Informatics View
on the Challenges of Identifying
Missing Proteins from Shotgun Proteomics
Version 2 2016-11-09, 09:14Version 2 2016-11-09, 09:14
Version 1 2016-02-12, 08:11Version 1 2016-02-12, 08:11
Posted on 2015-12-04 - 00:00
Protein
experiment evidence at protein level from mass spectrometry
and antibody experiments are essential to characterize the human proteome.
neXtProt (2014-09 release) reported 20 055 human proteins,
including 16 491 proteins identified at protein level and 3564
proteins unidentified. Excluding 616 proteins at uncertain level,
2948 proteins were regarded as missing proteins. Missing proteins
were unidentified partially due to MS limitations and intrinsic properties
of proteins, for example, only appearing in specific diseases or tissues.
Despite such reasons, it is desirable to explore issues affecting
validation of missing proteins from an “ideal” shotgun
analysis of human proteome. We thus performed in silico digestions
on the human proteins to generate all in silico fully digested peptides.
With these presumed peptides, we investigated the identification of
proteins without any unique peptide, the effect of sequence variants
on protein identification, difficulties in identifying olfactory receptors,
and highly similar proteins. Among all proteins with evidence at transcript
level, G protein-coupled receptors and olfactory receptors, based
on InterPro classification, were the largest families of proteins
and exhibited more frequent variants. To identify missing proteins,
the above analyses suggested including sequence variants in protein
FASTA for database searching. Furthermore, evidence of unique peptides
identified from MS experiments would be crucial for experimentally
validating missing proteins.
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Choong, Wai-Kok; Chang, Hui-Yin; Chen, Ching-Tai; Tsai, Chia-Feng; Hsu, Wen-Lian; Chen, Yu-Ju; et al. (2016). Informatics View
on the Challenges of Identifying
Missing Proteins from Shotgun Proteomics. ACS Publications. Collection. https://doi.org/10.1021/acs.jproteome.5b00482