A hitchhiker's guide to the cullin ubiquitin ligases: SCF and its kin

AbstractThe SCF (Skp1–Cullin–F-box) E3 ubiquitin ligase family was discovered through genetic requirements for cell cycle progression in budding yeast. In these multisubunit enzymes, an invariant core complex, composed of the Skp1 linker protein, the Cdc53/Cul1 scaffold protein and the Rbx1/Roc1/Hrt1 RING domain protein, engages one of a suite of substrate adaptors called F-box proteins that in turn recruit substrates for ubiquitination by an associated E2 enzyme. The cullin–RING domain–adaptor architecture has diversified through evolution, such that in total many hundreds of distinct SCF and SCF-like complexes enable degradation of myriad substrates. Substrate recognition by adaptors often depends on posttranslational modification of the substrate, which thus places substrate stability under dynamic regulation by intracellular signaling events. SCF complexes control cell proliferation through degradation of critical regulators such as cyclins, CDK inhibitors and transcription factors. A plethora of other processes in development and disease are controlled by other SCF-like complexes, including those based on Cul2–SOCS-box adaptor protein and Cul3–BTB domain adaptor protein combinations. Recent structural insights into SCF-like complexes have begun to illuminate aspects of substrate recognition and catalytic reaction mechanisms

Osprey: a network visualization system

We have developed a software platform called Osprey for visualization and manipulation of complex interaction networks. Osprey builds data-rich graphical representations that are color-coded for gene function and experimental interaction data. Mouse-over functions allow rapid elaboration and organization of network diagrams in a spoke model format. User-defined large-scale datasets can be readily combined with Osprey for comparison of different methods

Primordial Black Holes as Generators of Cosmic Structures

Primordial black holes (PBHs) could provide the dark matter in various mass windows below $10^2 M_{\odot}$ and those of $30 M_{\odot}$ might explain the LIGO events. PBHs much larger than this might have important consequences even if they provide only a small fraction of the dark matter. In particular, they could generate cosmological structure either individually through through the `seed' effect or collectively through the `Poisson' effect, thereby alleviating some problems associated with the standard CDM scenario. If the PBHs all have a similar mass and make a small contribution to the dark matter, then the seed effect dominates on small scales, in which case PBHs could seed the supermassive black holes in galactic nuclei or even galaxies themselves. If they have a similar mass and provide the dark matter, the Poisson effect dominates on all scales and the first bound clouds would form earlier than in the usual scenario, with interesting observational consequences. If the PBHs have an extended mass spectrum, which is more likely, they could fulfill all three roles - providing the dark matter, binding the first bound clouds and generating galaxies. In this case, the galactic mass function naturally has the observed form, with the galaxy mass being simply related to the black hole mass. The stochastic gravitational wave background from the PBHs in this scenario would extend continuously from the LIGO frequency to the LISA frequency, offering a potential goal for future surveys.Comment: 48 pages, 3 figures, accepted for publication in Monthly Notices of Royal Astronomical Societ

Evolutionary and Physiological Importance of Hub Proteins

It has been claimed that proteins with more interaction partners (hubs) are both physiologically more important (i.e., less dispensable) and, owing to an assumed high density of binding sites, slow evolving. Not all analyses, however, support these results, probably because of biased and less-than reliable global protein interaction data. Here we provide the first examination of these issues using a comprehensive literature-curated dataset of well-substantiated protein interactions in Saccharomyces cerevisiae. Whereas use of less reliable yeast two-hybrid data alone can reject the possibility that local connectivity correlates with measures of dispensability, in higher quality datasets a relatively robust correlation is observed. In contrast, local connectivity does not correlate with the rate of protein evolution even in reliable datasets. This perhaps surprising lack of correlation with evolutionary rate appears in part to arise from the fact that hub proteins do not have a higher density of residues associated with binding. However, hub proteins do have at least one other set of unusual features, namely rapid turnover and regulation, as manifest in high mRNA decay rates and a large number of phosphorylation sites. This, we suggest, is an adaptation to minimize unwanted activation of pathways that might be mediated by adventitious binding to hubs, were they to actively persist longer than required at any given time point. We conclude that hub proteins are more important for cellular growth rate and under tight regulation but are not slow evolving

BioGRID: a general repository for interaction datasets

Access to unified datasets of protein and genetic interactions is critical for interrogation of gene/protein function and analysis of global network properties. BioGRID is a freely accessible database of physical and genetic interactions available at . BioGRID release version 2.0 includes >116 000 interactions from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens. Over 30 000 interactions have recently been added from 5778 sources through exhaustive curation of the Saccharomyces cerevisiae primary literature. An internally hyper-linked web interface allows for rapid search and retrieval of interaction data. Full or user-defined datasets are freely downloadable as tab-delimited text files and PSI-MI XML. Pre-computed graphical layouts of interactions are available in a variety of file formats. User-customized graphs with embedded protein, gene and interaction attributes can be constructed with a visualization system called Osprey that is dynamically linked to the BioGRID

Structure-Templated Predictions of Novel Protein Interactions from Sequence Information

The multitude of functions performed in the cell are largely controlled by a set of carefully orchestrated protein interactions often facilitated by specific binding of conserved domains in the interacting proteins. Interacting domains commonly exhibit distinct binding specificity to short and conserved recognition peptides called binding profiles. Although many conserved domains are known in nature, only a few have well-characterized binding profiles. Here, we describe a novel predictive method known as domain–motif interactions from structural topology (D-MIST) for elucidating the binding profiles of interacting domains. A set of domains and their corresponding binding profiles were derived from extant protein structures and protein interaction data and then used to predict novel protein interactions in yeast. A number of the predicted interactions were verified experimentally, including new interactions of the mitotic exit network, RNA polymerases, nucleotide metabolism enzymes, and the chaperone complex. These results demonstrate that new protein interactions can be predicted exclusively from sequence information