Evidence map›Paper›PMID 25838811›Full record

ArticleJournal of chemical theory and computation2015

Enhanced Conformational Sampling Using Replica Exchange with Collective-Variable Tempering.

Alejandro Gil-Ley, Giovanni Bussi

Erratum issuedAbstract read
In one paragraph

Article in Journal of chemical theory and computation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Review
  2. Article
  3. Full-Length Context Disrupts Folding of IgG-Binding Domains of Protein A.bioRxiv : the preprint server for biology · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Structural bioinformatics for rational drug design.Research and practice in thrombosis and haemostasis · 2025
    Article
  10. Absolute Binding Free Energies with OneOPES.The journal of physical chemistry letters · 2024
    Article
  11. OneOPES, a Combined Enhanced Sampling Method to Rule Them All.Journal of chemical theory and computation · 2023
    Article
  12. Article
  13. From data to noise to data for mixing physics across temperatures with generative artificial intelligence.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  14. Article
  15. Review
  16. Article
  17. Computational methods for exploring protein conformations.Biochemical Society transactions · 2020
    Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Alejandro Gil-Ley
Giovanni Bussi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The computational study of conformational transitions in RNA and proteins with atomistic molecular dynamics often requires suitable enhanced sampling techniques. We here introduce a novel method where concurrent metadynamics are integrated in a Hamiltonian replica-exchange scheme. The ladder of replicas is built with different strengths of the bias potential exploiting the tunability of well-tempered metadynamics. Using this method, free-energy barriers of individual collective variables are significantly reduced compared with simple force-field scaling. The introduced methodology is flexible and allows adaptive bias potentials to be self-consistently constructed for a large number of simple collective variables, such as distances and dihedral angles. The method is tested on alanine dipeptide and applied to the difficult problem of conformational sampling in a tetranucleotide.

Indexed as

Molecular Dynamics SimulationAlanineDipeptidesMolecular ConformationRNAAlanineDipeptidesRNA

Identifiers

PMID25838811
PMCPMC4364913

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.