Evidence map›Paper›PMID 34464112›Full record

ArticleJournal of chemical theory and computation2021

Removing Thermostat Distortions of Protein Dynamics in Constant-Temperature Molecular Dynamics Simulations.

Alan Hicks, Matthew MacAinsh, Huan-Xiang Zhou

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Sequence-Dependent Backbone Dynamics of Intrinsically Disordered Proteins.Journal of chemical theory and computation · 2022
    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.

Alan Hicks
Matthew MacAinsh

Funding

Quantitative, Mechanistic Studies of Biomolecular RecognitionR35GM118091 · NIGMS · UNIVERSITY OF ILLINOIS AT CHICAGO · PI Huan-Xiang Zhou · 2016 to 2026
$6.5M
NIGMS NIH HHS R35 GM118091
6 · The paper itself

Abstract

Molecular dynamics simulations are widely used to determine equilibrium and dynamic properties of proteins. Nearly all simulations, currently, are carried out at constant temperature, with a Langevin thermostat among the most widely used. Thermostats distort protein dynamics, but whether or how such distortions can be corrected has long been an open question. Here, we show that constant-temperature simulations with a Langevin thermostat dilate protein dynamics and present a correction scheme to remove the dynamic distortions. Specifically, ns-scale time constants for overall rotation are dilated significantly but sub-ns time constants for internal motions are dilated modestly, while all motional amplitudes are unaffected. The correction scheme involves contraction of the time constants, with the contraction factor a linear function of the time constant to be corrected. The corrected dynamics of eight proteins are validated by NMR data for rotational diffusion and for backbone amide and side-chain methyl relaxation. The present work demonstrates that even for complex systems like proteins with dynamics spanning multiple timescales, one can predict how thermostats distort protein dynamics and remove such distortions. The correction scheme will have wide applications, facilitating force-field parameterization and propelling simulations to be on par with NMR and other experimental techniques in determining dynamic properties of proteins.

Indexed as

Molecular Dynamics SimulationTemperatureAlgorithmsMagnetic Resonance SpectroscopyProteinsThermodynamicsProteins

Identifiers

PMID34464112
PMCPMC8440497

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Registered trials

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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.