Speeding up tandem mass spectrometry based database searching by peptide and spectrum indexing.
Database searching is the technique of choice for shotgun proteomics, and to date much research effort has been spent on improving its effectiveness. However, database searching faces a serious challenge of efficiency, considering the large numbers of mass spectra and the ever fast increase in peptide databases resulting from genome translations, enzymatic digestions, and post-translational modifications. In this study, we conducted systematic research on speeding up database search engines for protein identification and illustrate the key points with the specific design of the pFind 2.1 search engine as a running example. Firstly, by constructing peptide indexes, pFind achieves a speedup of two to three compared with that without peptide indexes. Secondly, by constructing indexes for observed precursor and fragment ions, pFind achieves another speedup of two. As a result, pFind compares very favorably with predominant search engines such as Mascot, SEQUEST and X!Tandem.
Li
You
Y
Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.
Chi
Hao
H
Wang
Le-Heng
LH
Wang
Hai-Peng
HP
Fu
Yan
Y
Yuan
Zuo-Fei
ZF
Li
Su-Jun
SJ
Liu
Yan-Sheng
YS
Sun
Rui-Xiang
RX
Zeng
Rong
R
He
Si-Min
SM
D000465:Algorithms; D001798:Blood Proteins / Q000737:chemistry; D003198:Computer Simulation; D057225:Data Mining / Q000379:methods*; D003628:Database Management Systems; D030562:Databases, Protein; D005656:Fungal Proteins / Q000737:chemistry; D006801:Humans; D010446:Peptide Fragments / Q000737:chemistry*; D011506:Proteins / Q000737:chemistry*; D040901:Proteomics / Q000379:methods; D053719:Tandem Mass Spectrometry / Q000379:methods*
D001798:Blood Proteins; D005656:Fungal Proteins; D010446:Peptide Fragments; D011506:Proteins