Evidence map›Paper›PMID 31350773›Full record

ArticleProteins2019

NMR-assisted protein structure prediction with MELDxMD.

James C Robertson, Roy Nassar, Cong Liu, Emiliano Brini, Ken A Dill, Alberto Perez

Abstract read
In one paragraph

Article in Proteins, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. MELD in Action: Harnessing Data to Accelerate Molecular Dynamics.Journal of chemical information and modeling · 2025
    Review
  4. Review
  5. Article
  6. Using metagenomic data to boost protein structure prediction and discovery.Computational and structural biotechnology journal · 2022
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Protein storytelling through physics.Science (New York, N.Y.) · 2020
    Review
  14. Article
  15. Article
  16. 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

6 authors.

James C RobertsonLaufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York.
Roy NassarLaufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York.
Cong LiuLaufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York.
Emiliano BriniLaufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York.
Ken A DillLaufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York.
Alberto PerezDepartment of Chemistry, University of Florida, Gainesville, Florida.ORCID 0000-0002-5054-5338

Funding

IRACDA - The New York Consortium for the Advancement of Postdoctoral Scholars (NY CAPS)Phase IIK12GM102778 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI Carol A. Carter, Karian Janice Wright · 2012 to 2026
$13.1M
MELD: accelerating MD modeling of proteins using Bayesian inferenceR01GM125813 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI DILL, KEN A · 2018 to 2021
$1.3M
NIGMS NIH HHS GM125813NIGMS NIH HHS K12 GM102778NIGMS NIH HHS K12-GM-102778NIGMS NIH HHS R01 GM125813
6 · The paper itself

Abstract

We describe the performance of MELD-accelerated molecular dynamics (MELDxMD) in determining protein structures in the NMR-data-assisted category in CASP13. Seeded from web server predictions, MELDxMD was found best in the NMR category, over 17 targets, outperforming the next-best groups by a factor of ~4 in z-score. MELDxMD gives ensembles, not single structures; succeeds on a 326-mer, near the current upper limit for NMR structures; and predicts structures that match experimental residual dipolar couplings even though the only NMR-derived data used in the simulations was NOE-based ambiguous atom-atom contacts and backbone dihedrals. MELD can use noisy and ambiguous experimental information to reduce the MD search space. We believe MELDxMD is a promising method for determining protein structures from NMR data.

Indexed as

Molecular Dynamics SimulationProtein ConformationAlgorithmsComputational BiologyMagnetic Resonance SpectroscopyProteinsReproducibility of ResultsProteinsCASP13MELDmolecular dynamicsNMRprotein structure prediction

Identifiers

PMID31350773
PMCPMC6851473

What OpenQuestion holds

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Registered trials

None linked

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.