PROTEIN IDENTIFICATION USING SEQUENCE DATABASES

Scientific Journal of Astana IT University, 2020

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.37943/aitu.2020.91.98.002
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

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