<p>A few notes on data generation first:</p>
<p>There are currently two broad approaches for the generation of bottom-up or &quot;shotgun&quot; MS proteomics: data-dependent acquisition (DDA) and data-independent acquisition (DIA).1 In tandem MS (MS/MS), the DDA approach only puts forward certain peptides generated during the first cycle of MS for fragmentation during the second cycle, while with the DIA approach, all peptides generated during the first MS cycle can be fragmented in the second round.</p>
<p>The recently-introduced Orbitrap Fusion mass spectrometry permits various types of MS2 acquisition methods. There are four main MS2 strategies:</p>
<ul>
<li><p>HCD-OT (higher-energy-collisional-dissociation with Orbitrap detection),</p>
</li>
<li><p>HCD-IT (HCD with ion trap, IT),</p>
</li>
<li><p>CID-IT (collision-induced-dissociation with IT) and</p>
</li>
<li><p>CID-OT on Orbitrap Fusion</p>
</li>
</ul>
<p>Reading from the biorxiv preprint of Stitch:</p>
<p><a href="https://www.biorxiv.org/content/10.1101/2022.03.07.483237v1" rel="nofollow noreferrer">https://www.biorxiv.org/content/10.1101/2022.03.07.483237v1</a></p>
<p>&quot;With the aid of specialized software packages like DiPS, Supernovo, or ALPS, full and accurate sequences of the heavy and light chains can be reconstructed with the MS/MS spectra of the digested peptides.&quot;</p>
<p>Before running Stitch or similar tools, a peptide profiling tool needs to be executed on the .raw or .mgf data alone.</p>
<p>STITCH: <a href="https://www.biorxiv.org/content/10.1101/2022.03.07.483237v2" rel="nofollow noreferrer">https://www.biorxiv.org/content/10.1101/2022.03.07.483237v2</a></p>
<p>This currently requires the output of analysing .raw data via PEAKS, which is not free unfortunately. Authors currently looking into using other free de novo sequencing software for input into Stitch. The software also allows for FASTA format, which can then be executed on the output of PepNovo, Novor or similar.</p>
<p>DiPS: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5461544/" rel="nofollow noreferrer">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5461544/</a></p>
<p>ALPS: <a href="https://www.nature.com/articles/srep31730" rel="nofollow noreferrer">https://www.nature.com/articles/srep31730</a></p>
<p>&quot;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.&quot;</p>
<p>DeepNovo: <a href="https://www.pnas.org/doi/10.1073/pnas.1705691114" rel="nofollow noreferrer">https://www.pnas.org/doi/10.1073/pnas.1705691114</a></p>
<p>&quot;This field has been actively studied over the past 20 y, and many de novo sequencing tools have been proposed, such as PepNovo, PEAKS, NovoHMM, MSNovo, pNovo, UniNovo, and Novor among others (6–19). The recent &quot;gold rush&quot; into mAbs has undoubtedly elevated the application of de novo sequencing to a new horizon (20–23)&quot;</p>
<p>&quot;DeepNovo considerably outperformed state of the art methods, achieving 7.7–22.9% higher accuracy at the amino acid level and 38.1–64.0% higher accuracy at the peptide level&quot;</p>
<p>Available for download, requires activation via sending email to author, which then points to the company behind PEAKS, which will give you a 15 day evaluation license.</p>
<p>NovoHMM: the download page leads to a missing URL</p>
<p>DeepResolution2: <a href="https://www.sciencedirect.com/science/article/abs/pii/S0039914022002119" rel="nofollow noreferrer">https://www.sciencedirect.com/science/article/abs/pii/S0039914022002119</a></p>
<p>Capable of analyzing GC-MS data rather than MS/MS Ion Trap</p>
<p>DePS: <a href="https://arxiv.org/abs/2203.08820" rel="nofollow noreferrer">https://arxiv.org/abs/2203.08820</a></p>
<p>DeepNovoV2: <a href="https://github.com/volpato30/DeepNovoV2" rel="nofollow noreferrer">https://github.com/volpato30/DeepNovoV2</a></p>
<p>DPST: <a href="https://arxiv.org/abs/2203.13132" rel="nofollow noreferrer">https://arxiv.org/abs/2203.13132</a></p>
<p>Link does not work <a href="https://github.com/Yan98/DPST" rel="nofollow noreferrer">https://github.com/Yan98/DPST</a></p>
<p>PepNovo: <a href="http://proteomics.ucsd.edu/software-tools/531-2/" rel="nofollow noreferrer">http://proteomics.ucsd.edu/software-tools/531-2/</a></p>
<p>The new version is from 2012, includes models for CID and LTQ, but not HCD models.</p>
<p>pNovo: <a href="http://pfind.org/" rel="nofollow noreferrer">http://pfind.org/</a></p>
<p>Includes models for CID, HCD, ETD and HCD+ETD.</p>
<p>Novor: <a href="https://www.rapidnovor.com/" rel="nofollow noreferrer">https://www.rapidnovor.com/</a></p>
<p>Filling in a form, someone will contact you. Doesn't seem to be free.</p>
<p>METHODOLOGY used so far:</p>
<p>1 - ThermoRawFileParser: Convert .raw data to .gcf</p>
<p>2 - PepNovo: produce list of peptides, one-liner to convert to .fasta</p>
<p>3 - Stitch: analyse given a list of V(D)J+C references from templates and the .fasta file from above.</p>

CC BY-SA 4.0
2022-04-04T10:19:26.350Z
2022-04-11T08:40:22.147Z
2022-04-11T08:40:22.147Z
719016
<p>I've read about different proteomics tools that can do de novo assembly of MS/MS Ion Trap proteomics signatures for de novo antibody sequencing. Given the way CDR3s of antibodies are created, together with Somatic Hypermutation, can generate a huge diversity in the CDR regions of the heavy and light chains, the reference-based methods can fall short of determining the full sequence of an unknown antibody without a set of reference sequences including those with its CDRs.</p>
<p>Are there any other tools that can determine antibody sequences from MS/MS proteomics raw signals?</p>

<machine-learning><proteomics>
De novo antibody sequencing fromMS/MS Ion Trap proteomics raw signal
# De novo antibody sequencing fromMS/MS Ion Trap proteomics raw signal

(Asked by: username_0 on 2022-04-04)

I've read about different proteomics tools that can do de novo assembly of MS/MS Ion Trap proteomics signatures for de novo antibody sequencing. Given the way CDR3s of antibodies are created, together with Somatic Hypermutation, can generate a huge diversity in the CDR regions of the heavy and light chains, the reference-based methods can fall short of determining the full sequence of an unknown antibody without a set of reference sequences including those with its CDRs.

Are there any other tools that can determine antibody sequences from MS/MS proteomics raw signals?

**Tags:** machine-learning, proteomics

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## 1 answers

### Answer by username_0 on 2022-04-04. Score: 2

A few notes on data generation first:

There are currently two broad approaches for the generation of bottom-up or "shotgun" MS proteomics: data-dependent acquisition (DDA) and data-independent acquisition (DIA).1 In tandem MS (MS/MS), the DDA approach only puts forward certain peptides generated during the first cycle of MS for fragmentation during the second cycle, while with the DIA approach, all peptides generated during the first MS cycle can be fragmented in the second round.

The recently-introduced Orbitrap Fusion mass spectrometry permits various types of MS2 acquisition methods. There are four main MS2 strategies:

* HCD-OT (higher-energy-collisional-dissociation with Orbitrap detection),
* HCD-IT (HCD with ion trap, IT),
* CID-IT (collision-induced-dissociation with IT) and
* CID-OT on Orbitrap Fusion

Reading from the biorxiv preprint of Stitch:

<https://www.biorxiv.org/content/10.1101/2022.03.07.483237v1>

"With the aid of specialized software packages like DiPS, Supernovo, or ALPS, full and accurate sequences of the heavy and light chains can be reconstructed with the MS/MS spectra of the digested peptides."

Before running Stitch or similar tools, a peptide profiling tool needs to be executed on the .raw or .mgf data alone.

STITCH: <https://www.biorxiv.org/content/10.1101/2022.03.07.483237v2>

This currently requires the output of analysing .raw data via PEAKS, which is not free unfortunately. Authors currently looking into using other free de novo sequencing software for input into Stitch. The software also allows for FASTA format, which can then be executed on the output of PepNovo, Novor or similar.

DiPS: <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5461544/>

ALPS: <https://www.nature.com/articles/srep31730>

"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."

DeepNovo: <https://www.pnas.org/doi/10.1073/pnas.1705691114>

"This field has been actively studied over the past 20 y, and many de novo sequencing tools have been proposed, such as PepNovo, PEAKS, NovoHMM, MSNovo, pNovo, UniNovo, and Novor among others (6–19). The recent "gold rush" into mAbs has undoubtedly elevated the application of de novo sequencing to a new horizon (20–23)"

"DeepNovo considerably outperformed state of the art methods, achieving 7.7–22.9% higher accuracy at the amino acid level and 38.1–64.0% higher accuracy at the peptide level"

Available for download, requires activation via sending email to author, which then points to the company behind PEAKS, which will give you a 15 day evaluation license.

NovoHMM: the download page leads to a missing URL

DeepResolution2: <https://www.sciencedirect.com/science/article/abs/pii/S0039914022002119>

Capable of analyzing GC-MS data rather than MS/MS Ion Trap

DePS: <https://arxiv.org/abs/2203.08820>

DeepNovoV2: <https://github.com/volpato30/DeepNovoV2>

DPST: <https://arxiv.org/abs/2203.13132>

Link does not work <https://github.com/Yan98/DPST>

PepNovo: <http://proteomics.ucsd.edu/software-tools/531-2/>

The new version is from 2012, includes models for CID and LTQ, but not HCD models.

pNovo: <http://pfind.org/>

Includes models for CID, HCD, ETD and HCD+ETD.

Novor: <https://www.rapidnovor.com/>

Filling in a form, someone will contact you. Doesn't seem to be free.

METHODOLOGY used so far:

1 - ThermoRawFileParser: Convert .raw data to .gcf

2 - PepNovo: produce list of peptides, one-liner to convert to .fasta

3 - Stitch: analyse given a list of V(D)J+C references from templates and the .fasta file from above.


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