Evidence map›Paper›PMID 30816214›Full record

ArticleScientific reports2019

deMix: Decoding Deuterated Distributions from Heterogeneous Protein States via HDX-MS.

Seungjin Na, Jae-Jin Lee, Jong Wha J Joo, Kong-Joo Lee, Eunok Paek

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. A framework for automated multimodal HDX-MS analysis.bioRxiv : the preprint server for biology · 2025
    Article
  4. Rigorous Analysis of Multimodal HDX-MS Spectra.Journal of the American Society for Mass Spectrometry · 2025
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Seungjin NaDept. of Computer Science, Hanyang University, Seoul, 04763, South Korea.ORCID 0000-0002-5159-2048
Jae-Jin LeeGraduate School of Pharmaceutical Sciences, College of Pharmacy, Ewha Womans University, Seoul, 03760, South Korea.
Jong Wha J JooDept. of Computer Science and Engineering, Dongguk University-Seoul, Seoul, 04620, South Korea.
Kong-Joo LeeGraduate School of Pharmaceutical Sciences, College of Pharmacy, Ewha Womans University, Seoul, 03760, South Korea.
Eunok PaekDept. of Computer Science, Hanyang University, Seoul, 04763, South Korea. eunokpaek@hanyang.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Characterization of protein structural changes in response to protein modifications, ligand or chemical binding, or protein-protein interactions is essential for understanding protein function and its regulation. Amide hydrogen/deuterium exchange (HDX) coupled with mass spectrometry (MS) is one of the most favorable tools for characterizing the protein dynamics and changes of protein conformation. However, currently the analysis of HDX-MS data is not up to its full power as it still requires manual validation by mass spectrometry experts. Especially, with the advent of high throughput technologies, the data size grows everyday and an automated tool is essential for the analysis. Here, we introduce a fully automated software, referred to as 'deMix', for the HDX-MS data analysis. deMix deals directly with the deuterated isotopic distributions, but not considering their centroid masses and is designed to be robust over random noises. In addition, unlike the existing approaches that can only determine a single state from an isotopic distribution, deMix can also detect a bimodal deuterated distribution, arising from EX1 behavior or heterogeneous peptides in conformational isomer proteins. Furthermore, deMix comes with visualization software to facilitate validation and representation of the analysis results.

Indexed as

SoftwareHydrogen Deuterium Exchange-Mass SpectrometryProtein ConformationProteinsProteins

Identifiers

PMID30816214
PMCPMC6395696

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.