Evidence map›Paper›PMID 29925019›Full record

ArticleBiophysical journal2018

Refinement of Peptide Conformational Ensembles by 2D IR Spectroscopy: Application to Ala‒Ala‒Ala.

Chi-Jui Feng, Balamurugan Dhayalan, Andrei Tokmakoff

Abstract read
In one paragraph

Article in Biophysical journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Quantitative molecular simulations.Physical chemistry chemical physics : PCCP · 2022
    Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Efficient Ensemble Refinement by Reweighting.Journal of chemical theory and computation · 2019
    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.

Chi-Jui FengDepartment of Chemistry, James Franck Institute and Institute for Biophysical Dynamics, University of Chicago, Chicago, Illinois.
Balamurugan DhayalanDepartment of Chemistry, James Franck Institute and Institute for Biophysical Dynamics, University of Chicago, Chicago, Illinois.
Andrei TokmakoffDepartment of Chemistry, James Franck Institute and Institute for Biophysical Dynamics, University of Chicago, Chicago, Illinois. Electronic address: tokmakoff@uchicago.edu.

Funding

The Dynamics of Molecular Recognition by Proteins from 2D IR Spectroscopy and MD SimulationsR01GM118774 · NIGMS · UNIVERSITY OF CHICAGO · PI TOKMAKOFF, ANDREI · 2016 to 2019
$1.6M
NIGMS NIH HHS R01 GM118774
6 · The paper itself

Abstract

Characterizing ensembles of intrinsically disordered proteins is experimentally challenging because of the ill-conditioned nature of ensemble determination with limited data and the intrinsic fast dynamics of the conformational ensemble. Amide I two-dimensional infrared (2D IR) spectroscopy has picosecond time resolution to freeze structural ensembles as needed for probing disordered-protein ensembles and conformational dynamics. Also, developments in amide I computational spectroscopy now allow a quantitative and direct prediction of amide I spectra based on conformational distributions drawn from molecular dynamics simulations, providing a route to ensemble refinement against experimental spectra. We performed a Bayesian ensemble refinement method on Ala-Ala-Ala against isotope-edited Fourier-transform infrared spectroscopy and 2D IR spectroscopy and tested potential factors affecting the quality of ensemble refinements. We found that isotope-edited 2D IR spectroscopy provides a stringent constraint on Ala-Ala-Ala conformations and returns consistent conformational ensembles with the dominant ppII conformer across varying prior distributions from many molecular dynamics force fields and water models. The dominant factor influencing ensemble refinements is the systematic frequency uncertainty from spectroscopic maps. However, the uncertainty of conformer populations can be significantly reduced by incorporating 2D IR spectra in addition to traditional Fourier-transform infrared spectra. Bayesian ensemble refinement against isotope-edited 2D IR spectroscopy thus provides a route to probe equilibrium-complex protein ensembles and potentially nonequilibrium conformational dynamics.

Indexed as

AmidesMolecular Dynamics SimulationOligopeptidesProtein ConformationSpectrophotometry, Infraredalanyl-alanyl-alanineAmidesOligopeptides

Identifiers

PMID29925019
PMCPMC6026468

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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.