MASPIC:  Intensity-Based Tandem Mass Spectrometry Scoring Scheme That Improves Peptide Identification at High Confidence

Algorithmic search engines bridge the gap between large tandem mass spectrometry data sets and the identification of proteins associated with biological samples. Improvements in these tools can greatly enhance biological discovery. We present a new scoring scheme for comparing tandem mass spectra wi...

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Bibliographic Details
Published in:Analytical chemistry (Washington) 2005-12, Vol.77 (23), p.7581-7593
Main Authors: Narasimhan, Chandrasegaran, Tabb, David L, VerBerkmoes, Nathan C, Thompson, Melissa R, Hettich, Robert L, Uberbacher, Edward C
Format: Article
Language:English
Subjects:
ALGORITHMS
Amino Acid Sequence
Analytical chemistry
BASIC BIOLOGICAL SCIENCES
Chemistry
DATA PROCESSING
DISTRIBUTION
Endopeptidase K - chemistry
Endopeptidase K - metabolism
Exact sciences and technology
MASS SPECTRA
MASS SPECTROSCOPY
Methods
MIXTURES
Molecular Sequence Data
PEPTIDES
Peptides - analysis
Peptides - chemistry
PROBABILITY
PROTEINS
RHODOPSEUDOMONAS
Rhodopseudomonas - chemistry
Ribosomes - chemistry
Scientific imaging
SPECTRA
Spectrometric and optical methods
Tandem Mass Spectrometry - methods
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Summary:Algorithmic search engines bridge the gap between large tandem mass spectrometry data sets and the identification of proteins associated with biological samples. Improvements in these tools can greatly enhance biological discovery. We present a new scoring scheme for comparing tandem mass spectra with a protein sequence database. The MASPIC (Multinomial Algorithm for Spectral Profile-based Intensity Comparison) scorer converts an experimental tandem mass spectrum into a m/z profile of probability and then scores peak lists from potential candidate peptides using a multinomial distribution model. The MASPIC scoring scheme incorporates intensity, spectral peak density variations, and m/z error distribution associated with peak matches into a multinomial distribution. The scoring scheme was validated on two standard protein mixtures and an additional set of spectra collected on a complex ribosomal protein mixture from Rhodopseudomonas palustris. The results indicate a 5−15% improvement over Sequest for high-confidence identifications. The performance gap grows as sequence database size increases. Additional tests on spectra from proteinase-K digest data showed similar performance improvements demonstrating the advantages in using MASPIC for studying proteins digested with less specific proteases. All these investigations show MASPIC to be a versatile and reliable system for peptide tandem mass spectral identification.
ISSN:0003-2700
1520-6882
DOI:10.1021/ac0501745