1-21-2011 Identifying complex patterns of PTMs and Un-targeted database search

Guan, S, Burlingame, AL (2010). Data processing algorithms for analysis of high resolution MSMS spectra of peptides with complex patterns of posttranslational modifications. Mol. Cell Proteomics, 9, 5:804-10.

Aim: For a given Spectrum, Peptide, and set of PTMs, find a subset of plausible PTM modified peptide configurations and their relative abundances.

Achievements: 

- Greedy algorithm, repeatedly selects maximum scoring plausible PTM configurations from set of all possible configurations. 

- Relative Abundance is computed by minimizing the least square error of theoretical peak intensity based on configuration abundance and empirical intensity.

Responses:

- May not consider very similar configurations

- Will not handle overlapping peaks.

- A first attempt solution, where improvements can be made.

- Validation was lacking/non-existent.

Baliban, RC, DiMaggio, PA, Plazas-Mayorca, MD, Young, NL, Garcia, BA, Floudas, CA (2010). A novel approach for untargeted post-translational modification identification using integer linear optimization and tandem mass spectrometry. Mol. Cell Proteomics, 9, 5:764-79.

Aim: For a given Spectrum and x peptides, identify the PTM and localization. (With the implicit assumption that unrestricted search means a large set of plausible PTMs)

Achievements:

- ILP formulation of the problem to output candidate PTM-peptide matches with post-finagling to acquire best modified peptide matches

- Results appear excellent, with comparison to other tools.

- 5 distinct mass spec datasets.

Critiques:

- Good preprocessing policy.

- Reduce spectra to "b" ions only. This policy varies upon instrument.

- Strategy is slow, but the accuracy of results compensates.

- Unclear what "manual validation" means.

 

Speaker: Xiaowen

Scribe: Anand

Slides: here