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Shotgun Protein Sequencing

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Algorithms in Bioinformatics (WABI 2007)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 4645))

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Abstract

Despite significant advances in the identification of known proteins, the analysis of unknown proteins by tandem mass spectrometry (MS/MS) still remains a challenging open problem. Although Klaus Biemann recognized the potential of mass spectrometry for sequencing of unknown proteins in the 1980s, low-throughput Edman degradation followed by cloning still remains the main method to sequence unknown proteins. The automated spectral interpretation has been limited by a focus on individual spectra and has not capitalized on the information contained in spectra of overlapping peptides. Indeed, the powerful Shotgun DNA Sequencing strategies have not been extended to protein sequencing yet.We demonstrate, for the first time, the feasibility of Shotgun Protein Sequencing of protein mixtures and validate this approach by generating highly accurate de novo reconstructions of various proteins in western diamondback rattlesnake venom. We further argue that Shotgun Protein Sequencing has the potential to overcome the limitations of current protein sequencing approaches and thus catalyze the otherwise impractical applications of proteomics methodologies in studies of unknown proteins. We further describe applications of this technique to analyzing proteins that are not directly inscribed in DNA sequences (like antibodies and fusion proteins in cancer).

This is a joint work with Nuno Bandeira (UCSD) and Karl Clauser (Broad).

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Raffaele Giancarlo Sridhar Hannenhalli

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© 2007 Springer-Verlag Berlin Heidelberg

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Pevzner, P.A. (2007). Shotgun Protein Sequencing . In: Giancarlo, R., Hannenhalli, S. (eds) Algorithms in Bioinformatics. WABI 2007. Lecture Notes in Computer Science(), vol 4645. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74126-8_1

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  • DOI: https://doi.org/10.1007/978-3-540-74126-8_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74125-1

  • Online ISBN: 978-3-540-74126-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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