Abstract
In shotgun proteomics, proteins can be fractionated by 1-D gel electrophoresis and digested into peptides, followed by liquid chromatography to separate the peptide mixture. Mass spectrometry generates hundreds of thousands of tandem mass spectra from these fractions, and proteins are identified by database searching. However, the search scores are usually not sufficient to distinguish the correct peptides. In this study, we propose a confident protein identification method for high-throughput analysis of human proteome. To build a filtering protocol in database search, we chose Pseudomonas putida KT2440 as a reference because this bacterial proteome contains fewer modifications and is simpler than the human proteome. First, the P. putida KT2440 proteome was filtered by reversed sequence database search and correlated by the molecular weight in 1-D-gel band positions. The characterization protocol was then applied to determine the criteria for clustering of the human plasma proteome into three different groups. This protein filtering method, based on bacterial proteome data analysis, represents a rapid way to generate higher confidence protein list of the human proteome, which includes some of heavily modified and cleaved proteins.
| Original language | English |
|---|---|
| Pages (from-to) | 1121-1132 |
| Number of pages | 12 |
| Journal | Proteomics |
| Volume | 6 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2006 Feb 1 |
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All Science Journal Classification (ASJC) codes
- Biochemistry
- Molecular Biology
Cite this
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Human plasma proteome analysis by reversed sequence database search and molecular weight correlation based on a bacterial proteome analysis. / Park, Gun Wook; Kwon, Kyung Hoon; Kim, Jin Young; Lee, Jeong Hwa; Yun, Sung Ho; Kim, Seung Il; Park, Young Mok; Cho, Sang Yun; Paik, Young-Ki; Yoo, Jong Shin.
In: Proteomics, Vol. 6, No. 4, 01.02.2006, p. 1121-1132.Research output: Contribution to journal › Article
TY - JOUR
T1 - Human plasma proteome analysis by reversed sequence database search and molecular weight correlation based on a bacterial proteome analysis
AU - Park, Gun Wook
AU - Kwon, Kyung Hoon
AU - Kim, Jin Young
AU - Lee, Jeong Hwa
AU - Yun, Sung Ho
AU - Kim, Seung Il
AU - Park, Young Mok
AU - Cho, Sang Yun
AU - Paik, Young-Ki
AU - Yoo, Jong Shin
PY - 2006/2/1
Y1 - 2006/2/1
N2 - In shotgun proteomics, proteins can be fractionated by 1-D gel electrophoresis and digested into peptides, followed by liquid chromatography to separate the peptide mixture. Mass spectrometry generates hundreds of thousands of tandem mass spectra from these fractions, and proteins are identified by database searching. However, the search scores are usually not sufficient to distinguish the correct peptides. In this study, we propose a confident protein identification method for high-throughput analysis of human proteome. To build a filtering protocol in database search, we chose Pseudomonas putida KT2440 as a reference because this bacterial proteome contains fewer modifications and is simpler than the human proteome. First, the P. putida KT2440 proteome was filtered by reversed sequence database search and correlated by the molecular weight in 1-D-gel band positions. The characterization protocol was then applied to determine the criteria for clustering of the human plasma proteome into three different groups. This protein filtering method, based on bacterial proteome data analysis, represents a rapid way to generate higher confidence protein list of the human proteome, which includes some of heavily modified and cleaved proteins.
AB - In shotgun proteomics, proteins can be fractionated by 1-D gel electrophoresis and digested into peptides, followed by liquid chromatography to separate the peptide mixture. Mass spectrometry generates hundreds of thousands of tandem mass spectra from these fractions, and proteins are identified by database searching. However, the search scores are usually not sufficient to distinguish the correct peptides. In this study, we propose a confident protein identification method for high-throughput analysis of human proteome. To build a filtering protocol in database search, we chose Pseudomonas putida KT2440 as a reference because this bacterial proteome contains fewer modifications and is simpler than the human proteome. First, the P. putida KT2440 proteome was filtered by reversed sequence database search and correlated by the molecular weight in 1-D-gel band positions. The characterization protocol was then applied to determine the criteria for clustering of the human plasma proteome into three different groups. This protein filtering method, based on bacterial proteome data analysis, represents a rapid way to generate higher confidence protein list of the human proteome, which includes some of heavily modified and cleaved proteins.
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U2 - 10.1002/pmic.200500318
DO - 10.1002/pmic.200500318
M3 - Article
VL - 6
SP - 1121
EP - 1132
JO - Proteomics
JF - Proteomics
SN - 1615-9853
IS - 4
ER -