Anion–π interactions: CP-corrected vs. standard optimisation,AIM and NBO analyses

The anion–π interactions between Br^? , Cl^? , F^?  and H^?  anions and hexafluorobenzene (HFB), 1,2,4,5-tetracyanobenzene (TCB) and tetracyanopyrazine (TCP) have been studied by standard and counterpoise (CP) corrected methods at HF, B3LYP and MP2/6-31+ + G (d,p) levels of theory. The complexation energies were corrected for basis set superposition error (ΔE _BSSE) and zero point energy (ΔE _BSSE + ZPE). Also, the B3LYP results were corrected by single-point calculation at B3LYP/aug-cc-PVTZ level of theory. Although the CP-corrected method results in higher distances between anions and rings, the standard method gives lower complexation energies. TCP…X^?  series gives higher complexation energies in both CP-corrected and standard methods. Topological analysis of the charge density ρ(r) has been performed by the means of atoms in molecules method on the wave functions obtained at MP2/6-31+ + G (d,p) level of theory. The number and the nature of critical points depend on aromatic ring and anion. Natural bond orbital analysis indicates that n_X → π*_CC and n_X → π*_CN interactions are the most important interactions for TCB (and HFB)…X^?  and TCP…X^?  complexes, respectively.     

Targeted and proteome-wide analysis of metabolite–protein interactions

Understanding the molecular mechanisms of endogenous and environmental metabolites is crucial for basic biology and drug discovery. With the genome, proteome, and metabolome of many organisms being readily available, researchers now have the opportunity to dissect how key metabolites regulate complex cellular pathways in vivo. Nonetheless, characterizing the specific and functional protein targets of key metabolites associated with specific cellular phenotypes remains a major challenge. Innovations in chemical biology are now poised to address this fundamental limitation in physiology and disease. In this review, we highlight recent advances in chemoproteomics for targeted and proteome-wide analysis of metabolite–protein interactions that have enabled the discovery of unpredicted metabolite–protein interactions and facilitated the development of new small molecule therapeutics.     

Hydrogen-bonding interactions in adrenaline–water complexes: DFT and QTAIM studies of structures, properties, and topologies

ωB97XD/6-311++G(d,p) calculations were carried out to investigate the hydrogen-bonding interactions between adrenaline (Ad) and water. Six Ad-H(2)O complexes possessing various types of hydrogen bonds (H-bonds) were characterized in terms of their geometries, energies, vibrational frequencies, and electron-density topology. Natural bond orbital (NBO) and quantum theory of atoms in molecules (QTAIM) analyses were performed to elucidate the nature of the hydrogen-bonding interactions in these complexes. The intramolecular H-bond between the amino and carboxyl oxygen atom of Ad was retained in most of the complexes, and cooperativity between the intra- and intermolecular H-bonds was present in some of the complexes. H-bonds in which hydroxyls of Ad/water acted as proton donors were stronger than other H-bonds. Both hydrogen-bonding interactions and structural deformation play important roles in the relative stabilities of the complexes. The intramolecular H-bond was broken during the formation of the most stable complex, which indicates that Ad tends to break the intramolecular H-bond and form two new intermolecular H-bonds with the first water molecule.     

Aromatic-aromatic interactions: analysis of π-π interactions in interleukins and TNF proteins

Aromatic-aromatic hydrogen bonds are important in many areas of chemistry, biology and materials science. In this study we haveanalyzed the roles played by the π-π interactions in interleukins (ILs) and tumor necrosis factor (TNF) proteins. Majority of π-πinteracting residues are conserved in ILs and TNF proteins. The accessible surface area calculations in these proteins reveal thatthese interactions might be important in stabilizing the inner core regions of these proteins. In addition to π-π interactions, thearomatic residues also form π-networks in ILs and TNF proteins. The results obtained in the present study indicate that π-πinteractions and π-π networks play important roles in the structural stability of ILs and TNF proteins.     

d-matrix – database exploration,visualization and analysis

Background  

Motivated by a biomedical database set up by our group, we aimed to develop a generic database front-end with embedded knowledge discovery and analysis features. A major focus was the human-oriented representation of the data and the enabling of a closed circle of data query, exploration, visualization and analysis.     

Types, evolution and significance of plant – animal interactions

Abstract  Interactions between plants and animals are analyzed starting from the advantages gained by animals and proceeding to those gained exclusively by plants. These interactions are essentially of five types: 1. predation of plants by animals; 2. benevolence of plants towards certain animals to prevent or reduce predation; 3. predation by plants (carnivorous plants); 4. symbiosis and mutualism; 5. seduction and deception of animals by plants for dispersal of plant reproductive structures. All types of plants are preyed on by animals, though from as far back in evolution as algae, certain plant molecules reduce or prevent predation. In the most primitive land plants, other types of interactions beneficial for plants are encountered. More evolved land plants (angiosperms) show all facets of the five types of interaction, whereas in prokaryotic and eukaryotic algae there is only predation and in some cases countermeasures to avoid it. An evolutionary path leading from predation, the original condition, to seduction, deception and carnivory, is also postulated. Keywords Plants, Animals, Predation, Benevolence, Symbiosis, Mutualism, Pollination, Seed dispersal Subject codes: Animal Ecology, Plant Ecology, Evolutionary Biology     

Systems for the detection and analysis of protein–protein interactions

The analysis of protein–protein interactions is important for developing a better understanding of the functional annotations of proteins that are involved in various biochemical reactions in vivo. The discovery that a protein with an unknown function binds to a protein with a known function could provide a significant clue to the cellular pathway concerning the unknown protein. Therefore, information on protein–protein interactions obtained by the comprehensive analysis of all gene products is available for the construction of interactive networks consisting of individual protein–protein interactions, which, in turn, permit elaborate biological phenomena to be understood. Systems for detecting protein–protein interactions in vitro and in vivo have been developed, and have been modified to compensate for limitations. Using these novel approaches, comprehensive and reliable information on protein–protein interactions can be determined. Systems that permit this to be achieved are described in this review.K. Kuroda, M. Kato and J. Mima contributed equally to this work.     

Current trends in endotoxin detection and analysis of endotoxin–protein interactions

Endotoxin is a type of pyrogen that can be found in Gram-negative bacteria. Endotoxin can form a stable interaction with other biomolecules thus making its removal difficult especially during the production of biopharmaceutical drugs. The prevention of endotoxins from contaminating biopharmaceutical products is paramount as endotoxin contamination, even in small quantities, can result in fever, inflammation, sepsis, tissue damage and even lead to death. Highly sensitive and accurate detection of endotoxins are keys in the development of biopharmaceutical products derived from Gram-negative bacteria. It will facilitate the study of the intermolecular interaction of an endotoxin with other biomolecules, hence the selection of appropriate endotoxin removal strategies. Currently, most researchers rely on the conventional LAL-based endotoxin detection method. However, new methods have been and are being developed to overcome the problems associated with the LAL-based method. This review paper highlights the current research trends in endotoxin detection from conventional methods to newly developed biosensors. Additionally, it also provides an overview of the use of electron microscopy, dynamic light scattering (DLS), fluorescence resonance energy transfer (FRET) and docking programs in the endotoxin–protein analysis.     

SpectralNET – an application for spectral graph analysis and visualization

Background  

Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks.     

Genomic analysis of cold-active Colwelliaphage 9A and psychrophilic phage�Chost interactions

The 104 kb genome of cold-active bacteriophage 9A, which replicates in the marine psychrophilic gamma-proteobacterium Colwellia psychrerythraea strain 34H (between ?12 and 8 °C), was sequenced and analyzed to investigate elements of molecular adaptation to low temperature and phage?Chost interactions in the cold. Most characterized ORFs indicated closest similarity to gamma-proteobacteria and their phages, though no single module provided definitive phylogenetic grouping. A subset of primary structural features linked to psychrophily suggested that the majority of annotated phage proteins were not psychrophilic; those that were, primarily serve phage-specific functions and may also contribute to 9A??s restricted temperature range for replication as compared to host. Comparative analyses suggest ribonucleotide reductase genes were acquired laterally from host. Neither restriction modification nor the CRISPR-Cas system appeared to be the predominant phage defense mechanism of Cp34H or other cold-adapted bacteria; we hypothesize that psychrophilic hosts rely more on the use of extracellular polymeric material to block cell surface receptors recognized by phages. The relative dearth of evidence for genome-specific defenses, genetic transfer events or auxiliary metabolic genes suggest that the 9A-Cp34H system may be less tightly coupled than are other genomically characterized marine phage?Chost systems, with possible implications for phage specificity under different environmental conditions.     

Molecular modelling of phthalates – PPARs interactions

Di(2-ethylhexyl) phthalate (DEHP) is the most widely plasticizer for polyvinyl chloride (PVC) that is used in plastic tubes, in medical and paramedical devices as well as in food storage packaging. The toxicological profile of DEHP has been evaluated in a number of experimental animal models and has been extensively documented. Its toxicity is in part linked to the activation of the peroxisome proliferator-activated receptor α (PPAR_α). As a response, an intensive research for a new, biologically inert plasticizer has been initiated. Among the alternative studied, tri(2-ethylhexyl) trimellitate (TEHTM) or trioctyl trimellitate (TOTM) has attracted increasing interest. However, very little information is available on their biological effects. We proceeded to dock TOTM, DEHP and its metabolites in order to identify compounds that are likely to interact with PPAR_α and PPAR_γ binding sites. The results obtained hint that TOTM is not able to bind to PPARs and should therefore be safer than DEHP.     

MolTalk – a programming library for protein structures and structure analysis

Background  

Two of the mostly unsolved but increasingly urgent problems for modern biologists are a) to quickly and easily analyse protein structures and b) to comprehensively mine the wealth of information, which is distributed along with the 3D co-ordinates by the Protein Data Bank (PDB). Tools which address this issue need to be highly flexible and powerful but at the same time must be freely available and easy to learn.     

Ecological hierarchies and self-organisation – Pattern analysis,modelling and process integration across scales

A continuing discussion in applied and theoretical ecology focuses on the relationship of different organisational levels and on how ecological systems interact across scales. We address principal approaches to cope with complex across-level issues in ecology by applying elements of hierarchy theory and the theory of complex adaptive systems. A top-down approach, often characterised by the use of statistical techniques, can be applied to analyse large-scale dynamics and identify constraints exerted on lower levels. Current developments are illustrated with examples from the analysis of within-community spatial patterns and large-scale vegetation patterns. A bottom-up approach allows one to elucidate how interactions of individuals shape dynamics at higher levels in a self-organisation process; e.g., population development and community composition. This may be facilitated by various modelling tools, which provide the distinction between focal levels and resulting properties. For instance, resilience in grassland communities has been analysed with a cellular automaton approach, and the driving forces in rodent population oscillations have been identified with an agent-based model. Both modelling tools illustrate the principles of analysing higher level processes by representing the interactions of basic components.The focus of most ecological investigations on either top-down or bottom-up approaches may not be appropriate, if strong cross-scale relationships predominate. Here, we propose an ‘across-scale-approach’, closely interweaving the inherent potentials of both approaches. This combination of analytical and synthesising approaches will enable ecologists to establish a more coherent access to cross-level interactions in ecological systems.     

Antarctic archaea–virus interactions: metaproteome-led analysis of invasion,evasion and adaptation

Despite knowledge that viruses are abundant in natural ecosystems, there is limited understanding of which viruses infect which hosts, and how both hosts and viruses respond to those interactions—interactions that ultimately shape community structure and dynamics. In Deep Lake, Antarctica, intergenera gene exchange occurs rampantly within the low complexity, haloarchaea-dominated community, strongly balanced by distinctions in niche adaptation which maintain sympatric speciation. By performing metaproteomics for the first time on haloarchaea, genomic variation of S-layer, archaella and other cell surface proteins was linked to mechanisms of infection evasion. CRISPR defense systems were found to be active, with haloarchaea responding to at least eight distinct types of viruses, including those infecting between genera. The role of BREX systems in defending against viruses was also examined. Although evasion and defense were evident, both hosts and viruses also may benefit from viruses carrying and expressing host genes, thereby potentially enhancing genetic variation and phenotypic differences within populations. The data point to a complex inter-play leading to a dynamic optimization of host–virus interactions. This comprehensive overview was achieved only through the integration of results from metaproteomics, genomics and metagenomics.     

Refinement of human lysozyme at 1.5 Å resolution analysis of non-bonded and hydrogen-bond interactions

The structure of human lysozyme has been crystallographically refined at 1.5 Å resolution by difference map and restrained least-squares procedures to an R factor of 0.187. A comprehensive analysis of the non-bonded and hydrogen-bonded contacts in the lysozyme molecule, which were not restrained, revealed by the refinement has been carried out. The non-bonded CC contacts begin at ~3.45 Å, and the shorter contacts are dominated, as expected, by interactions between trigonal and tetrahedral carbon atoms. The CO contact distances have a “foot” at 3.05 Å. The CN distance plot shows a significant peak at 3.25 Å, which results from close contact between peptide NHs and carbonyl carbons involved in N_iC′_{i ? 2} interactions in α-helices and reverse turns. The distances involving sulphur atoms discriminate SC trigonal interactions at 3.4 to 3.6 Å from SC tetrahedral interactions at 3.7 Å. All these types of non-bonded interactions show minimum distances close to standard van der Waals' separations.Analysis of hydrogen-bond distances has been carried out by using standard geometry to place hydrogen atoms and measuring the XHO distances. On this basis, there are 130 intramolecular hydrogens: 111 NHO bonds, of which 69 are between main-chain atoms, 13 between side-chain atoms and 29 between mainchain and side-chain atoms. If a cluster of four well-defined internal water molecules is included in the protein structure, there is a total of 19 OHO hydrogen bonds. The mean NO, NHO distances and HN?O angles are 2.96 ± 0.17 Å, 2.05 ± 0.18 Å and 18.5 ± 9.6 °, and the mean OO, OHO distances and HÔO angles are 2.83 ± 0.19 Å, 1.98 ± 0.26 Å and 23.8 ± 13.4 °. The distances agree well with standard values, although the hydrogen bonds are consistently more non-linear than in equivalent small molecules. An analysis of the hydrogen-bond angles at the receptor atom indicates that the α-helix, β-sheet and reverse turn have characteristic angular values. A detailed analysis of the regularity of the α-helices and reverse turns shows small but consistent differences between the α-helices in lysozyme and the current standard model, which may now need revision. Of the 21 reverse turns that include a hydrogen bond, the conformations of 19 agree very closely with four of the five standard types. We conclude that the restrained least-squares method of refinement has been validated by these analyses.