582 research outputs found

    ComplexViewer: visualization of curated macromolecular complexes.

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    SUMMARY: Proteins frequently function as parts of complexes, assemblages of multiple proteins and other biomolecules, yet network visualizations usually only show proteins as parts of binary interactions. ComplexViewer visualizes interactions with more than two participants and thereby avoids the need to first expand these into multiple binary interactions. Furthermore, if binding regions between molecules are known then these can be displayed in the context of the larger complex. AVAILABILITY AND IMPLEMENTATION: freely available under Apache version 2 license; EMBL-EBI Complex Portal: http://www.ebi.ac.uk/complexportal; Source code: https://github.com/MICommunity/ComplexViewer; Package: https://www.npmjs.com/package/complexviewer; http://biojs.io/d/complexviewer. Language: JavaScript; Web technology: Scalable Vector Graphics; Libraries: D3.js. CONTACT: [email protected] or [email protected]

    Carbohydrate chemistry: synthetic and structural challenges towards the end of the 20th century*

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    Abstract: Carbohydrate chemistry has acquired considerable interest in many different facets during the last decades of the century. Particularly, the synthesis of complex carbohydrates in the form of large oligosaccharides has paved the way for a better appreciation of the function of carbohydrates in biological systems. The impressive advances associated with the structural determination and analysis of oligosaccharides has furthermore contributed to the increased focus on the role of carbohydrates particularly in the form of glycoproteins but also as signal molecules in general. The primary goal of this work is to discuss the advancement of structural assessment of large oligosaccharides as typi®ed by the structural determination of the 22-mer saccharide from the LPS of Salmonella enterica ssp. typhimurium strain 1135 using very high ®eld strength NMR spectroscopy. The challenges of synthesizing and analysing the structure of glycopeptides will also be discussed. Finally, the latest developments in glycopeptide libraries generated by solidphase combinatorial chemistry will be presented in addition to examples of new techniques where the increased sensitivity using nanoprobe technology in combination with MALDI-TOF MS spectroscopy was used in the structural assignment of such complex glycopeptides; a methodology of invaluable importance for the analysis of glycopeptides on single beads

    JAMI: a Java library for molecular interactions and data interoperability.

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    BACKGROUND: A number of different molecular interactions data download formats now exist, designed to allow access to these valuable data by diverse user groups. These formats include the PSI-XML and MITAB standard interchange formats developed by Molecular Interaction workgroup of the HUPO-PSI in addition to other, use-specific downloads produced by other resources. The onus is currently on the user to ensure that a piece of software is capable of read/writing all necessary versions of each format. This problem may increase, as data providers strive to meet ever more sophisticated user demands and data types. RESULTS: A collaboration between EMBL-EBI and the University of Cambridge has produced JAMI, a single library to unify standard molecular interaction data formats such as PSI-MI XML and PSI-MITAB. The JAMI free, open-source library enables the development of molecular interaction computational tools and pipelines without the need to produce different versions of software to read different versions of the data formats. CONCLUSION: Software and tools developed on top of the JAMI framework are able to integrate and support both PSI-MI XML and PSI-MITAB. The use of JAMI avoids the requirement to chain conversions between formats in order to reach a desired output format and prevents code and unit test duplication as the code becomes more modular. JAMI's model interfaces are abstracted from the underlying format, hiding the complexity and requirements of each data format from developers using JAMI as a library

    The IMEx coronavirus interactome: an evolving map of Coronaviridae-host molecular interactions

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    The current coronavirus disease of 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus (SARS-CoV)-2, has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions can provide fine-grained resolution of the mechanisms behind the virus biology and the human organism response. We present a curated dataset of physical molecular interactions focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family that has been manually extracted by International Molecular Exchange (IMEx) Consortium curators. Currently, the dataset comprises over 4400 binarized interactions extracted from 151 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website (https://www.ebi.ac.uk/intact) and will be continuously updated as research on COVID-19 progresses

    Development of selective ADAMTS-5 peptide substrates to monitor proteinase activity

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    The dysregulation of proteinase activity is a hallmark of osteoarthritis (OA), a disease characterized by progressive degradation of articular cartilage by catabolic proteinases such as a disintegrin and metalloproteinase with thrombospondin type I motifs-5 (ADAMTS-5). The ability to detect such activity sensitively would aid disease diagnosis and the evaluation of targeted therapies. Förster resonance energy transfer (FRET) peptide substrates can detect and monitor disease-related proteinase activity. To date, FRET probes for detecting ADAMTS-5 activity are nonselective and relatively insensitive. We describe the development of rapidly cleaved and highly selective ADAMTS-5 FRET peptide substrates through in silico docking and combinatorial chemistry. The lead substrates 3 and 26 showed higher overall cleavage rates (∼3–4-fold) and catalytic efficiencies (∼1.5–2-fold) compared to the best current ADAMTS-5 substrate ortho-aminobenzoyl(Abz)-TESE↓SRGAIY-N-3-[2,4-dinitrophenyl]-l-2,3-diaminopropionyl(Dpa)-KK-NH2. They exhibited high selectivity for ADAMTS-5 over ADAMTS-4 (∼13–16-fold), MMP-2 (∼8–10-fold), and MMP-9 (∼548–2561-fold) and detected low nanomolar concentrations of ADAMTS-5

    Annotation extensions

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    The specificity of knowledge that Gene Ontology (GO) annotations currently can represent is still restricted by the legacy format of the GO annotation file, a format intentionally designed for simplicity to keep the barriers to entry low and thus encourage initial adoption. Historically, the information that could be captured in a GO annotation was simply the role or location of a gene product, although genetically interacting or binding partners could be specified. While there was no mechanism within the original GO annotation format for capturing additional information about the context of a GO term, such as the target gene of an activity or the location of a molecular function, the long-term vision for the GO Consortium was to provide greater expressivity in its annotations to capture physiologically relevant information. Thus, as a step forwards, the GO Consortium has introduced a new field into the annotation format, annotation extensions, which can be used to capture valuable contextual detail. This provides experimentally verified links between gene products and other physiological information that is crucial for accurate analysis of pathway and network data. This chapter will provide a simple overview of annotation extensions, illustrated with examples of their usage, and explain why they are useful for scientists and bioinformaticians alike

    Encompassing new use cases - level 3.0 of the HUPO-PSI format for molecular interactions.

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    BACKGROUND: Systems biologists study interaction data to understand the behaviour of whole cell systems, and their environment, at a molecular level. In order to effectively achieve this goal, it is critical that researchers have high quality interaction datasets available to them, in a standard data format, and also a suite of tools with which to analyse such data and form experimentally testable hypotheses from them. The PSI-MI XML standard interchange format was initially published in 2004, and expanded in 2007 to enable the download and interchange of molecular interaction data. PSI-XML2.5 was designed to describe experimental data and to date has fulfilled this basic requirement. However, new use cases have arisen that the format cannot properly accommodate. These include data abstracted from more than one publication such as allosteric/cooperative interactions and protein complexes, dynamic interactions and the need to link kinetic and affinity data to specific mutational changes. RESULTS: The Molecular Interaction workgroup of the HUPO-PSI has extended the existing, well-used XML interchange format for molecular interaction data to meet new use cases and enable the capture of new data types, following extensive community consultation. PSI-MI XML3.0 expands the capabilities of the format beyond simple experimental data, with a concomitant update of the tool suite which serves this format. The format has been implemented by key data producers such as the International Molecular Exchange (IMEx) Consortium of protein interaction databases and the Complex Portal. CONCLUSIONS: PSI-MI XML3.0 has been developed by the data producers, data users, tool developers and database providers who constitute the PSI-MI workgroup. This group now actively supports PSI-MI XML2.5 as the main interchange format for experimental data, PSI-MI XML3.0 which additionally handles more complex data types, and the simpler, tab-delimited MITAB2.5, 2.6 and 2.7 for rapid parsing and download

    Enhanced Membrane Pore Formation through High-Affinity Targeted Antimicrobial Peptides

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    Many cationic antimicrobial peptides (AMPs) target the unique lipid composition of the prokaryotic cell membrane. However, the micromolar activities common for these peptides are considered weak in comparison to nisin, which follows a targeted, pore-forming mode of action. Here we show that AMPs can be modified with a high-affinity targeting module, which enables membrane permeabilization at low concentration. Magainin 2 and a truncated peptide analog were conjugated to vancomycin using click chemistry, and could be directed towards specific membrane embedded receptors both in model membrane systems and whole cells. Compared with untargeted vesicles, a gain in permeabilization efficacy of two orders of magnitude was reached with large unilamellar vesicles that included lipid II, the target of vancomycin. The truncated vancomycin-peptide conjugate showed an increased activity against vancomycin resistant Enterococci, whereas the full-length conjugate was more active against a targeted eukaryotic cell model: lipid II containing erythrocytes. This study highlights that AMPs can be made more selective and more potent against biological membranes that contain structures that can be targeted

    Capturing variation impact on molecular interactions in the IMEx Consortium mutations data set

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    The current wealth of genomic variation data identified at nucleotide level presents the challenge of understanding by which mechanisms amino acid variation affects cellular processes. These effects may manifest as distinct phenotypic differences between individuals or result in the development of disease. Physical interactions between molecules are the linking steps underlying most, if not all, cellular processes. Understanding the effects that sequence variation has on a molecule's interactions is a key step towards connecting mechanistic characterization of nonsynonymous variation to phenotype. We present an open access resource created over 14 years by IMEx database curators, featuring 28,000 annotations describing the effect of small sequence changes on physical protein interactions. We describe how this resource was built, the formats in which the data is provided and offer a descriptive analysis of the data set. The data set is publicly available through the IntAct website and is enhanced with every monthly release
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