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Ghost proteins are issued from alternative Open Reading Frames (ORFs) and are missing a genome annotation. Indeed, historical filters applied for the detection of putative translated ORFs led to a wrong classification of transcripts considered as non-coding although translated proteins can be detected by proteomics. This Ghost (also called Alternative) proteome was neglected, and one major issue is to identify the implication of the Ghost proteins in the biological processes. In this context, we aimed to identify the protein-protein interactions (PPIs) of the Ghost proteins. For that, we re-explored a cross-link MS study performed on nuclei of HeLa cells using cross-linking mass spectrometry (XL-MS) associated with the HaltOrf database. Among 1679 cross-link interactions identified, 292 are involving Ghost Proteins. Forty-Four of these Ghost proteins are found to interact with 7 Reference proteins related to ribonucleoproteins, ribosome subunits and zinc finger proteins network. We, thus, have focused our attention on the heterotrimer between the RE/poly(U)-binding/degradation factor 1 (AUF1), the Ribosomal protein 10 (RPL10) and AltATAD2. Using I-Tasser software we performed docking models from which we could suggest the attachment of AUF1 on the external part of RPL10 and the interaction of AltATAD2 on the RPL10 region interacting with 5S ribosomal RNA as a mechanism of regulation of the ribosome. Taken together, these results reveal the importance of Ghost Proteins within known protein interaction networks.
Pubmed ID: 31128158
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Software application that finds starting points for MCMC analysis performed on large, complex pedigrees and polymorphic markers. (entry from Genetic Analysis Software)
View all literature mentionsWeb server as integrated platform for automated protein structure and function prediction. Used for protein 3D structure prediction. Resource for automated protein structure prediction and structure-based function annotation.
View all literature mentionsWeb tool for protein-protein docking. Server provides removal of unstructured protein regions, application of attraction or repulsion, accounting for pairwise distance restraints, construction of homo-multimers, consideration of small-angle X-ray scattering data, and location of heparin-binding sites. Six different energy functions can be used, depending on protein type.This protocol describes use of various options, construction of auxiliary restraints files, selection of energy parameters, and analysis of results.
View all literature mentionsPercolator post-processes the results of a shotgun proteomics database search program, re-ranking peptide-spectrum matches so that the top of the list is enriched for correct matches. Shotgun proteomics uses liquid chromatography-tandem mass spectrometry to identify proteins in complex biological samples. We describe an algorithm, called Percolator, for improving the rate of peptide identifications from a collection of tandem mass spectra. Percolator uses semi-supervised machine learning to discriminate between correct and decoy spectrum identifications, correctly assigning peptides to 17% more spectra from a tryptic dataset and up to 77% more spectra from non-tryptic digests, relative to a fully supervised approach. The yeast-01 data is available in tab delimetered format. The SEQUEST parameter file and target database for the yeast and worm data are also available.
View all literature mentionsCell line HeLa is a Cancer cell line with a species of origin Homo sapiens
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