtained by calculating-spheres via the algorithm of Dijkstra. We prove that the graph entropy and, hence, the local vertex functionals can be computed with polynomial time complexity enabling the application of our measure for large graphs. In this paper we present numerical results for the graph entropy of chemical graphs and discuss resulting properties. (C) 2007 Elsevier Ltd. All rights reserved.

Rapid identification of precursor cDNAs encoding five structural classes of antimicrobial peptides from pickerel frog (Rana palustris) skin secretion by single step “shotgun” cloning.

The skin secretion of the North American pickerel frog (Rana palustris) has long been known to have pronounced noxious/toxic properties and to be highly effective in defence against predators and against other sympatric amphibians. As it consists largely of a complex mixture of peptides, it has been subjected to systematic peptidomic study but there has been little focus on molecular cloning of peptide-encoding cDNAs and by deduction, the biosynthetic precursors that they encode. Here, we demonstrate that the cDNAs encoding the five major structural families of antimicrobial peptides can be elucidated by a single step “shotgun” cloning approach using a cDNA library constructed from the source material of the peptidomic studies—the defensive skin secretion itself. Using a degenerate primer pool designed to a highly conserved nucleic acid sequence 5' to the initiation codon of known antimicrobial peptide precursor transcripts, we amplified cDNA sequences representing five major classes of antimicrobial peptides, such as esculentins, brevinins, ranatuerins, palustrins and temporins. Bioinformatic comparisons of precursor open-reading frames and nucleic acid sequences revealed high degrees of structural similarities between analogous peptides of R. palustris and the Chinese bamboo odorous frog, Rana versabilis. This approach thus constitutes a robust technique that can be used either alone or ideally, in parallel with peptidomic analysis of skin secretion, to rapidly extract primary structural information on amphibian skin secretion peptides and their biosynthetic precursors.

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.

Thermodynamics, structure, and dynamics in room temperature ionic liquids: The case of 1-butyl-3-methyl imidazolium hexafluorophosphate ([bmim][PF6])

A detailed investigation of the phase diagram of 1-butyl-3-methyl imidazolium hexafluorophosphate ([bmim][PF6]) is presented on the basis of a wide set of experimental data accessing thermodynamic, structural, and dynamical properties of this important room temperature ionic liquid (RTIL). The combination of quasi adiabatic, continuous calorimetry, wide angle neutron and X-ray diffraction, and quasi elastic neutron scattering allows the exploration of many novel features of this material. Thermodynamic and microscopic structural information is derived on both glassy and crystalline states and compared with results that recently appeared in the literature allowing direct information to be obtained on the existence of two crystalline phases that were not previously characterized and confirming the view that RTILs show a substantial degree of order (even in their amorphous states), which resembles the crystalline order. We highlight a strong connection between structure and dynamics, showing the existence of three temperature ranges in the glassy state across which both the spatial correlation and the dynamics change. The complex crystalline polymorphism in [bmim][PF6] also is investigated; we compare our findings with the corresponding findings for similar RTILs. These results provide a strong experimental basis for the exploration of the features of the phase diagram of RTILs and for the further study of longer alkyl chain salts.

Evaluation of Gas Solubility Prediction in Ionic Liquids using COSMOthermX

As the range of available ionic liquids increases, methods by which important engineering parameters such as gas solubilities can be estimated from simple structural information become ever more desirable. COSMO-based thermodynamic models, such as that used by COSMOthermX, allow the determination of such data for pure and mixed component systems. Herein, we evaluate the predictive capability of COSMOthermX through a comparison with literature data obtained from the IUPAC database which contains data for 15 gases in 27 ionic liquids, To determine any effect inherent to ionic liquids, gas solubility predictions were first performed for selected molecular solvents at constant temperature and pressure. Further estimations of gas solubility at temperatures ranging from (278 to 368) K at 0.1 MPa in water were performed for 14 gases. The Study has demonstrated that COSMOthermX is capable of predicting, qualitatively, gas solubilities in ionic liquids and, hence, reducing the amount of unnecessary experimental measurements prior to specific applications using ionic liquids.

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.

Inferring the conservative causal core of gene regulatory networks

Background
Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically.

Results
In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently.

Conclusions
For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.

Binding modes of diketo-acid inhibitors of HIV-1 integrase: A comparative molecular dynamics simulation study

HIV-1 integrase (IN) has become an attractive target since drug resistance against HIV-1 reverse transcriptase (RT) and protease (PR) has appeared. Diketo acid (DKA) inhibitors are potent and selective inhibitors of HIV-1 IN: however the action mechanism is not well understood. Here, to study the inhibition mechanism of DKAs we performed 10 ns comparative molecular dynamics simulations on HIV-1 IN bound with three most representative DMA inhibitors: Shionogi inhibitor, S-1360 and two Merck inhibitors L-731,988 and L-708,906. Our simulations show that the acidic part of S-1360 formed salt bridge and cation-pi interactions with Lys159. In addition, the catalytic Glu152 in S-1360 was pushed away from the active site to form an ion-pair interaction with Arg199. The Merck inhibitors can maintain either one or both of these ion-pair interaction features. The difference in potencies of the DMA inhibitors is thus attributed to the different binding modes at the catalytic site. Such structural information at atomic level, not only demonstrates the action modes of DMA inhibitors but also provides a novel starting point for structural-based design of HIV-1 IN inhibitors.

THE FMRFAMIDE-LIKE NEUROPEPTIDE AF2 (ASCARIS-SUUM) IS PRESENT IN THE FREE-LIVING NEMATODE, PANAGRELLUS-REDIVIVUS (NEMATODA, RHABDITIDA)

Available primary structural information suggests that the FMRFamide-related peptides (FaRPs) from parasitic and free-living nematodes are different, and that free-living forms may not represent appropriate models for the study of the neurochemistry of parasitic forms in the laboratory. However, here we report the isolation and unequivocal identification of AF2 (originally isolated from the parasite, Ascaris suum) from acidified alcoholic extracts of the free-living species, Panagrellus redivivus. While reverse-phase HPLC analysis of extracts revealed FMRFamide-immunoreactivity to be highly heterogeneous, AF2 was the predominant FMRFamide-immunoreactive peptide present (at least 26 pmol/g wet weight of worms). This peptide was also the major immunoreactant identified by an antiserum raised to the conserved C-terminal hexapeptide amide of mammalian pancreatic polypeptide (PP), which has been used previously to isolate neuropeptide F (NPF). These observations were confirmed by radioimmunoassay and chromatographic fractionation of an acidified alcoholic extract of A. suum heads. The FMRFamide-related peptides present in a nematode extract may be highly dependent on the extraction medium employed, and these data would suggest that this complement of neuropeptides may not be as different between parasitic and free-living nematodes as initial studies have suggested. Finally, all of the evidence suggests that NPF is not present in nematodes and that the PP-immunoreactant previously demonstrated immunochemically is probably AF2.

The typology of Irish hard rock aquifers based on an integrated hydrogeological and geophysical approach

Groundwater flow in hard-rock aquifers is strongly controlled by the characteristics and distribution of structural heterogeneity. A methodology for catchment-scale characterisation is presented, based on the integration of complementary, multi-scale hydrogeological, geophysical and geological approaches. This was applied to three contrasting catchments underlain by metamorphic rocks in the northern parts of Ireland (Republic of Ireland and Northern Ireland, UK). Cross-validated surface and borehole geophysical investigations confirm the discontinuous overburden, lithological compartmentalisation of the bedrock and important spatial variations of the weathered bedrock profiles at macro-scale. Fracture analysis suggests that the recent (Alpine) tectonic fabric exerts strong control on the internal aquifer structure at meso-scale, which is likely to impact on the anisotropy of aquifer properties. The combination of the interpretation of depth-specific hydraulic-test data with the structural information provided by geophysical tests allows characterisation of the hydrodynamic properties of the identified aquifer units. Regionally, the distribution of hydraulic conductivities can be described by inverse power laws specific to the aquifer litho-type. Observed groundwater flow directions reflect this multi-scale structure. The proposed integrated approach applies widely available investigative tools to identify key dominant structures controlling groundwater flow, characterising the aquifer type for each catchment and resolving the spatial distribution of relevant aquifer units and associated hydrodynamic parameters.

Non-parametric nonlinear system identification: A data-driven orthogonal basis function approach

In this paper, a data driven orthogonal basis function approach is proposed for non-parametric FIR nonlinear system identification. The basis functions are not fixed a priori and match the structure of the unknown system automatically. This eliminates the problem of blindly choosing the basis functions without a priori structural information. Further, based on the proposed basis functions, approaches are proposed for model order determination and regressor selection along with their theoretical justifications. © 2008 IEEE.

Validated ligand binding sites in CCK receptors. Next step: Computer aided design of novel CCK ligands

Computer-aided drug design becomes an important part of G-protein coupled receptors (GPCR) drug discovery process that is applied for improving the efficiency of derivation and optimization of novel ligands. It represents the combination of methods that-use-structural information of a receptor binding site of known ligands to design new ligands. In this report, we give a brief description of ligand binding sites in cholecystokinin and gastrin receptors (CK1R and CCK2R) which were delineated using experimental and computational methods, and then, we show how the validated ligand binding sites can be used to design and improve novel ligands. The translation of the knowledge of ligand-binding sites of different GPCRs to computer-aided design of novel ligands is summarized.

Self-assembly using dendritic building blocks - towards controllable nanomaterials

Dendritic molecules have well defined, three-dimensional branched architectures, and constitute a unique nanoscale toolkit. This review focuses on examples in which individual dendritic molecules are assembled into more complex arrays via non-covalent interactions. In particular, it illustrates how the structural information programmed into the dendritic architecture controls the assembly process, and as a consequence, the properties of the supramolecular structures which are generated. Furthermore, the review emphasises how the use of non-covalent (supramolecular) interactions, provides the assembly process with reversibility, and hence a high degree of control. The review also illustrates how self-assembly offers an ideal approach for amplifying the branching of small, synthetically accessible, relatively inexpensive dendritic systems (e.g. dendrons), into highly branched complex nanoscale assemblies.

The review begins by considering the assembly of dendritic molecules to generate discrete, well-defined supramolecular assemblies. The variety of possible assembled structures is illustrated, and the ability of an assembled structure to encapsulate a templating unit is described. The ability of both organic and inorganic building blocks to direct the assembly process is discussed. The review then describes larger discrete assemblies of dendritic molecules, which do not exist as a single well-defined species, but instead exist as statistical distributions. For example, assembly around nanoparticles, the assembly of amphiphilic dendrons and the assembly of dendritic systems in the presence of DNA will all be discussed. Finally, the review examines dendritic molecules, which assemble or order themselves into extended arrays. Such systems extend beyond the nanoscale into the microscale or even the macroscale domain, exhibiting a wide range of different architectures. The ability of these assemblies to act as gel-phase or liquid crystalline materials will be considered.

Taken as a whole, this review emphasises the control and tunability that underpins the assembly of nanomaterials using dendritic building blocks, and furthermore highlights the potential future applications of these assemblies at the interfaces between chemistry, biology and materials science. 

VIEWING LEED PATTERNS AS ELECTRON HOLOGRAMS

It is shown theoretically that LEED patterns from ordered overlayer systems bear a strong relationship to electron holograms, and that phase information is recorded in the diffraction intensities. It is, therefore, possible to obtain structural information by direct holographic inversion from conventional LEED I-V spectra.