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Flying blind, or just flying under the radar? The underappreciated power of de novo methods of mass spectrometric peptide identification
Author(s) -
O'Bryon Isabelle,
Jenson Sarah C.,
Merkley Eric D.
Publication year - 2020
Publication title -
protein science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.353
H-Index - 175
eISSN - 1469-896X
pISSN - 0961-8368
DOI - 10.1002/pro.3919
Subject(s) - proteogenomics , computational biology , identification (biology) , proteomics , tandem mass spectrometry , computer science , genome , database search engine , sequence assembly , peptide mass fingerprinting , sequence database , sequence (biology) , bottom up proteomics , mass spectrometry , biology , genomics , chemistry , genetics , gene , search engine , protein mass spectrometry , information retrieval , chromatography , botany , transcriptome , gene expression
Mass spectrometry‐based proteomics is a popular and powerful method for precise and highly multiplexed protein identification. The most common method of analyzing untargeted proteomics data is called database searching, where the database is simply a collection of protein sequences from the target organism, derived from genome sequencing. Experimental peptide tandem mass spectra are compared to simplified models of theoretical spectra calculated from the translated genomic sequences. However, in several interesting application areas, such as forensics, archaeology, venomics, and others, a genome sequence may not be available, or the correct genome sequence to use is not known. In these cases, de novo peptide identification can play an important role. De novo methods infer peptide sequence directly from the tandem mass spectrum without reference to a sequence database, usually using graph‐based or machine learning algorithms. In this review, we provide a basic overview of de novo peptide identification methods and applications, briefly covering de novo algorithms and tools, and focusing in more depth on recent applications from venomics, metaproteomics, forensics, and characterization of antibody drugs.