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Topograph, a Software Platform for Precursor Enrichment Corrected Global Protein Turnover Measurements
Journal article   Open access   Peer reviewed

Topograph, a Software Platform for Precursor Enrichment Corrected Global Protein Turnover Measurements

Edward J Hsieh, Nicholas J Shulman, Dao-Fu Dai, Evelyn S Vincow, Pabalu P Karunadharma, Leo Pallanck, Peter S Rabinovitch and Michael J MacCoss
Molecular & cellular proteomics, Vol.11(11), pp.1468-1474
11/2012
DOI: 10.1074/mcp.O112.017699
PMCID: PMC3494182
PMID: 22865922
url
https://doi.org/10.1074/mcp.O112.017699View
Published (Version of record) Open Access

Abstract

Defects in protein turnover have been implicated in a broad range of diseases, but current proteomics methods of measuring protein turnover are limited by the software tools available. Conventional methods require indirect approaches to differentiate newly synthesized protein when synthesized from partially labeled precursor pools. To address this, we have developed Topograph, a software platform which calculates the fraction of peptides that are from newly synthesized proteins and their turnover rates. A unique feature of Topograph is the ability to calculate amino acid precursor pool enrichment levels which allows for accurate calculations when the precursor pool is not fully labeled, and the approach used by Topograph is applicable regardless of the stable isotope label used. We validate the Topograph algorithms using data acquired from a mouse labeling experiment and demonstrate the influence that precursor pool corrections can have on protein turnover measurements.
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