Predicting metal-binding site residues in low-resolution structural models

The accurate prediction of the biochemical function of a protein is becoming increasingly important, given the unprecedented growth of both structural and sequence databanks. Consequently, computational methods are required to analyse such data in an automated manner to ensure genomes are annotated accurately. Protein structure prediction methods, for example, are capable of generating approximate structural models on a genome-wide scale. However, the detection of functionally important regions in such crude models, as well as structural genomics targets, remains an extremely important problem. The method described in the current study, MetSite, represents a fully automatic approach for the detection of metal-binding residue clusters applicable to protein models of moderate quality. The method involves using sequence profile information in combination with approximate structural data. Several neural network classifiers are shown to be able to distinguish metal sites from non-sites with a mean accuracy of 94.5%. The method was demonstrated to identify metal-binding sites correctly in LiveBench targets where no obvious metal-binding sequence motifs were detectable using InterPro. Accurate detection of metal sites was shown to be feasible for low-resolution predicted structures generated using mGenTHREADER where no side-chain information was available. High-scoring predictions were observed for a recently solved hypothetical protein from Haemophilus influenzae, indicating a putative metal-binding site.

Automatic prediction of functional site regions in low-resolution protein structures

World-wide structural genomics initiatives are rapidly accumulating structures for which limited functional information is available. Additionally, state-of-the art structural prediction programs are now capable of generating at least low resolution structural models of target proteins. Accurate detection and classification of functional sites within both solved and modelled protein structures therefore represents an important challenge. We present a fully automatic site detection method, FuncSite, that uses neural network classifiers to predict the location and type of functionally important sites in protein structures. The method is designed primarily to require only backbone residue positions without the need for specific side-chain atoms to be present. In order to highlight effective site detection in low resolution structural models FuncSite was used to screen model proteins generated using mGenTHREADER on a set of newly released structures. We found effective metal site detection even for moderate quality protein models illustrating the robustness of the method.

Multiple-project discount rates for cost-benefit analysis in construction projects: A formal risk model for microgeneration renewable energy technologies

The traditional economic approach for appraising the costs and benefits of construction project Net Present Values involves the calculation of net returns for each investment option under different discount rates. An alternative approach consists of multiple-project discount rates based on risk modelling. The example of a portfolio of microgeneration renewable energy technology (MRET) is presented to demonstrate that risks and future available budget for re-investment can be taken into account when setting discount rates for construction project specifications in presence of uncertainty. A formal demonstration is carried out through a reversed intertemporal approach of applied general equilibrium. It is demonstrated that risk and the estimated available budget for future re-investment can be included in the simultaneous assessment of the costs and benefits of multiple projects.

Proportions of A1, A2, B and C β-casein protein variants in retail milk in the UK

The A1 variant protein of the β-casein family has been implicated in various disease states although much evidence is weak or contradictory. The primary objective was to measure, for the first time, the proportions of the key β-casein variant proteins in UK retail milk over the course of one year. In total, 55 samples of semi-skimmed milk were purchased from five supermarkets over the course of a year and the proportions of the A1, A2, B and C casein variant proteins were measured, using high resolution HPLC-MS. The results showed that β-casein in UK retail milk comprises approximately 0.58, 0.31, 0.07 and 0.03 A2, A1, B and C protein variants, respectively. The proportion of A2 is higher than some early studies would predict although the reasons for this and any implications for health are unclear

The curious case of the camelthorn: competition, coexistence and nest-site limitation in a multispecies mutualism

Myrmecophyte plants house ants in domatia in exchange for protection from herbivores. Ant-myrmecophyte mutualisms exhibit two general patterns due to competition between ants for plant occupancy: i) domatia nest-sites are a limiting resource and ii) each individual plant hosts one ant species at a time. However, individual camelthorn trees (Vachellia erioloba) typically host two to four ant species simultaneously, often coexisting in adjacent domatia on the same branch. Such fine-grain spatial coexistence brings into question the conventional wisdom on ant-myrmecophyte mutualisms. Camelthorn ants appear not to be nest-site limited, despite low abundance of suitable domatia, and have random distributions of nest-sites within and across trees. These patterns suggest a lack of competition between ants for domatia and contrast strongly with other ant-myrmecophyte systems. Comparison of this unusual case with others suggests that spatial scale is crucial to coexistence or competitive exclusion involving multiple ant species. Furthermore, coexistence may be facilitated when co-occurring ant species diverge strongly on at least one niche axis. Our conclusions provide recommendations for future ant-myrmecophyte research, particularly in utilising multispecies systems to further our understanding of mutualism biology.

Cell stress-induced phosphorylation of ATF2 and c-Jun transcription factors in rat ventricular myocytes.

Ventricular myocytes are exposed to various pathologically important cell stresses in vivo. In vitro, extreme stresses (sorbitol-induced hyperosmotic shock in the presence or absence of okadaic acid, and anisomycin) were applied to ventricular myocytes cultured from neonatal rat hearts to induce a robust activation of the 46 and 54 kDa stress-activated protein kinases (SAPKs). These activities were increased in nuclear extracts of cells in the absence of any net import of SAPK protein. Phosphorylation of ATF2 and c-Jun was increased as shown by the appearance of reduced-mobility species on SDS/PAGE, which were sensitive to treatment with protein phosphatase 2A. Hyperosmotic shock and anisomycin had no effect on the abundance of ATF2. In contrast, cell stresses induced a greater than 10-fold increase in total c-Jun immunoreactivity detected on Western blots with antibody to c-Jun (KM-1). Cycloheximide did not inhibit this increase, which we conclude represents phosphorylation of c-Jun. This conclusion was supported by use of a c-Jun(phospho-Ser-73) antibody. Immunostaining of cells also showed increases in nuclear phospho-c-Jun in response to hyperosmotic stress. Severe stress (hyperosmotic shock+okadaic acid for 2 h) induced proteins (migrating at approx. 51 and 57 kDa) that cross-reacted strongly with KM-1 antibodies in both the nucleus and the cytosol. These may represent forms of c-Jun that had undergone further modification. These studies show that stresses induce phosphorylation of transcription factors in ventricular myocytes and we suggest that this response may be pathologically relevant.

Effects of species turnover on reserve site selection in a fragmented landscape

Changes in species composition is an important process in many ecosystems but rarely considered in systematic reserve site selection. To test the influence of temporal variability in species composition on the establishment of a reserve network, we compared network configurations based on species data of small mammals and frogs sampled during two consecutive years in a fragmented Atlantic Forest landscape (SE Brazil). Site selection with simulated annealing was carried out with the datasets of each single year and after merging the datasets of both years. Site selection resulted in remarkably divergent network configurations. Differences are reflected in both the identity of the selected fragments and in the amount of flexibility and irreplaceability in network configuration. Networks selected when data for both years were merged did not include all sites that were irreplaceable in one of the 2 years. Results of species number estimation revealed that significant changes in the composition of the species community occurred. Hence, temporal variability of community composition should be routinely tested and considered in systematic reserve site selection in dynamic systems.

Two-dimensional electron states bound to an off-plane donor in a magnetic field

The states of an electron confined in a two-dimensional (2D) plane and bound to an off-plane donor impurity center, in the presence of a magnetic field, are investigated. The energy levels of the ground state and the first three excited states are calculated variationally. The binding energy and the mean orbital radius of these states are obtained as a function of the donor center position and the magnetic field strength. The limiting cases are discussed for an in-plane donor impurity (i.e. a 2D hydrogen atom) as well as for the donor center far away from the 2D plane in strong magnetic fields, which corresponds to a 2D harmonic oscillator.