Citation: ZHENG Nai-Ren, SHAN Yi-Chu, DENG Yu-Lin, ZHANG Yu-Kui. Novel Algorithm for Identification and Quantification of Proteins Based on Strategy of Isobaric Peptide Termini Labelling[J]. Chinese Journal of Analytical Chemistry, ;2017, 45(10): 1441-1447. doi: 10.11895/j.issn.0253-3820.170250 shu

Novel Algorithm for Identification and Quantification of Proteins Based on Strategy of Isobaric Peptide Termini Labelling

1.
School of Life Science, Beijing Institute of Technology, Beijing 100081, China;2 Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116011, China

Received Date: 20 April 2017
Revised Date: 29 August 2017

Fund Project: This work was supported by the National Major Scientific Instruments and Equipments Special Project (No. 2012YQ04014005).

Isobaric peptide termini labeling (IPTL) is a technology which uses light and heavy isotopes to label C-terminus and N-terminus of peptides. As the masses of labeled peptides are equivalent, the complexity of sample is low when analyzing MS data produced by this technology. Besides, paired b and y ions are helpful while analyzing MS/MS data in this kind of experiments. On the basis of this, a novel scoring algorithm, all ions scoring algorithm (AISA), has been designed for IPTL experiments. The information of quantification and qualification can be acquired at the same time using AISA. On Q-Exactive HeLa 2D RPLC dataset, peptide spectrum matches (PSMs), distinct peptides and protein groups identified by AISA are 15%, 26% and 22% higher than Morpheus. On human-HCC-HL dataset, PSMs, distinct peptides and protein groups identified by AISA are 24%, 39% and 27% higher than Morpheus. Quantification ratio on Q-Exactive HeLa and human-HCC-HL datasets are 1.18 and 0.90, respectively, which are very close to 1. Besides, quantification ratios between 0.5 and 2.0 are 91% and 94%, respectively.
- Proteomics,
- Isobaric labeling,
- Identification of proteins
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沈阳化工大学材料科学与工程学院沈阳 110142