Matching–centrality decomposition and the forecasting of new links in networks

Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching–centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network.     

PCS-based structure determination of protein–protein complexes

A simple and fast nuclear magnetic resonance method for docking proteins using pseudo-contact shift (PCS) and ¹H^N/¹⁵N chemical shift perturbation is presented. PCS is induced by a paramagnetic lanthanide ion that is attached to a target protein using a lanthanide binding peptide tag anchored at two points. PCS provides long-range (~40 Å) distance and angular restraints between the lanthanide ion and the observed nuclei, while the ¹H^N/¹⁵N chemical shift perturbation data provide loose contact-surface information. The usefulness of this method was demonstrated through the structure determination of the p62 PB1-PB1 complex, which forms a front-to-back 20 kDa homo-oligomer. As p62 PB1 does not intrinsically bind metal ions, the lanthanide binding peptide tag was attached to one subunit of the dimer at two anchoring points. Each monomer was treated as a rigid body and was docked based on the backbone PCS and backbone chemical shift perturbation data. Unlike NOE-based structural determination, this method only requires resonance assignments of the backbone ¹H^N/¹⁵N signals and the PCS data obtained from several sets of two-dimensional ¹⁵N-heteronuclear single quantum coherence spectra, thus facilitating rapid structure determination of the protein–protein complex.     

Protein–protein interaction networks studies and importance of 3D structure knowledge

Protein–protein interaction networks (PPINs) are a powerful tool to study biological processes in living cells. In this review, we present the progress of PPIN studies from abstract to more detailed representations. We will focus on 3D interactome networks, which offer detailed information at the atomic level. This information can be exploited in understanding not only the underlying cellular mechanisms, but also how human variants and disease-causing mutations affect protein functions and complexes’ stability. Recent studies have used structural information on PPINs to also understand the molecular mechanisms of binding partner selection. We will address the challenges in generating 3D PPINs due to the restricted number of solved protein structures. Finally, some of the current use of 3D PPINs will be discussed, highlighting their contribution to the studies in genotype–phenotype relationships and in the optimization of targeted studies to design novel chemical compounds for medical treatments.     

The protein–protein interaction network of the human Sirtuin family

Protein–protein interaction networks are useful for studying human diseases and to look for possible health care through a holistic approach. Networks are playing an increasing and important role in the understanding of physiological processes such as homeostasis, signaling, spatial and temporal organizations, and pathological conditions. In this article we show the complex system of interactions determined by human Sirtuins (Sirt) largely involved in many metabolic processes as well as in different diseases. The Sirtuin family consists of seven homologous Sirt-s having structurally similar cores but different terminal segments, being rather variable in length and/or intrinsically disordered. Many studies have determined their cellular location as well as biological functions although molecular mechanisms through which they act are actually little known therefore, the aim of this work was to define, explore and understand the Sirtuin-related human interactome. As a first step, we have integrated the experimentally determined protein–protein interactions of the Sirtuin-family as well as their first and second neighbors to a Sirtuin-related sub-interactome. Our data showed that the second-neighbor network of Sirtuins encompasses 25% of the entire human interactome, and exhibits a scale-free degree distribution and interconnectedness among top degree nodes. Moreover, the Sirtuin sub interactome showed a modular structure around the core comprising mixed functions. Finally, we extracted from the Sirtuin sub-interactome subnets related to cancer, aging and post-translational modifications for information on key nodes and topological space of the subnets in the Sirt family network.     

On the functional and structural characterization of hubs in protein–protein interaction networks

A number of interesting issues have been addressed on biological networks about their global and local properties. The connection between the topological properties of proteins in Protein–Protein Interaction (PPI) networks and their biological relevance has been investigated focusing on hubs, i.e. proteins with a large number of interacting partners. We will survey the literature trying to answer the following questions: Do hub proteins have special biological properties? Do they tend to be more essential than non-hub proteins? Are they more evolutionarily conserved? Do they play a central role in modular organization of the protein interaction network? Are there structural properties that characterize hub proteins?     

The neurobiology of depression—revisiting the serotonin hypothesis. I. Cellular and molecular mechanisms

The serotonin (5-HT) hypothesis of depression dates from the 1960s. It originally postulated that a deficit in brain serotonin, corrected by antidepressant drugs, was the origin of the illness. Nowadays, it is generally accepted that recurring mood disorders are brain diseases resulting from the combination, to various degrees, of genetic and other biological as well as environmental factors, evolving through the lifespan. All areas of neuroscience, from genes to behaviour, molecules to mind, and experimental to clinical, are actively engaged in attempts at elucidating the pathophysiology of depression and the mechanisms underlying the efficacy of antidepressant treatments. This first of two special issues of Philosophical Transactions B seeks to provide an overview of current developments in the field, with an emphasis on cellular and molecular mechanisms, and how their unravelling opens new perspectives for future research.     

Interactome of signaling networks in wheat: the protein–protein interaction between TaRAR1 and TaSGT1

RAR1 and SGT1 are required for development and disease resistance in plants. In many cases, RAR1 and SGT1 regulate the resistance (R)-gene-mediated defense signaling pathways. Lr21 is the first identified NBS-LRR-type R protein in wheat and is required for resistance to the leaf rust pathogen. The Lr21-mediated signaling pathways require the wheat homologs of RAR1, SGT1, and HSP90. However, the molecular mechanisms of the Lr21-mediated signaling networks remain unknown. Here I present the DNA and protein sequences of TaRAR1 and TaSGT1, and demonstrate for the first time a direct protein-protein interaction between them.     

A computational tool to predict the evolutionarily conserved protein–protein interaction hot-spot residues from the structure of the unbound protein

Identifying hot-spot residues – residues that are critical to protein–protein binding – can help to elucidate a protein’s function and assist in designing therapeutic molecules to target those residues. We present a novel computational tool, termed spatial-interaction-map (SIM), to predict the hot-spot residues of an evolutionarily conserved protein–protein interaction from the structure of an unbound protein alone. SIM can predict the protein hot-spot residues with an accuracy of 36–57%. Thus, the SIM tool can be used to predict the yet unknown hot-spot residues for many proteins for which the structure of the protein–protein complexes are not available, thereby providing a clue to their functions and an opportunity to design therapeutic molecules to target these proteins.     

Reuse of structural domain–domain interactions in protein networks

Background  

Protein interactions are thought to be largely mediated by interactions between structural domains. Databases such as iPfam relate interactions in protein structures to known domain families. Here, we investigate how the domain interactions from the iPfam database are distributed in protein interactions taken from the HPRD, MPact, BioGRID, DIP and IntAct databases.     

The protein–protein interactions required for assembly of the Tn3 resolution synapse

The site-specific recombinase Tn3 resolvase initiates DNA strand exchange when two res recombination sites and six resolvase dimers interact to form a synapse. The detailed architecture of this intricate recombination machine remains unclear. We have clarified which of the potential dimer–dimer interactions are required for synapsis and recombination, using a novel complementation strategy that exploits a previously uncharacterized resolvase from Bartonella bacilliformis (“Bart”). Tn3 and Bart resolvases recognize different DNA motifs, via diverged C-terminal domains (CTDs). They also differ substantially at N-terminal domain (NTD) surfaces involved in dimerization and synapse assembly. We designed NTD-CTD hybrid proteins, and hybrid res sites containing both Tn3 and Bart dimer binding sites. Using these components in in vivo assays, we demonstrate that productive synapsis requires a specific “R” interface involving resolvase NTDs at all three dimer-binding sites in res. Synapses containing mixtures of wild-type Tn3 and Bart resolvase NTD dimers are recombination-defective, but activity can be restored by replacing patches of Tn3 resolvase R interface residues with Bart residues, or vice versa. We conclude that the Tn3/Bart family synapse is assembled exclusively by R interactions between resolvase dimers, except for the one special dimer–dimer interaction required for catalysis.     

The structure of the FMO protein from Chlorobium tepidum at 2.2 Å resolution

The bacteriochlorophyll protein, or FMO protein, from Chlorobium tepidum, which serves as a light-harvesting complex and directs light energy from the chlorosomes attached to the cell membrane to the reaction center has been crystallized in a new space group. The crystals belong to the cubic space group P4₃32 and the structure has been refined to a resolution 2.2 Å with a R factor of 19.7%. The electron density maps show that the structure is composed of two sheets that surround seven bacteriochlorophylls as previously reported (Li et al. (1997) J Mol Biol 271: 456–471). The availability of the new data allows a more accurate refinement of the pigment–protein complex including identification of bound solvent molecules. Several structural differences probably contribute to the observed spectroscopic differences between the FMO proteins from Cb. tepidum and Prosthecochloris aestuarii, including differences in the planarity of corresponding tetrapyrroles. A citrate molecule is found on the surface of each protein subunit of the trimer from Cb. tepidum. However, the citrate molecule is over 15 Å from any bacteriochlorophyll. The presence of the citrate probably does not contribute to the function of the protein although it does contribute to the crystallization as it interacts with a crystallographically related trimer. Among the 236 water molecules found in the protein are four that appear to play a special role in the properties of bacteriochlorophyll 2, as this tetrapyrrole is coordinated by one of these water molecules and the waters form a hydrogen-bonded network that leads to the surface of the protein.This revised version was published online in October 2005 with corrections to the Cover Date.     

The Trivers–Willard hypothesis of parental investment: No effect in the contemporary United States

The Trivers–Willard hypothesis (TWH) predicts that parents will bias their sex ratio toward sons when in good condition and toward daughters when in poor condition. Many human studies have tested the related hypothesis that parents' bias allocation of resources to existing sons and daughters according to the same principle. The present study used time diary and self-report data from the parents of 3200 children in the US to test the hypothesis that as status increases, parents will allocate more resources to sons vs. daughters. It finds no evidence that higher-status parents invest more in sons or that lower status parents invest more in daughters. This finding illustrates the specificity of situations in which the TWH effects should be expected. Only certain types of parental investment — such as protection and a bias in the sex ratio — may have been selected to vary according to parental condition. Optimal allocation of resources after the child is born, however, is achieved not by the simple bias predicted by the TWH, but by allocating resources among offspring in ways that yield the largest marginal inclusive fitness gains.