Evidence map›Paper›PMID 17726544›Full record

ArticlePloS one2007

Distinguishing functional amino acid covariation from background linkage disequilibrium in HIV protease and reverse transcriptase.

Qi Wang, Christopher Lee

Open access · goldAbstract readComparative Study
In one paragraph

Article in PloS one, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.5field-weighted citation impact, top 44% 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

12 citing papers in PubMed, 20 citations in OpenAlex.

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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 1 institution in 1 country.

Qi WangCenter for Computational Biology, Molecular Biology Institute, Institute for Genomics and Proteomics, University of California at Los Angeles, Los Angeles, United States of America.
Christopher Lee
University of California, Los Angeles · US

Funding

Center for Computational Biology (RMI)U54RR021813 · NCRR · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI TOGA, ARTHUR W · 2004 to 2010
$25.3M
NCRR NIH HHS U54 RR021813
6 · The paper itself

Abstract

Correlated amino acid mutation analysis has been widely used to infer functional interactions between different sites in a protein. However, this analysis can be confounded by important phylogenetic effects broadly classifiable as background linkage disequilibrium (BLD). We have systematically separated the covariation induced by selective interactions between amino acids from background LD, using synonymous (S) vs. amino acid (A) mutations. Covariation between two amino acid mutations, (A,A), can be affected by selective interactions between amino acids, whereas covariation within (A,S) pairs or (S,S) pairs cannot. Our analysis of the pol gene--including the protease and the reverse transcriptase genes--in HIV reveals that (A,A) covariation levels are enormously higher than for either (A,S) or (S,S), and thus cannot be attributed to phylogenetic effects. The magnitude of these effects suggests that a large portion of (A,A) covariation in the HIV pol gene results from selective interactions. Inspection of the most prominent (A,A) interactions in the HIV pol gene showed that they are known sites of independently identified drug resistance mutations, and physically cluster around the drug binding site. Moreover, the specific set of (A,A) interaction pairs was reproducible in different drug treatment studies, and vanished in untreated HIV samples. The (S,S) covariation curves measured a low but detectable level of background LD in HIV.

Indexed as

Genetic VariationLinkage DisequilibriumAmino Acid SequenceAmino Acid SubstitutionHIV ProteaseModels, MolecularProtein ConformationRNA-Directed DNA PolymeraseSequence AlignmentHIV ProteaseRNA-Directed DNA Polymerase

Identifiers

PMID17726544
PMCPMC1950573
OpenAlexW1982694918

What OpenQuestion holds

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Registered trials

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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.