Evidence map›Paper›PMID 18506577›Full record

ArticleJournal of computer-aided molecular design2008

2D and 3D QSAR studies of diarylpyrimidine HIV-1 reverse transcriptase inhibitors.

Joseph Rebehmed, Florent Barbault, Cátia Teixeira, François Maurel

Abstract readComparative StudyValidation Study
PubMed Publisher
In one paragraph

Article in Journal of computer-aided molecular design, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Current mathematical methods used in QSAR/QSPR studies.International journal of molecular sciences · 2009
    Review
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

4 authors.

Joseph RebehmedUniversité Paris Diderot (Paris 7), ITODYS (Interfaces, Traitements, Organisation et Dynamique des Systèmes), CNRS UMR 7086, Paris, France.
Florent Barbault
Cátia Teixeira
François Maurel

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

2D and 3D QSAR studies were applied on a set of 28 diarylpyrimidine derivatives to model and understand their HIV-1 reverse transcriptase (RT) inhibitory activities. Special cares were taken to build our set of molecules according to their bioactive conformations which is crucial to elaborate good QSAR models. 2D QSAR was performed using the heuristic method in CODESSA which had led to a linear model (R (2) = 0.928 and s (2) = 0.015) between the inhibitory activity and five descriptors. CoMFA and CoMSIA models were established using SYBYL package of programs. The better predictive ability of the CoMSIA model (q (2) = 0.730) over the CoMFA model (q (2) = 0.597) was assigned to the large contribution of hydrogen-bonding interactions to the inhibitory activity. CoMSIA physicochemical properties are in agreement with the 2D QSAR descriptors. The CoMSIA PLS contour surfaces were mapped to the binding pocket of the RT and showed that the results obtained by the 2D and 3D models are in respect with the protein environment. This link permitted us to validate our model and give important insights for the structure activity interpretations. These results will guide further structural modification and prediction of new HIV-1 RT inhibitors.

Indexed as

Quantitative Structure-Activity RelationshipBacterial ProteinsDNA-Binding ProteinsHIV-1HIV Reverse TranscriptaseHumansMolecular ConformationMolecular StructurePyrimidinesReverse Transcriptase InhibitorsBacterial ProteinscomF1 protein, Bacillus subtilisDNA-Binding ProteinsHIV Reverse TranscriptasePyrimidinesreverse transcriptase, Human immunodeficiency virus 1Reverse Transcriptase Inhibitors

Identifiers

What OpenQuestion holds

Textmetadata
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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.