Optimization of Bioinformatics Analysis Conditions by Peptide Mass Fingerprint Identify Proteins

The bioinformatics analysis conditions (databases and major parameters) in the process of Peptide Mass Fingerprint (PMF) identify target proteins were optimized in this study. In this process of experiment design and analysis, the Bovine Carbonic anhydrase-2 (CAH2_BOVIN) and human Hsp70s protein (Heat shock protein 70) were separated by two-dimension electrophoresis(2-DE), proteolysis by Trypsin Gold, and then the lysed peptides were gathered and analyzed using MALDI-TOF-MS, and the peptides mass data and mass spectrogram were obtained. In this study, the Swissprot, MSDB, NCBInr, Random databases, MASCOT, and MS-Fit were selected as search engines, and the standard CAH2_BOVIN was used as model to set up protein search standard conditions. Results show that Swissprot is the better database for protein PMF study, the better missed cleavage is one site, the better peptide tolerance is ±1 Da, and average peptide mass type is better than monoisotopic type to get target proteins. Then human Hsp70s protein mass data was used as sample to check the accuracy of MS search standard conditions. Results show that the optimized databases and parameters are reliable.