Evidence map›Paper›PMID 22905104›Full record

ArticlePloS one2012

Predicting HLA class I non-permissive amino acid residues substitutions.

T Andrew Binkowski, Susana R Marino, Andrzej Joachimiak

Abstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  6. Review
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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

3 authors.

T Andrew BinkowskiBiosciences Division, Argonne National Laboratory, Midwest Center for Structural Genomics, Argonne, Illinois, United States of America.
Susana R Marino
Andrzej Joachimiak

Funding

Midwest Center for Structural GenomicsU54GM094585 · NIGMS · UNIVERSITY OF CHICAGO · PI MINOR, WLADEK · 2010 to 2014
$33.7M
NIGMS NIH HHS GM094585NIGMS NIH HHS U54 GM094585
6 · The paper itself

Abstract

Prediction of peptide binding to human leukocyte antigen (HLA) molecules is essential to a wide range of clinical entities from vaccine design to stem cell transplant compatibility. Here we present a new structure-based methodology that applies robust computational tools to model peptide-HLA (p-HLA) binding interactions. The method leverages the structural conservation observed in p-HLA complexes to significantly reduce the search space and calculate the system's binding free energy. This approach is benchmarked against existing p-HLA complexes and the prediction performance is measured against a library of experimentally validated peptides. The effect on binding activity across a large set of high-affinity peptides is used to investigate amino acid mismatches reported as high-risk factors in hematopoietic stem cell transplantation.

Indexed as

Amino AcidsAmino Acid SequenceAmino Acid SubstitutionArea Under CurveCrystallography, X-RayDatabases, ProteinHematopoietic Stem Cell TransplantationHistocompatibility Antigens Class IHumansModels, MolecularMolecular Sequence DataPeptidesProtein BindingProtein ConformationReproducibility of ResultsRiskAmino AcidsHistocompatibility Antigens Class IPeptides

Identifiers

PMID22905104
PMCPMC3414483

What OpenQuestion holds

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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.