Improving the prediction of protein binding sites by combining heterogeneous data and Voronoi diagrams

BACKGROUND: Protein binding site prediction by computational means can yield valuable information that complements and guides experimental approaches to determine the structure of protein complexes. Predictions become even more relevant and timely given the current resolution of protein interaction maps, where there is a very large and still expanding gap between the available information on: (i) which proteins interact and (ii) how proteins interact. Proteins interact through exposed residues that present differential physicochemical properties, and these can be exploited to identify protein interfaces. RESULTS: Here we present VORFFIP, a novel method for protein binding site prediction. The method makes use of broad set of heterogeneous data and defined of residue environment, by means of Voronoi Diagrams that are integrated by a two-steps Random Forest ensemble classifier. Four sets of residue features (structural, energy terms, sequence conservation, and crystallographic B-factors) used in different combinations together with three definitions of residue environment (Voronoi Diagrams, sequence sliding window, and Euclidian distance) have been analyzed in order to maximize the performance of the method. CONCLUSIONS: The integration of different forms information such as structural features, energy term, evolutionary conservation and crystallographic B-factors, improves the performance of binding site prediction. Including the information of neighbouring residues also improves the prediction of protein interfaces. Among the different approaches that can be used to define the environment of exposed residues, Voronoi Diagrams provide the most accurate description. Finally, VORFFIP compares favourably to other methods reported in the recent literature

A holistic in silico approach to predict functional sites in protein structures

Abstract Motivation: Proteins execute and coordinate cellular functions by interacting with other biomolecules. Among these interactions, protein–protein (including peptide-mediated), protein–DNA and protein–RNA interactions cover a wide range of critical processes and cellular functions. The functional characterization of proteins requires the description and mapping of functional biomolecular interactions and the identification and characterization of functional sites is an important step towards this end. Results: We have developed a novel computational method, Multi-VORFFIP (MV), a tool to predicts protein-, peptide-, DNA- and RNA-binding sites in proteins. MV utilizes a wide range of structural, evolutionary, experimental and energy-based information that is integrated into a common probabilistic framework by means of a Random Forest ensemble classifier. While remaining competitive when compared with current methods, MV is a centralized resource for the prediction of functional sites and is interfaced by a powerful web application tailored to facilitate the use of the method and analysis of predictions to non-expert end-users. Availability:  http://www.bioinsilico.org/MVORFFIP Supplementary information:  Supplementary data are available at Bioinformatics online. Contact:  [email protected]; [email protected]</jats:p

VORFFIP-Driven Dock:V-D ²OCK, a fast, accurate protein docking strategy

The experimental determination of the structure of protein complexes cannot keep pace with the generation of interactomic data, hence resulting in an ever-expanding gap. As the structural details of protein complexes are central to a full understanding of the function and dynamics of the cell machinery, alternative strategies are needed to circumvent the bottleneck in structure determination. Computational protein docking is a valid and valuable approach to model the structure of protein complexes. In this work, we describe a novel computational strategy to predict the structure of protein complexes based on data-driven docking: VORFFIP-driven dock (V-D²OCK). This new approach makes use of our newly described method to predict functional sites in protein structures, VORFFIP, to define the region to be sampled during docking and structural clustering to reduce the number of models to be examined by users. V-D²OCK has been benchmarked using a validated and diverse set of protein complexes and compared to a state-of-art docking method. The speed and accuracy compared to contemporary tools justifies the potential use of VD²OCK for high-throughput, genome-wide, protein docking. Finally, we have developed a web interface that allows users to browser and visualize V-D²OCK predictions from the convenience of their web-browsers

Chronic Invasive Aspergillosis caused by Aspergillus viridinutans

Aspergillus viridinutans, a mold phenotypically resembling A. fumigatus, was identified by gene sequence analyses from 2 patients. Disease was distinct from typical aspergillosis, being chronic and spreading in a contiguous manner across anatomical planes. We emphasize the recognition of fumigati-mimetic molds as agents of chronic or refractory aspergillosis

Detection of a CMB decrement towards a cluster of mJy radiosources

We present the results of radio, optical and near-infrared observations of the field of TOC J0233.3+3021, a cluster of milliJansky radiosources from the TexOx Cluster survey. In an observation of this field with the Ryle Telescope (RT) at 15 GHz, we measure a decrement in the cosmic microwave background (CMB) of $-675 \pm 95 \mu$Jy on the RT's $\approx$ 0.65 k$\lambda$ baseline. Using optical and infrared imaging with the McDonald 2.7-m Smith Reflector, Calar Alto 3.5-m telescope and UKIRT, we identify the host galaxies of five of the radiosources and measure magnitudes of $R \approx 24$, $J \approx 20$, $K \approx 18$. The CMB decrement is consistent with the Sunyaev-Zel'dovich (SZ) effect of a massive cluster of galaxies, which if modelled as a spherical King profile of core radius $\theta_C = 20^{\prime\prime}$ has a central temperature decrement of $900 \mu$K. The magnitudes and colours of the galaxies are consistent with those of old ellipticals at $z \sim 1$. We therefore conclude that TOC J0233.3+3021 is a massive, high redshift cluster. These observations add to the growing evidence for a significant population of massive clusters at high redshift, and demonstrate the effectiveness of combining searches for AGN `signposts' to clusters with the redshift-independence of the SZ effect.Comment: Six pages; accepted for publication in MNRAS. Version with full-resolution UV plot available from http://www.mrao.cam.ac.uk/~garret/MB185.p

Tumour cell CD99 regulates transendothelial migration via CDC42 and actin remodelling

Metastasis requires tumour cells to cross endothelial cell (EC) barriers using pathways similar to those used by leucocytes during inflammation. Cell surface CD99 is expressed by healthy leucocytes and ECs, and participates in inflammatory transendothelial migration (TEM). Tumour cells also express CD99, and we have analysed its role in tumour progression and cancer cell TEM. Tumour cell CD99 was required for adhesion to ECs but inhibited invasion of the endothelial barrier and migratory activity. Furthermore, CD99 depletion in tumour cells caused redistribution of the actin cytoskeleton and increased activity of the Rho GTPase CDC42, known for its role in actin remodelling and cell migration. In a xenograft model of breast cancer, tumour cell CD99 expression inhibited metastatic progression, and patient samples showed reduced expression of the CD99 gene in brain metastases compared to matched primary breast tumours. We conclude that CD99 negatively regulates CDC42 and cell migration. However, CD99 has both pro- and anti-tumour activity, and our data suggest that this results in part from its functional linkage to CDC42 and the diverse signalling pathways downstream of this Rho GTPase. This article has an associated First Person interview with the first author of the paper

Do Global Diversity Patterns of Vertebrates Reflect Those of Monocots?

Few studies of global diversity gradients in plants exist, largely because the data are not available for all species involved. Instead, most global studies have focussed on vertebrates, as these taxa have historically been associated with the most complete data. Here, we address this shortfall by first investigating global diversity gradients in monocots, a morphologically and functionally diverse clade representing a quarter of flowering plant diversity, and then assessing congruence between monocot and vertebrate diversity patterns. To do this, we create a new dataset that merges biome-level associations for all monocot genera with country-level associations for almost all &sim;70,000 species. We then assess the evidence for direct versus indirect effects of this plant diversity on vertebrate diversity using a combination of linear regression and structural equation modelling (SEM). Finally, we also calculate overlap of diversity hotspots for monocots and each vertebrate taxon. Monocots follow a latitudinal gradient although with pockets of extra-tropical diversity, mirroring patterns in vertebrates. Monocot diversity is positively associated with vertebrate diversity, but the strength of correlation varies depending on the clades being compared. Monocot diversity explains marginal amounts of variance (&lt;10%) after environmental factors have been accounted for. However, correlations remain among model residuals, and SEMs apparently reveal some direct effects of monocot richness. Our results suggest that collinear responses to environmental gradients are behind much of the congruence observed, but that there is some evidence for direct effects of producer diversity on consumer diversity. Much remains to be done before broad-scale diversity gradients among taxa are fully explained. Our dataset of monocot distributions will aid in this endeavour

Investigating hyper-vigilance for social threat of lonely children

The hypothesis that lonely children show hypervigilance for social threat was examined in a series of three studies that employed different methods including advanced eye-tracking technology. Hypervigilance for social threat was operationalized as hostility to ambiguously motivated social exclusion in a variation of the hostile attribution paradigm (Study 1), scores on the Children’s Rejection-Sensitivity Questionnaire (Study 2), and visual attention to socially rejecting stimuli (Study 3). The participants were 185 children (11 years-7 months to 12 years-6 months), 248 children (9 years-4 months to 11 years-8 months) and 140 children (8 years-10 months to 12 years-10 months) in the three studies, respectively. Regression analyses showed that, with depressive symptoms covaried, there were quadratic relations between loneliness and these different measures of hypervigilance to social threat. As hypothesized, only children in the upper range of loneliness demonstrated elevated hostility to ambiguously motivated social exclusion, higher scores on the rejection sensitivity questionnaire, and disengagement difficulties when viewing socially rejecting stimuli. We found that very lonely children are hypersensitive to social threat

Pro- and anti-tumour activities of CD146/MCAM in breast cancer result from its heterogeneous expression and association with epithelial to mesenchymal transition

CD146, also known as melanoma cell adhesion molecule (MCAM), is expressed in numerous cancers and has been implicated in the regulation of metastasis. We show that CD146 negatively regulates transendothelial migration (TEM) in breast cancer. This inhibitory activity is reflected by a reduction in MCAM gene expression and increased promoter methylation in tumour tissue compared to normal breast tissue. However, increased CD146/MCAM expression is associated with poor prognosis in breast cancer, a characteristic that is difficult to reconcile with inhibition of TEM by CD146 and its epigenetic silencing. Single cell transcriptome data revealed MCAM expression in multiple cell types, including the malignant cells, tumour vasculature and normal epithelium. MCAM expressing malignant cells were in the minority and expression was associated with epithelial to mesenchymal transition (EMT). Furthermore, gene expression signatures defining invasiveness and a stem cell-like phenotype were most strongly associated with mesenchymal-like tumour cells with low levels of MCAM mRNA, likely to represent a hybrid epithelial/mesenchymal (E/M) state. Our results show that high levels of MCAM gene expression are associated with poor prognosis in breast cancer because they reflect tumour vascularisation and high levels of EMT. We suggest that high levels of mesenchymal-like malignant cells reflect large populations of hybrid E/M cells and that low CD146 expression on these hybrid cells is permissive for TEM, aiding metastasis