Evidence map›Paper›PMID 32105651›Full record

ArticleBiophysical journal2020

Interpretation of HDX Data by Maximum-Entropy Reweighting of Simulated Structural Ensembles.

Richard T Bradshaw, Fabrizio Marinelli, José D Faraldo-Gómez, Lucy R Forrest

Abstract read
In one paragraph

Article in Biophysical journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

24 citing papers in PubMed.

  1. Review
  2. Article
  3. Intrinsic Hydrogen-Deuterium Exchange Rates in HThe journal of physical chemistry. B · 2026
    Article
  4. Article
  5. Article
  6. State-of-the-Art and Future Directions in Structural Proteomics.Molecular & cellular proteomics : MCP · 2025
    Review
  7. Article
  8. Article
  9. Free energy landscape of the PI3Kα C-terminal activation.Computational and structural biotechnology journal · 2024
    Article
  10. Conformational dynamics underlying atypical chemokine receptor 3 activation.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  11. Conformational free-energy landscapes of a NaProceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Review
  19. Article
  20. Article
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

4 authors.

Richard T BradshawComputational Structural Biology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland.
Fabrizio MarinelliTheoretical Molecular Biophysics Unit, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland.
José D Faraldo-GómezTheoretical Molecular Biophysics Unit, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland. Electronic address: jose.faraldo@nih.gov.
Lucy R ForrestComputational Structural Biology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland. Electronic address: lucy.forrest@nih.gov.

Funding

Molecular Mechanisms in Membrane Bioenergetics, Transport and SignalingZIAHL006203 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI FARALDO-GÓMEZ, JOSE · 2015 to 2023
$15.4M
Development and assessment of methods for studying membrane protein structure and functionZIANS003143 · NINDS · NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE · PI FORREST, LUCY · 2014 to 2025
$8.9M
6 · The paper itself

Abstract

Hydrogen-deuterium exchange combined with mass spectrometry (HDX-MS) is a widely applied biophysical technique that probes the structure and dynamics of biomolecules without the need for site-directed modifications or bio-orthogonal labels. The mechanistic interpretation of HDX data, however, is often qualitative and subjective, owing to a lack of quantitative methods to rigorously translate observed deuteration levels into atomistic structural information. To help address this problem, we have developed a methodology to generate structural ensembles that faithfully reproduce HDX-MS measurements. In this approach, an ensemble of protein conformations is first generated, typically using molecular dynamics simulations. A maximum-entropy bias is then applied post hoc to the resulting ensemble such that averaged peptide-deuteration levels, as predicted by an empirical model, agree with target values within a given level of uncertainty. We evaluate this approach, referred to as HDX ensemble reweighting (HDXer), for artificial target data reflecting the two major conformational states of a binding protein. We demonstrate that the information provided by HDX-MS experiments and by the model of exchange are sufficient to recover correctly weighted structural ensembles from simulations, even when the relevant conformations are rarely observed. Degrading the information content of the target data-e.g., by reducing sequence coverage, by averaging exchange levels over longer peptide segments, or by incorporating different sources of uncertainty-reduces the structural accuracy of the reweighted ensemble but still allows for useful insights into the distinctive structural features reflected by the target data. Finally, we describe a quantitative metric to rank candidate structural ensembles according to their correspondence with target data and illustrate the use of HDXer to describe changes in the conformational ensemble of the membrane protein LeuT. In summary, HDXer is designed to facilitate objective structural interpretations of HDX-MS data and to inform experimental approaches and further developments of theoretical exchange models.

Indexed as

Deuterium Exchange MeasurementHydrogen Deuterium Exchange-Mass SpectrometryEntropyMass SpectrometryProtein Conformation

Identifiers

PMID32105651
PMCPMC7136279

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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.