Evidence map›Paper›PMID 38172126›Full record

ArticleNature communications2024

Combining stochastic resetting with Metadynamics to speed-up molecular dynamics simulations.

Ofir Blumer, Shlomi Reuveni, Barak Hirshberg

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Accelerating Molecular Dynamics through Informed Resetting.Journal of chemical theory and computation · 2025
    Article
  5. Restart uncertainty relation for monitored quantum dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  6. Review
  7. Review
  8. Short-Time Infrequent Metadynamics for Improved Kinetics Inference.Journal of chemical theory and computation · 2024
    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

3 authors.

Ofir BlumerSchool of Chemistry, Tel Aviv University, Tel Aviv, 6997801, Israel.
Shlomi ReuveniSchool of Chemistry, Tel Aviv University, Tel Aviv, 6997801, Israel.ORCID http://orcid.org/0000-0003-2292-8005
Barak HirshbergSchool of Chemistry, Tel Aviv University, Tel Aviv, 6997801, Israel. hirshb@tauex.tau.ac.il.ORCID http://orcid.org/0000-0002-0014-515X

Funding

EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 947731Israel Science Foundation (ISF) 1037/22Israel Science Foundation (ISF) 1312/22Israel Science Foundation (ISF) 394/19PAZY Foundation (PAZY) 415/2023
6 · The paper itself

Abstract

Metadynamics is a powerful method to accelerate molecular dynamics simulations, but its efficiency critically depends on the identification of collective variables that capture the slow modes of the process. Unfortunately, collective variables are usually not known a priori and finding them can be very challenging. We recently presented a collective variables-free approach to enhanced sampling using stochastic resetting. Here, we combine the two methods, showing that it can lead to greater acceleration than either of them separately. We also demonstrate that resetting Metadynamics simulations performed with suboptimal collective variables can lead to speedups comparable with those obtained with optimal collective variables. Therefore, applying stochastic resetting can be an alternative to the challenging task of improving suboptimal collective variables, at almost no additional computational cost. Finally, we propose a method to extract unbiased mean first-passage times from Metadynamics simulations with resetting, resulting in an improved tradeoff between speedup and accuracy. This work enables combining stochastic resetting with other enhanced sampling methods to accelerate a broad range of molecular simulations.

Identifiers

PMID38172126
PMCPMC10764788

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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.