Open AccessPROTEIN IDENTIFICATION USING SEQUENCE DATABASES
Author(s) -
Y. S. Golenko,
Aisulu Ismailova,
Ye Rais
Publication year - 2020
Publication title -
scientific journal of astana it university
Language(s) - English
Resource type - Journals
eISSN - 2707-904X
pISSN - 2707-9031
DOI - 10.37943/aitu.2020.91.98.002
Subject(s) - shotgun proteomics , database search engine , computer science , sequence database , identification (biology) , workflow , bottom up proteomics , database , mascot , proteomics , data mining , sequence (biology) , tandem mass spectrometry , protein sequencing , information retrieval , computational biology , peptide sequence , mass spectrometry , search engine , chemistry , biology , protein mass spectrometry , chromatography , biochemistry , botany , political science , law , gene
The bottom-up proteomics approach (also known as the shotgun approach), based on the digestion of proteins in peptides and their sequencing using tandem mass spectrometry (MS/MS), has become widespread. The identification of peptides from the obtained MS/MS data is most often done using available sequence databases. In this paper, we present a detailed overview of the peptide identification workflow and description of the main protein bioinformatics databases. Choosing the correct search parameters and the sequence database is essential to the success of this method, and we pay special attention to the practical aspects of searching for efficient analysis of MS/MS spectra. We also consider possible reasons why database search tools cannot find the correct sequence for some MS/MS spectra, and highlight the issues of misidentification that can significantly reduce the value of published data. To help assess the assignment of peptides to MS/MS spectra, we will look at the scoring algorithms that are used in the most popular database search tools. We also analyze statistical methods and computational tools for validating peptide compliance with MS/MS data. The final part describes the process of determining the identity of protein samples from a list of peptide identifications and discusses the limitations of bottom-up proteomics