Evidence map›Paper›PMID 33087575›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

Broad distributions of transition-path times are fingerprints of multidimensionality of the underlying free energy landscapes.

Rohit Satija, Alexander M Berezhkovskii, Dmitrii E Makarov

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Accelerating Molecular Dynamics through Informed Resetting.Journal of chemical theory and computation · 2025
    Article
  3. Article
  4. General theory for localizing the where and when of entropy production meets single-molecule experiments.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
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  11. Article
  12. Article
  13. Broad distributions of transition-path times are fingerprints of multidimensionality of the underlying free energy landscapes.Proceedings of the National Academy of Sciences of the United States of America · 2020
    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.

Rohit SatijaDepartment of Chemistry, University of Texas at Austin, Austin, TX 78712.ORCID 0000-0003-1776-8860
Alexander M BerezhkovskiiMathematical and Statistical Computing Laboratory, Office of Intramural Research, Center for Information Technology, National Institutes of Health, Bethesda, MD 20892.
Dmitrii E MakarovDepartment of Chemistry, University of Texas at Austin, Austin, TX 78712; makarov@cm.utexas.edu.ORCID 0000-0002-8421-1846

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent single-molecule experiments have observed transition paths, i.e., brief events where molecules (particularly biomolecules) are caught in the act of surmounting activation barriers. Such measurements offer unprecedented mechanistic insights into the dynamics of biomolecular folding and binding, molecular machines, and biological membrane channels. A key challenge to these studies is to infer the complex details of the multidimensional energy landscape traversed by the transition paths from inherently low-dimensional experimental signals. A common minimalist model attempting to do so is that of one-dimensional diffusion along a reaction coordinate, yet its validity has been called into question. Here, we show that the distribution of the transition path time, which is a common experimental observable, can be used to differentiate between the dynamics described by models of one-dimensional diffusion from the dynamics in which multidimensionality is essential. Specifically, we prove that the coefficient of variation obtained from this distribution cannot possibly exceed 1 for any one-dimensional diffusive model, no matter how rugged its underlying free energy landscape is: In other words, this distribution cannot be broader than the single-exponential one. Thus, a coefficient of variation exceeding 1 is a fingerprint of multidimensional dynamics. Analysis of transition paths in atomistic simulations of proteins shows that this coefficient often exceeds 1, signifying essential multidimensionality of those systems.

Indexed as

Transition TemperatureCell MembraneComputational BiologyDiffusionEntropyNanotechnologyOptical TweezersProtein FoldingProteinsThermodynamicsProteinsforce spectroscopyprotein foldingsingle moleculestransition paths

Identifiers

PMID33087575
PMCPMC7959536

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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.