Structural interpretation of protein-protein interaction network

Background Currently a huge amount of protein-protein interaction data is available from high throughput experimental methods. In a large network of protein-protein interactions, groups of proteins can be identified as functional clusters having related functions where a single protein can occur in multiple clusters. However experimental methods are error-prone and thus the interactions in a functional cluster may include false positives or there may be unreported interactions. Therefore correctly identifying a functional cluster of proteins requires the knowledge of whether any two proteins in a cluster interact, whether an interaction can exclude other interactions, or how strong the affinity between two interacting proteins is. Methods In the present work the yeast protein-protein interaction network is clustered using a spectral clustering method proposed by us in 2006 and the individual clusters are investigated for functional relationships among the member proteins. 3D structural models of the proteins in one cluster have been built – the protein structures are retrieved from the Protein Data Bank or predicted using a comparative modeling approach. A rigid body protein docking method (Cluspro) is used to predict the protein-protein interaction complexes. Binding sites of the docked complexes are characterized by their buried surface areas in the docked complexes, as a measure of the strength of an interaction. Results The clustering method yields functionally coherent clusters. Some of the interactions in a cluster exclude other interactions because of shared binding sites. New interactions among the interacting proteins are uncovered, and thus higher order protein complexes in the cluster are proposed. Also the relative stability of each of the protein complexes in the cluster is reported. Conclusions Although the methods used are computationally expensive and require human intervention and judgment, they can identify the interactions that could occur together or ones that are mutually exclusive. In addition indirect interactions through another intermediate protein can be identified. These theoretical predictions might be useful for crystallographers to select targets for the X-ray crystallographic determination of protein complexes

Protein sequence entropy is closely related to packing density and hydrophobicity

We investigated the correlation between the Shannon information entropy, ‘sequence entropy’, with respect to the local flexibility of native globular proteins as described by inverse packing density. These are determined at each residue position for a total set of 130 query proteins, where sequence entropies are calculated from each set of aligned residues. For the accompanying aggregate set of 130 alignments, a strong linear correlation is observed between the calculated sequence entropy and the corresponding inverse packing density determined at an associated residue position. This region of linearity spans the range of Cα packing densities from 12 to 25 amino acids within a sphere of 9 Å radius. Three different hydrophobicity scales all mimic the behavior of the sequence entropies. This confirms the idea that the ability to accommodate mutations is strongly dependent on the available space and on the propensity for each amino acid type to be buried. Future applications of these types of methods may prove useful in identifying both core and flexible residues within a protein

Structural compliance: A new metric for protein flexibility

Proteins are the active players in performing essential molecular activities throughout biology, and their dynamics has been broadly demonstrated to relate to their mechanisms. The intrinsic fluctuations have often been used to represent their dynamics and then compared to the experimental B-factors. However, proteins do not move in a vacuum and their motions are modulated by solvent that can impose forces on the structure. In this paper, we introduce a new structural concept, which has been called the structural compliance, for the evaluation of the global and local deformability of the protein structure in response to intramolecular and solvent forces. Based on the application of pairwise pulling forces to a protein elastic network, this structural quantity has been computed and sometimes is even found to yield an improved correlation with the experimental B-factors, meaning that it may serve as a better metric for protein flexibility. The inverse of structural compliance, namely the structural stiffness, has also been defined, which shows a clear anticorrelation with the experimental data. Although the present applications are made to proteins, this approach can also be applied to other biomolecular structures such as RNA. This present study considers only elastic network models, but the approach could be applied further to conventional atomic molecular dynamics. Compliance is found to have a slightly better agreement with the experimental B-factors, perhaps reflecting its bias toward the effects of local perturbations, in contrast to mean square fluctuations. The code for calculating protein compliance and stiffness is freely accessible at https://jerniganlab.github.io/Software/PACKMAN/Tutorials/compliance

Graphene formation on SiC substrates

Graphene layers were created on both C and Si faces of semi-insulating, on-axis, 4H- and 6H-SiC substrates. The process was performed under high vacuum (<10-4 mbar) in a commercial chemical vapor deposition SiC reactor. A method for H2 etching the on-axis sub-strates was developed to produce surface steps with heights of 0.5 nm on the Si-face and 1.0 to 1.5 nm on the C-face for each polytype. A process was developed to form graphene on the substrates immediately after H2 etching and Raman spectroscopy of these samples confirmed the formation of graphene. The morphology of the graphene is described. For both faces, the underlying substrate morphology was significantly modified during graphene formation; sur-face steps were up to 15 nm high and the uniform step morphology was sometimes lost. Mo-bilities and sheet carrier concentrations derived from Hall Effect measurements on large area (16 mm square) and small area (2 and 10 um square) samples are presented and shown to compare favorably to recent reports.Comment: European Conference on Silicon Carbide and Related Materials 2008 (ECSCRM '08), 4 pages, 4 figure

The importance of chemosensory clues in Aguaruna tree classification and identification

<p>Abstract</p> <p>Background</p> <p>The ethnobotanical literature still contains few detailed descriptions of the sensory criteria people use for judging membership in taxonomic categories. Olfactory criteria in particular have been explored very little. This paper will describe the importance of odor for woody plant taxonomy and identification among the Aguaruna Jívaro of the northern Peruvian Amazon, focusing on the Aguaruna category <b><it>númi </it></b>(trees excluding palms). Aguaruna informants almost always place trees that they consider to have a similar odor together as <b><it>kumpají </it></b>– 'companions,' a metaphor they use to describe trees that they consider to be related.</p> <p>Methods</p> <p>The research took place in several Aguaruna communities in the upper Marañón region of the Peruvian Amazon. Structured interview data focus on informant criteria for membership in various folk taxa of trees. Informants were also asked to explain what members of each group of related companions had in common. This paper focuses on odor and taste criteria that came to light during these structured interviews. Botanical voucher specimens were collected, wherever possible.</p> <p>Results</p> <p>Of the 182 tree folk genera recorded in this study, 51 (28%) were widely considered to possess a distinctive odor. Thirty nine of those (76%) were said to have odors similar to some other tree, while the other 24% had unique odors. Aguaruna informants very rarely described tree odors in non-botanical terms. Taste was used mostly to describe trees with edible fruits. Trees judged to be related were nearly always in the same botanical family.</p> <p>Conclusion</p> <p>The results of this study illustrate that odor of bark, sap, flowers, fruit and leaves are important clues that help the Aguaruna to judge the relatedness of trees found in their local environment. In contrast, taste appears to play a more limited role. The results suggest a more general ethnobotanical hypothesis that could be tested in other cultural settings: people tend to consider plants with similar odors to be related, but say that plants with unique odors are unrelated to any other plants.</p

Characterization of a POROS\u3csup\u3eTM\u3c/sup\u3e-fumonisin B1 Affinity Column for Isolating Ceramide Synthase from Rat Liver

Fumonisin B1 is a mycotoxin produced by fungi of the genus Fusarium, common pathogens of corn and other grain plants. Toxic effects associated with fumonisin B1 include equine leukoencephalomacia, porcine pulmonary edema, rat renal carcinoma, and murine hepatocellular carcinoma. Increased risk for esophageal cancer in humans has been epidemiologically associated with consumption of corn contaminated with Fusarium, suggesting that fumonisin B1 may be involved. The biological effects of fumonisin B1 exposure result primarily from disruption of de novo sphingolipid biosynthesis via inhibition of ceramide synthase. Exposure of animals or cultured cells to fumonisin B1 results in the characteristic accumulation of sphinganine, a toxic sphingolipid intermediate, concomitant with depletion of essential complex sphingolipids. Ceramide synthase has not been purified to homogeniety and characterized. We prepared crude ceramide synthase from detergent-extracted rat liver homogenates using PEG-precipitation and cation exchange chromatography. Ceramide synthase activity was then sequestered, using fumonisin B1 covalently coupled to POROS-NH particles, and eluted selectively. The observed 119-fold enrichment in specific activity demonstrates the utility of fumonisin-POROS affinity chromatography in the purification of ceramide synthase

Origin of Native Driving Force in Protein Folding

We derive an expression with four adjustable parameters that reproduces well the 20x20 Miyazawa-Jernigan potential matrix extracted from known protein structures. The numerical values of the parameters can be approximately computed from the surface tension of water, water-screened dipole interactions between residues and water and among residues, and average exposures of residues in folded proteins.Comment: LaTeX file, Postscript file; 4 pages, 1 figure (mij.eps), 2 table