A new scoring function for top-down spectral deconvolution
- Indiana Univ.-Purdue Univ. Indianapolis, Indianapolis, IN (United States)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Indiana Univ. School of Medicine, Indianapolis, IN (United States)
Background: Top-down mass spectrometry plays an important role in intact protein identification and characterization. Top-down mass spectra are more complex than bottom-up mass spectra because they often contain many isotopomer envelopes from highly charged ions, which may overlap with one another. As a result, spectral deconvolution, which converts a complex top-down mass spectrum into a monoisotopic mass list, is a key step in top-down spectral interpretation. Results: In this paper, we propose a new scoring function, L-score, for evaluating isotopomer envelopes. By combining L-score with MS-Deconv, a new software tool, MS-Deconv+, was developed for top-down spectral deconvolution. Experimental results showed that MS-Deconv+ outperformed existing software tools in top-down spectral deconvolution. Conclusions: L-score shows high discriminative ability in identification of isotopomer envelopes. Using L-score, MS-Deconv+ reports many correct monoisotopic masses missed by other software tools, which are valuable for proteoform identification and characterization.
- Research Organization:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
- Grant/Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1207277
- Journal Information:
- BMC Genomics, Journal Name: BMC Genomics Journal Issue: 1 Vol. 15; ISSN 1471-2164
- Publisher:
- SpringerCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Approximating Isotope Distributions of Biomolecule Fragments
|
journal | September 2018 |
Informed-Proteomics: open-source software package for top-down proteomics
|
journal | August 2017 |
Deconvolution in mass spectrometry based proteomics
|
journal | April 2018 |
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