Evidence map›Paper›PMID 19436759›Full record

ArticlePloS one2009

Characterizing structural transitions using localized free energy landscape analysis.

Nilesh K Banavali, Alexander D Mackerell

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. 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

2 authors at 2 institutions in 1 country.

Nilesh K BanavaliLaboratory of Computational and Structural Biology, Division of Genetics, Wadsworth Center, New York State Department of Health, Albany, New York, USA. banavali@wadsworth.org
Alexander D Mackerell
New York State Department of Health · USUniversity of Maryland, Baltimore · US

Funding

Oligonucleotide Conformational HeterogeneityR01GM051501 · NIGMS · UNIVERSITY OF MARYLAND BALTIMORE · PI MACKERELL, ALEXANDER D · 2003 to 2018
$3.6M
HALOGEN FREE ENERGY DATABASE FOR RATIONAL DRUG DESIGNR29GM051501 · NIGMS · UNIVERSITY OF MARYLAND BALTIMORE · PI MACKERELL, ALEXANDER D. · 1996 to 2000
$108k
NIGMS NIH HHS GM51501NIGMS NIH HHS R01 GM051501NIGMS NIH HHS R29 GM051501
6 · The paper itself

Abstract

backgroundStructural changes in molecules are frequently observed during biological processes like replication, transcription and translation. These structural changes can usually be traced to specific distortions in the backbones of the macromolecules involved. Quantitative energetic characterization of such distortions can greatly advance the atomic-level understanding of the dynamic character of these biological processes. METHODOLOGY/PRINCIPAL

findingsMolecular dynamics simulations combined with a variation of the Weighted Histogram Analysis Method for potential of mean force determination are applied to characterize localized structural changes for the test case of cytosine (underlined) base flipping in a GTCAGCGCATGG DNA duplex. Free energy landscapes for backbone torsion and sugar pucker degrees of freedom in the DNA are used to understand their behavior in response to the base flipping perturbation. By simplifying the base flipping structural change into a two-state model, a free energy difference of upto 14 kcal/mol can be attributed to the flipped state relative to the stacked Watson-Crick base paired state. This two-state classification allows precise evaluation of the effect of base flipping on local backbone degrees of freedom. CONCLUSIONS/SIGNIFICANCE: The calculated free energy landscapes of individual backbone and sugar degrees of freedom expectedly show the greatest change in the vicinity of the flipping base itself, but specific delocalized effects can be discerned upto four nucleotide positions away in both 5' and 3' directions. Free energy landscape analysis thus provides a quantitative method to pinpoint the determinants of structural change on the atomic scale and also delineate the extent of propagation of the perturbation along the molecule. In addition to nucleic acids, this methodology is anticipated to be useful for studying conformational changes in all macromolecules, including carbohydrates, lipids, and proteins.

Indexed as

ThermodynamicsBase PairingBase SequenceBinding SitesComputer SimulationDNADNA ReplicationMolecular Sequence DataNucleic Acid ConformationNucleotidesStructure-Activity RelationshipDNANucleotides

Identifiers

PMID19436759
PMCPMC2678196
OpenAlexW1981099076

What OpenQuestion holds

Textmetadata
LicenceCC0
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.