36 research outputs found

    Framework for a Protein Ontology

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    Biomedical ontologies are emerging as critical tools in genomic and proteomic research, where complex data in disparate resources need to be integrated. A number of ontologies describe properties that can be attributed to proteins. For example, protein functions are described by the Gene Ontology (GO) and human diseases by SNOMED CT or ICD10. There is, however, a gap in the current set of ontologies – one that describes the protein entities themselves and their relationships. We have designed the PRotein Ontology (PRO) to facilitate protein annotation and to guide new experiments. The components of PRO extend from the classification of proteins on the basis of evolutionary relationships to the representation of the multiple protein forms of a gene (products generated by genetic variation, alternative splicing, proteolytic cleavage, and other post-translational modifications). PRO will allow the specification of relationships between PRO, GO and other ontologies in the OBO Foundry. Here we describe the initial development of PRO, illustrated using human and mouse proteins involved in the transforming growth factor-beta and bone morphogenetic protein signaling pathways

    From protein sequences to 3D-structures and beyond: the example of the UniProt Knowledgebase

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    With the dramatic increase in the volume of experimental results in every domain of life sciences, assembling pertinent data and combining information from different fields has become a challenge. Information is dispersed over numerous specialized databases and is presented in many different formats. Rapid access to experiment-based information about well-characterized proteins helps predict the function of uncharacterized proteins identified by large-scale sequencing. In this context, universal knowledgebases play essential roles in providing access to data from complementary types of experiments and serving as hubs with cross-references to many specialized databases. This review outlines how the value of experimental data is optimized by combining high-quality protein sequences with complementary experimental results, including information derived from protein 3D-structures, using as an example the UniProt knowledgebase (UniProtKB) and the tools and links provided on its website (http://www.uniprot.org/). It also evokes precautions that are necessary for successful predictions and extrapolations

    Photo-Active Biological Molecular Materials: From Photoinduced Dynamics to Transient Electronic Spectroscopies

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    We present an overview of a methodology for the simulation of the photo-response of biological (macro)molecules, designed around a Quantum Mechanics / Molecular Mechanics (QM/MM) subtractive scheme. The resulting simulation workflow, that goes from the characterization of the photo-active system to the modeling of (transient) electronic spectroscopies is implemented in the software COBRAMM, but is completely general and can be used in the framework of any specific QM/MM implementation. COBRAMM is a smart interface to existing state-of-the-art theoretical chemistry codes, combining different levels of description and different algorithms to realize tailored problem-driven computations. The power of this approach is illustrated by reviewing the studies of two fundamental problems involving biological light-sensitive molecules. First, we will consider the photodynamics of the retinal molecule, the pigment of rhodopsin, a visual receptor protein contained in the rod cells of the retina. Retinal, with its light-induced isomerization, triggers a cascade of events leading to the production of the nerve impulse. Then, we will review some studies focusing on the interaction of DNA systems with ultraviolet (UV) light, a problem that has become one of the benchmark for the development of nonlinear spectroscopy, because of the ultrashort excited state lifetimes that arise from very efficient radiationless excited state decay and consent self-protection of DNA against UV damage

    Reproducible isolation of distinct, overlapping segments of the phosphoproteome

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    The ability to routinely analyze and quantitatively measure changes in protein phosphorylation on a proteome-wide scale is essential for biological and clinical research. We assessed the ability of three common phosphopeptide isolation methods (phosphoramidate chemistry (PAC), immobilized metal affinity chromatography (IMAC) and titanium dioxide) to reproducibly, specifically and comprehensively isolate phosphopeptides from complex mixtures. Phosphopeptides were isolated from aliquots of a tryptic digest of the cytosolic fraction of Drosophila melanogaster Kc167 cells and analyzed by liquid chromatography-electrospray ionization tandem mass spectrometry. Each method reproducibly isolated phosphopeptides. The methods, however, differed in their specificity of isolation and, notably, in the set of phosphopeptides isolated. The results suggest that the three methods detect different, partially overlapping segments of the phosphoproteome and that, at present, no single method is sufficient for a comprehensive phosphoproteome analysis
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