Literature DB >> 29202576

Poisson Model To Generate Isotope Distribution for Biomolecules.

Rovshan G Sadygov1.   

Abstract

We introduce a simplified computational algorithm for computing isotope distributions (relative abundances and masses) of biomolecules. The algorithm is based on Poisson approximation to binomial and multinomial distributions. It leads to a small number of arithmetic operations to compute isotope distributions of molecules. The approach uses three embedded loops to compute the isotope distributions, as compared with the eight embedded loops in exact calculations. The speed improvement is about 3-fold compared to the fast Fourier transformation-based isotope calculations, often termed as ultrafast isotope calculation. The approach naturally incorporates the determination of the masses of each molecular isotopomer. It is applicable to high mass accuracy and resolution mass spectrometry data. The application to tryptic pan class="Chemical">peptides in a UniProt protein database revealed that the mass accuracy of the computed isotopomers is better than 1 ppm. Even better mass accuracy (below 1 ppm) is achievable when the method is class="Chemical">paired with the exact calculations, which we term a hybrid approach. The algorithms have been implemented in a freely available C/C++ code.

Entities:  

Keywords:  Poisson distribution; isotope envelope; mass spectrometry; stable isotope labeling

Mesh:

Year:  2017        PMID: 29202576      PMCID: PMC5789464          DOI: 10.1021/acs.jproteome.7b00807

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  32 in total

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9.  Decimal place slope, a fast and precise method for quantifying 13C incorporation levels for detecting the metabolic activity of microbial species.

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10.  DeuteRater: a tool for quantifying peptide isotope precision and kinetic proteomics.

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  2 in total

1.  Proteome Dynamics from Heavy Water Metabolic Labeling and Peptide Tandem Mass Spectrometry.

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2.  Protein turnover models for LC-MS data of heavy water metabolic labeling.

Authors:  Rovshan G Sadygov
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  2 in total

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