A highly specific phosphatase that acts on ADP-ribose 1″-phosphate, a metabolite of tRNA splicing in Saccharomyces cerevisiae

One molecule of ADP-ribose 1″,2″-cyclic phosphate (Appr>p) is formed during each of the approximately 500 000 tRNA splicing events per Saccharomyces cerevisiae generation. The metabolism of Appr>p remains poorly defined. A cyclic phosphodiesterase (Cpd1p) has been shown to convert Appr>p to ADP-ribose-1″-phosphate (Appr1p). We used a biochemical genomics approach to identify two yeast phosphatases that can convert Appr1p to ADP-ribose: the product of ORF YBR022w (now Poa1p), which is completely unrelated to other known phosphatases; and Hal2p, a known 3′-phosphatase of 5′,3′-pAp. Poa1p is highly specific for Appr1p, and thus likely acts on this molecule in vivo. Poa1 has a relatively low K(M) for Appr1p (2.8 μM) and a modest k(cat) (1.7 min(−1)), but no detectable activity on several other substrates. Furthermore, Poa1p is strongly inhibited by ADP-ribose (K(I), 17 μM), modestly inhibited by other nucleotides containing an ADP-ribose moiety and not inhibited at all by other tested molecules. In contrast, Hal2p is much more active on pAp than on Appr1p, and several other tested molecules were Hal2p substrates or inhibitors. poa1-Δ mutants have no obvious growth defect at different temperatures in rich media, and analysis of yeast extracts suggests that ∼90% of Appr1p processing activity originates from Poa1p

A simple physical model for scaling in protein-protein interaction networks

It has recently been demonstrated that many biological networks exhibit a scale-free topology where the probability of observing a node with a certain number of edges (k) follows a power law: i.e. p(k) ~ k^-g. This observation has been reproduced by evolutionary models. Here we consider the network of protein-protein interactions and demonstrate that two published independent measurements of these interactions produce graphs that are only weakly correlated with one another despite their strikingly similar topology. We then propose a physical model based on the fundamental principle that (de)solvation is a major physical factor in protein-protein interactions. This model reproduces not only the scale-free nature of such graphs but also a number of higher-order correlations in these networks. A key support of the model is provided by the discovery of a significant correlation between number of interactions made by a protein and the fraction of hydrophobic residues on its surface. The model presented in this paper represents the first physical model for experimentally determined protein-protein interactions that comprehensively reproduces the topological features of interaction networks. These results have profound implications for understanding not only protein-protein interactions but also other types of scale-free networks.Comment: 50 pages, 17 figure

Predictive and experimental approaches for elucidating protein–protein interactions and quaternary structures

The elucidation of protein–protein interactions is vital for determining the function and action of quaternary protein structures. Here, we discuss the difficulty and importance of establishing protein quaternary structure and review in vitro and in silico methods for doing so. Determining the interacting partner proteins of predicted protein structures is very time-consuming when using in vitro methods, this can be somewhat alleviated by use of predictive methods. However, developing reliably accurate predictive tools has proved to be difficult. We review the current state of the art in predictive protein interaction software and discuss the problem of scoring and therefore ranking predictions. Current community-based predictive exercises are discussed in relation to the growth of protein interaction prediction as an area within these exercises. We suggest a fusion of experimental and predictive methods that make use of sparse experimental data to determine higher resolution predicted protein interactions as being necessary to drive forward development

On the Energy Transfer Performance of Mechanical Nanoresonators Coupled with Electromagnetic Fields

We study the energy transfer performance in electrically and magnetically coupled mechanical nanoresonators. Using the resonant scattering theory, we show that magnetically coupled resonators can achieve the same energy transfer performance as for their electrically coupled counterparts, or even outperform them within the scale of interest. Magnetic and electric coupling are compared in the Nanotube Radio, a realistic example of a nano-scale mechanical resonator. The energy transfer performance is also discussed for a newly proposed bio-nanoresonator composed of a magnetosomes coated with a net of protein fibers.Comment: 9 Pages, 3 Figure

Aggregation of Mod5 is affected by tRNA binding with implications for tRNA gene‐mediated silencing

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137240/1/feb212627_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137240/2/feb212627.pd

Plasmon resonance optical tuning based on photosensitive composite structures

This paper reports a numerical investigation of a periodic metallic structure sandwiched between two quartz plates. The volume comprised between the quartz plates and the metallic structure is infiltrated by a mixture of azo-dye-doped liquid crystal. The exposure to a low power visible light beam modifies the azo dye molecular configuration, thus allowing the wavelength shift of the resonance of the system. The wavelength shift depends on the geometry of the periodic structure and it also depends on the intensity of the visible light beam

Towards a Protein-Protein Interaction information extraction system: recognizing named entities

[EN] The majority of biological functions of any living being are related to Protein Protein Interactions (PPI). PPI discoveries are reported in form of research publications whose volume grows day after day. Consequently, automatic PPI information extraction systems are a pressing need for biologists. In this paper we are mainly concerned with the named entity detection module of PPIES (the PPI information extraction system we are implementing) which recognizes twelve entity types relevant in PPI context. It is composed of two sub-modules: a dictionary look-up with extensive normalization and acronym detection, and a Conditional Random Field classifier. The dictionary look-up module has been tested with Interaction Method Task (IMT), and it improves by approximately 10% the current solutions that do not use Machine Learning (ML). The second module has been used to create a classifier using the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA 04) data set. It does not use any external resources, or complex or ad hoc post-processing, and obtains 77.25%, 75.04% and 76.13 for precision, recall, and F1-measure, respectively, improving all previous results obtained for this data set.This work has been funded by MICINN, Spain, as part of the "Juan de la Cierva" Program and the Project DIANA-Applications (TIN2012-38603-C02-01), as well as the by the European Commission as part of the WIQ-EI IRSES Project (Grant No. 269180) within the FP 7 Marie Curie People Framework.Danger Mercaderes, RM.; Pla Santamaría, F.; Molina Marco, A.; Rosso, P. (2014). Towards a Protein-Protein Interaction information extraction system: recognizing named entities. Knowledge-Based Systems. 57:104-118. https://doi.org/10.1016/j.knosys.2013.12.010S1041185

Construction, Verification and Experimental Use of Two Epitope-Tagged Collections of Budding Yeast Strains

A major challenge in the post-genomic era is the development of experimental approaches to monitor the properties of proteins on a proteome-wide level. It would be particularly useful to systematically assay protein subcellular localization, post-translational modifications and protein–protein interactions, both at steady state and in response to environmental stimuli. Development of new reagents and methods will enhance our ability to do so efficiently and systematically. Here we describe the construction of two collections of budding yeast strains that facilitate proteome-wide measurements of protein properties. These collections consist of strains with an epitope tag integrated at the C-terminus of essentially every open reading frame (ORF), one with the tandem affinity purification (TAP) tag, and one with the green fluorescent protein (GFP) tag. We show that in both of these collections we have accurately tagged a high proportion of all ORFs (approximately 75% of the proteome) by confirming expression of the fusion proteins. Furthermore, we demonstrate the use of the TAP collection in performing high-throughput immunoprecipitation experiments. Building on these collections and the methods described in this paper, we hope that the yeast community will expand both the quantity and type of proteome level data available

Crystal structure and assembly of the functional Nanoarchaeum equitans tRNA splicing endonuclease

The RNA splicing and processing endonuclease from Nanoarchaeum equitans (NEQ) belongs to the recently identified (αβ)2 family of splicing endonucleases that require two different subunits for splicing activity. N. equitans splicing endonuclease comprises the catalytic subunit (NEQ205) and the structural subunit (NEQ261). Here, we report the crystal structure of the functional NEQ enzyme at 2.1 Å containing both subunits, as well as that of the NEQ261 subunit alone at 2.2 Å. The functional enzyme resembles previously known α2 and α4 endonucleases but forms a heterotetramer: a dimer of two heterodimers of the catalytic subunit (NEQ205) and the structural subunit (NEQ261). Surprisingly, NEQ261 alone forms a homodimer, similar to the previously known homodimer of the catalytic subunit. The homodimers of isolated subunits are inhibitory to heterodimerization as illustrated by a covalently linked catalytic homodimer that had no RNA cleavage activity upon mixing with the structural subunit. Detailed structural comparison reveals a more favorable hetero- than homodimerization interface, thereby suggesting a possible regulation mechanism of enzyme assembly through available subunits. Finally, the uniquely flexible active site of the NEQ endonuclease provides a possible explanation for its broader substrate specificity