Evidence map›Paper›PMID 25073457›Full record

ArticleJournal of molecular modeling2014

Insight into HIV-1 reverse transcriptase-aptamer interaction from molecular dynamics simulations.

Niran Aeksiri, Napat Songtawee, M Paul Gleeson, Supa Hannongbua, Kiattawee Choowongkomon

Abstract read
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In one paragraph

Article in Journal of molecular modeling, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

7 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Review
  3. Methods and Applications of In Silico Aptamer Design and Modeling.International journal of molecular sciences · 2020
    Review
  4. Article
  5. Review
  6. Review
  7. 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

5 authors at 2 institutions in 1 country.

Niran AeksiriInterdisciplinary Program in Genetic Engineering, Graduate School, Kasetsart University, Chatuchak, Bangkok, 10900, Thailand.
Napat Songtawee
M Paul Gleeson
Supa Hannongbua
Kiattawee Choowongkomon
Kasetsart University · THMahidol University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human immunodeficiency virus-1 reverse transcriptase (HIV-1 RT) is considered to be one of the key targets for antiviral drug therapy. The emergence of the aptamers as potential inhibitors against HIV-1 reverse transcriptase has attracted the attention of the scientific community because these macromolecules can effectively inhibit HIV-1 RT with between micromolar to picomolar concentrations. However, it is not clear how aptamers interact with HIV-1 RT. We have undertaken a molecular dynamics (MD) study in order to gain a keen insight into the conformational dynamics of HIV-1 RT on the formation of a complex with an aptamer or DNA substrate. We have therefore employed three separate models: apo HIV-1 RT, HIV-1 RT with a bound RNA aptamer, and HIV-1 RT with a bound DNA substrate. The results show that HIV-1 RT complex with an aptamer was more stable than that with DNA substrate. It was found that the aptamer interacted with HIV-1 RT in a fingers-and-thumb-closed conformation, at the bound at the nucleic acid substrate binding site. We identified key residues within the HIV-1 RT-aptamer complex in order to help design, develop, and test a new aptamer based on therapies in the future.

Indexed as

Molecular Dynamics SimulationAptamers, NucleotideDNAHIV Reverse TranscriptaseHumansHydrogen BondingPrincipal Component AnalysisProtein Structure, TertiaryThermodynamicsAptamers, NucleotideDNAHIV Reverse Transcriptasereverse transcriptase, Human immunodeficiency virus 1

Identifiers

PMID25073457
OpenAlexW2013545480

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.