Methods in molecular biology
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UniCarbKB ( http://unicarbkb.org ) is a comprehensive resource for mammalian glycoprotein and annotation data. In particular, the database provides information on the oligosaccharides characterized from a glycoprotein at either the global or site-specific level. This evidence is accumulated from a peer-reviewed and manually curated collection of information on oligosaccharides derived from membrane and secreted glycoproteins purified from biological fluids and/or tissues. ⋯ In this Chapter, we outline the objectives of UniCarbKB, and describe a selection of step-by-step workflows for navigating the information available. We also provide a short description of web services available and future plans for improving data access. The information presented in this Chapter supplements content available in our knowledgebase including regular updates on interface improvements, new features, and revisions to the database content ( http://confluence.unicarbkb.org ).
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Traditional bottom-up mass spectrometry-based proteomics relies on the use of an enzyme, often trypsin, to generate small peptides (typically < 25 amino acids long). In top-down proteomics, proteins remain intact and are directly measured within the mass spectrometer. ⋯ In this chapter, we will show the analysis of intact protein spectra through deconvolution, deisotoping, and searching with ProSight Lite, a free, vendor-agnostic tool for the analysis of top-down mass spectrometry data. We will illustrate with two examples of intact protein fragmentation spectra and discuss the iterative use of the software to characterize proteoforms and discover the sites of post-translational modifications.
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High-throughput proteomics studies generate large amounts of data. Biological interpretation of these large scale datasets is often challenging. ⋯ In this chapter, we describe various analyses that can be performed and bioinformatics tools and resources that enable users to do the analyses. Many Web-based and stand-alone tools are relatively user-friendly and can be used by most biologists without significant assistance.
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Recent advancements in high-throughput technologies such as mass spectrometry have led to an increase in the rate at which data is generated and accumulated. As a result, standard statistical methods no longer suffice as a way of analyzing such gigantic amounts of data. Network analysis, the evaluation of how nodes relate to one another, has over the years become an integral tool for analyzing high throughput proteomic data as they provide a structure that helps reduce the complexity of the underlying data. ⋯ These tools enable the visualization of proteins as networks of signaling, regulatory, and biochemical interactions. In this chapter, we provide an overview of networks and network theory fundamentals for the analysis of proteomics data. We further provide an overview of interaction databases and network tools which are frequently used for analyzing proteomics data.
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The protocol herein describes a robust and proven method for the measurement of pseudokinase-ligand interaction using a fluorescence-based thermal shift assay (TSA). Pseudokinases are kinase-like proteins that have recently emerged as crucial regulatory modules of signal transduction pathways and may well represent a novel class of drug targets. However, unlike kinases, the regulatory activity of pseudokinases is mainly conferred through protein-protein interactions. ⋯ Ligand binding to a protein is known to increase its thermal stability, which is reflected by a shift between the thermal denaturation curves of the unliganded protein and the liganded protein. Here, we illustrate the utility of the method with the pseudokinases, ErbB3/HER3, ILK, ROP5Bi, JAK1, JAK2, TYK2, MLKL, STRAD, TRIB1, VRK3, and ROR1. This method can also be used to determine optimal buffer conditions that may increase protein stability and can be tailored to other protein families.