Evidence map›Paper›PMID 35502992›Full record

ArticleJournal of chemical theory and computation2022

Accelerating the Ensemble Convergence of RNA Hairpin Simulations with a Replica Exchange Structure Reservoir.

Kenneth Lam, Koushik Kasavajhala, Sarah Gunasekera, Carlos Simmerling

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 2022. 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. Recent Developments in Amber Biomolecular Simulations.Journal of chemical information and modeling · 2025
    Article
  2. Article
  3. Accurately Modeling RNA Stem-Loops in an Implicit Solvent Environment.Journal of chemical information and modeling · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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.

Kenneth LamMolecular and Cellular Biology, Stony Brook University, Stony Brook, New York 11794, United States.
Koushik KasavajhalaDepartment of Chemistry, Stony Brook University, Stony Brook, New York 11794, United States.
Sarah GunasekeraProgram in Biology, Stony Brook University, Stony Brook, New York 11794, United States.
Carlos SimmerlingMolecular and Cellular Biology, Stony Brook University, Stony Brook, New York 11794, United States.ORCID 0000-0002-7252-4730

Funding

New Solvent Models, Sampling Methods and Maintenance of Amber SoftwareR01GM107104 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI SIMMERLING, CARLOS · 2013 to 2020
$2.4M
NIGMS NIH HHS R01 GM107104
6 · The paper itself

Abstract

RNA is a key participant in many biological processes, but studies of RNA using computer simulations lag behind those of proteins, largely due to less-developed force fields and the slow dynamics of RNA. Generating converged RNA ensembles for force field development and other studies remains a challenge. In this study, we explore the ability of replica exchange molecular dynamics to obtain well-converged conformational ensembles for two RNA hairpin systems in an implicit solvent. Even for these small model systems, standard REMD remains computationally costly, but coupling to a pre-generated structure library using the reservoir REMD approach provides a dramatic acceleration of ensemble convergence for both model systems. Such precise ensembles could facilitate RNA force field development and validation and applications of simulation to more complex RNA systems. The advantages and remaining challenges of applying R-REMD to RNA are investigated in detail.

Indexed as

Molecular Dynamics SimulationRNAHumansMolecular ConformationProteinsSolventsProteinsRNASolvents

Identifiers

PMID35502992
PMCPMC10658646

What OpenQuestion holds

Textmetadata
LicenceTDM
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.