ITTC Project

K-INBRE: Complete, Upgrade and Enhance Data Handling in the Analytical Proteomics Laboratory

Project Award Date: 06-26-2007


Researchers will refine preliminary software designed to generate statistically justifiable and robust protein identifications especially for the KU investigators looking at targeted proteomes of 100s to 1000s proteins, e.g. Mitochondrial, Lipid Rafts, Liver Microsomes, Protein-Protein interaction pull downs
-- Current research will be used to validate peptide hits by the calculation of parameters matching the training set. This will improve robustness of PMF from 4700 data.
-- Build the "Inverse" data base for the determination of false hits and thus reliability of searches. This project will formalize the utilization of SeQuest, along with Mascot and X!Tandem to obtain Scaffold processed valid hits.
-- Adapt 4700 ms/ms data to scaffold data stream.

Protein Mapping
Propose a variety of refinement tasks including:
-- Improve custom database generation to allow search engines to assign amino acid substitutions, PTMs or non-specific cleavage assignments to the unassigned spectra in a data set. Included would be a systematic way to identify and exclude contamination proteins.
-- Adapt MSQuant software or develop custom tools with the primary MS data system to process LC/MS 1 data for quantitation by SILAC or peptide/protein internal standard introduction.
-- Continue "processing of high performance" MS 1 data for improved protein coverage and ill of trace components. Project findings were reported in a 2006 ASMS poster.

Signal Processing
Propose a variety of refinement tasks including:
-- Develop a search filter to exclude MS/MS data that are not peptidic (a set of criteria have been published) including developing a library of contaminating spectra (NOT proteins, e.g. detergents, phthalates buffer and salt clusters)
-- Adapt an existing filter routine for MS 1 data that falls outside of the required "mass defect space" (the subject of a recent JASMS publication). The resulting routine would be applicable to both MALDI and high resolution ESI data.


Faculty Investigator(s): Gerald Lushington (PI), Jianwen Fang

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