Evidence map›Paper›PMID 23298176›Full record

ReviewBiochemistry2013

Visualizing functional motions of membrane transporters with molecular dynamics simulations.

Saher A Shaikh, Jing Li, Giray Enkavi, Po-Chao Wen, Zhijian Huang, Emad Tajkhorshid

Abstract readReview
In one paragraph

Review in Biochemistry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Post-translational modifications of transporters.Pharmacology & therapeutics · 2018
    Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Simulating the function of sodium/proton antiporters.Proceedings of the National Academy of Sciences of the United States of America · 2015
    Article
  18. Article
  19. Article
  20. 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

6 authors.

Saher A ShaikhDepartment of Biochemistry, Beckman Institute for Advanced Science and Technology, and Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, 405 North Mathews Avenue, Urbana, IL 61801, USA.
Jing Li
Giray Enkavi
Po-Chao Wen
Zhijian Huang
Emad Tajkhorshid

Funding

Synthetic Antigen Binder CoreU54GM087519 · NIGMS · UNIVERSITY OF CHICAGO · PI BOWIE, JAMES U · 2010 to 2017
$31.9M
WHOLE CELL SIMULATIONP41GM104601 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI TAJKHORSHID, EMAD · 2012 to 2021
$19.0M
Molecular Mechanisms of Active Transport Across Cellular MembranesR01GM086749 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI TAJKHORSHID, EMAD · 2009 to 2013
$1.5M
NIGMS NIH HHS P41-GM104601NIGMS NIH HHS R01 GM086749NIGMS NIH HHS R01-GM086749NIGMS NIH HHS U54 GM087519NIGMS NIH HHS U54-GM087519
6 · The paper itself

Abstract

Computational modeling and molecular simulation techniques have become an integral part of modern molecular research. Various areas of molecular sciences continue to benefit from, indeed rely on, the unparalleled spatial and temporal resolutions offered by these technologies, to provide a more complete picture of the molecular problems at hand. Because of the continuous development of more efficient algorithms harvesting ever-expanding computational resources, and the emergence of more advanced and novel theories and methodologies, the scope of computational studies has expanded significantly over the past decade, now including much larger molecular systems and far more complex molecular phenomena. Among the various computer modeling techniques, the application of molecular dynamics (MD) simulation and related techniques has particularly drawn attention in biomolecular research, because of the ability of the method to describe the dynamical nature of the molecular systems and thereby to provide a more realistic representation, which is often needed for understanding fundamental molecular properties. The method has proven to be remarkably successful in capturing molecular events and structural transitions highly relevant to the function and/or physicochemical properties of biomolecular systems. Herein, after a brief introduction to the method of MD, we use a number of membrane transport proteins studied in our laboratory as examples to showcase the scope and applicability of the method and its power in characterizing molecular motions of various magnitudes and time scales that are involved in the function of this important class of membrane proteins.

Indexed as

Molecular Dynamics SimulationBiological TransportHumansHydrogen BondingMembrane Transport ProteinsProtein Structure, SecondaryProtein Structure, TertiaryThermodynamicsMembrane Transport Proteins

Identifiers

PMID23298176
PMCPMC3560430

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.