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Complete De Novo Assembly of Monoclonal Antibody Sequences

Authors: Ngoc Hieu Tran; M. Ziaur Rahman; Lin He; Lei Xin; Baozhen Shan; Ming Li;

Complete De Novo Assembly of Monoclonal Antibody Sequences

Abstract

AbstractDe novo protein sequencing is one of the key problems in mass spectrometry-based proteomics, especially for novel proteins such as monoclonal antibodies for which genome information is often limited or not available. However, due to limitations in peptides fragmentation and coverage, as well as ambiguities in spectra interpretation, complete de novo assembly of unknown protein sequences still remains challenging. To address this problem, we propose an integrated system, ALPS, which for the first time can automatically assemble full-length monoclonal antibody sequences. Our system integrates de novo sequencing peptides, their quality scores and error-correction information from databases into a weighted de Bruijn graph to assemble protein sequences. We evaluated ALPS performance on two antibody data sets, each including a heavy chain and a light chain. The results show that ALPS was able to assemble three complete monoclonal antibody sequences of length 216–441 AA, at 100% coverage and 96.64–100% accuracy.

Related Organizations
Keywords

Glycosylation, Sequence Homology, Amino Acid, Antibodies, Monoclonal, Computational Biology, Metalloendopeptidases, Reproducibility of Results, Article, Automation, Contig Mapping, Sequence Analysis, Protein, Tandem Mass Spectrometry, Immunoglobulin G, Animals, Chymotrypsin, Humans, Muramidase, Trypsin, Amino Acids, Peptides, Chickens, Chromatography, Liquid

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    119
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
119
Top 1%
Top 10%
Top 10%
Green
gold