A text-mining system for extracting metabolic reactions from full-text articles

Background: Increasingly biological text mining research is focusing on the extraction of complex relationships relevant to the construction and curation of biological networks and pathways. However, one important category of pathway—metabolic pathways—has been largely neglected. Here we present a relatively simple method for extracting metabolic reaction information from free text that scores different permutations of assigned entities (enzymes and metabolites) within a given sentence based on the presence and location of stemmed keywords. This method extends an approach that has proved effective in the context of the extraction of protein–protein interactions. Results: When evaluated on a set of manually-curated metabolic pathways using standard performance criteria, our method performs surprisingly well. Precision and recall rates are comparable to those previously achieved for the well-known protein-protein interaction extraction task. Conclusions: We conclude that automated metabolic pathway construction is more tractable than has often been assumed, and that (as in the case of protein–protein interaction extraction) relatively simple text-mining approaches can prove surprisingly effective. It is hoped that these results will provide an impetus to further research and act as a useful benchmark for judging the performance of more sophisticated methods that are yet to be developed

Towards a lightweight generic computational grid framework for biological research

Background: An increasing number of scientific research projects require access to large-scale computational resources. This is particularly true in the biological field, whether to facilitate the analysis of large high-throughput data sets, or to perform large numbers of complex simulations – a characteristic of the emerging field of systems biology. Results: In this paper we present a lightweight generic framework for combining disparate computational resources at multiple sites (ranging from local computers and clusters to established national Grid services). A detailed guide describing how to set up the framework is available from the following URL: http://igrid-ext.cryst.bbk.ac.uk/portal_guide/. Conclusion: This approach is particularly (but not exclusively) appropriate for large-scale biology projects with multiple collaborators working at different national or international sites. The framework is relatively easy to set up, hides the complexity of Grid middleware from the user, and provides access to resources through a single, uniform interface. It has been developed as part of the European ImmunoGrid project

Utilities for high-throughput analysis of B-cell clonal lineages

There are at present few tools available to assist with the determination and analysis of B-cell lineage trees from next-generation sequencing data. Here we present two utilities that support automated large-scale analysis and the creation of publication-quality results. The tools are available on the web, and are also available for download so that they can be integrated into an automated pipeline. Critically, and in contrast to previously published tools, these utilities can be used with any suitable phylogenetic inference method and with any antibody germline library, and hence are species-independent

Investigating substitutions in antibody–antigen complexes using molecular dynamics: a case study with broad-spectrum, Influenza A antibodies

In studying the binding of host antibodies to the surface antigens of pathogens, the structural and functional characterization of antibody–antigen complexes by X-ray crystallography and binding assay is important. However, the characterization requires experiments that are typically time consuming and expensive: thus, many antibody–antigen complexes are under-characterized. For vaccine development and disease surveillance, it is often vital to assess the impact of amino acid substitutions on antibody binding. For example, are there antibody substitutions capable of improving binding without a loss of breadth, or antigen substitutions that lead to antigenic escape? The questions cannot be answered reliably from sequence variation alone, exhaustive substitution assays are usually impractical, and alanine scans provide at best an incomplete identification of the critical residue–residue interactions. Here, we show that, given an initial structure of an antibody bound to an antigen, molecular dynamics simulations using the energy method molecular mechanics with Generalized Born surface area (MM/GBSA) can model the impact of single amino acid substitutions on antibody–antigen binding energy. We apply the technique to three broad-spectrum antibodies to influenza A hemagglutinin and examine both previously characterized and novel variant strains observed in the human population that may give rise to antigenic escape. We find that in some cases the impact of a substitution is local, while in others it causes a reorientation of the antibody with wide-ranging impact on residue–residue interactions: this explains, in part, why the change in chemical properties of a residue can be, on its own, a poor predictor of overall change in binding energy. Our estimates are in good agreement with experimental results—indeed, they approximate the degree of agreement between different experimental techniques. Simulations were performed on commodity computer hardware; hence, this approach has the potential to be widely adopted by those undertaking infectious disease research. Novel aspects of this research include the application of MM/GBSA to investigate binding between broadly binding antibodies and a viral glycoprotein; the development of an approach for visualizing substrate–ligand interactions; and the use of experimental assay data to rescale our predictions, allowing us to make inferences about absolute, as well as relative, changes in binding energy

Flexibility and intrinsic disorder are conserved features of hepatitis C virus E2 glycoprotein

The glycoproteins of hepatitis C virus, E1E2, are unlike any other viral fusion machinery yet described, and are the current focus of immunogen design in HCV vaccine development; thus, making E1E2 both scientifically and medically important. We used pre-existing, but fragmentary, structures to model a complete ectodomain of the major glycoprotein E2 from three strains of HCV. We then performed molecular dynamic simulations to explore the conformational landscape of E2, revealing a number of important features. Despite high sequence divergence, and subtle differences in the models, E2 from different strains behave similarly, possessing a stable core flanked by highly flexible regions, some of which perform essential functions such as receptor binding. Comparison with sequence data suggest that this consistent behaviour is conferred by a network of conserved residues that act as hinge and anchor points throughout E2. The variable regions (HVR-1, HVR-2 and VR-3) exhibit particularly high flexibility, and bioinformatic analysis suggests that HVR-1 is a putative intrinsically disordered protein region. Dynamic cross-correlation analyses demonstrate intramolecular communication and suggest that specific regions, such as HVR-1, can exert influence throughout E2. To support our computational approach we performed small-angle X-ray scattering with purified E2 ectodomain; this data was consistent with our MD experiments, suggesting a compact globular core with peripheral flexible regions. This work captures the dynamic behaviour of E2 and has direct relevance to the interaction of HCV with cell-surface receptors and neutralising antibodies

Loss of LKB1-NUAK1 signalling enhances NF-κB activity in a spheroid model of high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) is an aggressive malignancy often diagnosed at an advanced stage. Although most HGSOC patients respond initially to debulking surgery combined with cytotoxic chemotherapy, many ultimately relapse with platinum-resistant disease. Thus, improving outcomes requires new ways of limiting metastasis and eradicating residual disease. We identified previously that Liver kinase B1 (LKB1) and its substrate NUAK1 are implicated in EOC spheroid cell viability and are required for efficient metastasis in orthotopic mouse models. Here, we sought to identify additional signalling pathways altered in EOC cells due to LKB1 or NUAK1 loss-of-function. Transcriptome analysis revealed that inflammatory signalling mediated by NF-κB transcription factors is hyperactive due to LKB1-NUAK1 loss in HGSOC cells and spheroids. Upregulated NF-κB signalling due to NUAK1 loss suppresses reactive oxygen species (ROS) production and sustains cell survival in spheroids. NF-κB signalling is also activated in HGSOC precursor fallopian tube secretory epithelial cell spheroids, and is further enhanced by NUAK1 loss. Finally, immunohistochemical analysis of OVCAR8 xenograft tumors lacking NUAK1 displayed increased RelB expression and nuclear staining. Our results support the idea that NUAK1 and NF-κB signalling pathways together regulate ROS and inflammatory signalling, supporting cell survival during each step of HGSOC pathogenesis. We propose that their combined inhibition may be efficacious as a novel therapeutic strategy for advanced HGSOC

A realistic assessment of methods for extracting gene/protein interactions from free text

Background: The automated extraction of gene and/or protein interactions from the literature is one of the most important targets of biomedical text mining research. In this paper we present a realistic evaluation of gene/protein interaction mining relevant to potential non-specialist users. Hence we have specifically avoided methods that are complex to install or require reimplementation, and we coupled our chosen extraction methods with a state-of-the-art biomedical named entity tagger. Results: Our results show: that performance across different evaluation corpora is extremely variable; that the use of tagged (as opposed to gold standard) gene and protein names has a significant impact on performance, with a drop in F-score of over 20 percentage points being commonplace; and that a simple keyword-based benchmark algorithm when coupled with a named entity tagger outperforms two of the tools most widely used to extract gene/protein interactions. Conclusion: In terms of availability, ease of use and performance, the potential non-specialist user community interested in automatically extracting gene and/or protein interactions from free text is poorly served by current tools and systems. The public release of extraction tools that are easy to install and use, and that achieve state-of-art levels of performance should be treated as a high priority by the biomedical text mining community

Increased epitope complexity correlated with antibody affinity maturation and a novel binding mode revealed by structures of rabbit antibodies against the third variable loop (V3) of HIV-1 gp120.

The V3 loop of HIV-1 gp120 is an immunodominant region targeted by neutralizing antibodies (nAbs). Despite limited breadth, better characterization of the structural details of the interactions between these nAbs and their target epitopes would enhance our understanding of the mechanism of neutralization and facilitate designing better immunogens to induce nAbs with greater breadth. Recently, we isolated two anti-V3 neutralizing monoclonal antibodies (mAbs), 10A3 and 10A37, from a rabbit immunized with gp120 of the M group consensus sequence. In this study, crystal structures of these mAbs bound to target epitopes were determined. 10A3 binds to the V3 crown (303TRKSIHIGPGRAF317), using the cradle binding mode similar to human V3 mAbs encoded by IGHV5-51 germline genes and its epitope structure resembles that bound to the human antibodies. In contrast, 10A37, which exhibits greater breadth and potency than 10A3, binds the V3 crown and the succeeding stem region (308HIGPGRAFYTTGEI323). Unexpectedly, the 315RAFYTT320 portion of the epitope existed as helical turns, a V3 structure that has not been observed previously. Its main chain-dominated antigen-antibody interactions not only explain the broad neutralization of 10A37 but also show that its epitope is a potential vaccine target to be further evaluated. In conclusion, our study provides novel insights about neutralization-susceptible epitope structures of the V3 loop of HIV-1 gp120 and demonstrates that, despite low amino acid sequence similarity from human antibody germline genes, rabbits can serve as a useful animal model to evaluate human vaccine candidates. IMPORTANCE The apex crown of the third variable loop (V3) of HIV-1 gp120 is the most immunogenic region of the surface glycoprotein and many mAbs targeting this region have been developed. Structural understanding of V3 crown mAbs not only can help understand how antibody responses targeting this unique region, but also contribute to immunogen design for vaccine development. We present here crystal structures of two neutralizing V3 mAbs, 10A3 and 10A37, developed from rabbits immunized with gp120. Our analysis of 10A3 in complex with V3 provided a detailed example of how epitope complexity can evolve with affinity maturation, while that of 10A37 revealed a novel V3 binding mode targeting the C-terminal side of V3 crown and showed that this region can form a helical structure. Our study provides novel insights about neutralization-susceptible V3 epitope structures and demonstrates that rabbits can serve as a useful animal model to evaluate human vaccine candidates