Evidence map›Paper›PMID 28337243›Full record

ArticleThe journal of physical chemistry. C, Nanomaterials and interfaces2016

Residue-Specific Interactions of an Intrinsically Disordered Protein with Silica Nanoparticles and their Quantitative Prediction.

Mouzhe Xie, Alexandar L Hansen, Jiaqi Yuan, Rafael Brüschweiler

Open access · greenAbstract read
In one paragraph

Article in The journal of physical chemistry. C, Nanomaterials and interfaces, 2016. 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
1.3field-weighted citation impact, top 21% 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, 35 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

4 authors at 1 institution in 1 country.

Mouzhe XieDepartment of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States.
Alexandar L HansenCampus Chemical Instrument Center, The Ohio State University, Columbus, Ohio 43210, United States.
Jiaqi YuanDepartment of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States.
Rafael BrüschweilerDepartment of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States; Campus Chemical Instrument Center, The Ohio State University, Columbus, Ohio 43210, United States; Department of Biological Chemistry and Pharmacology, The Ohio State University, Columbus, Ohio 43210, United States.
The Ohio State University · US

Funding

New hybrid methods for the improved and integrated analysis of complex metabolomics mixturesR01GM066041 · NIGMS · OHIO STATE UNIVERSITY · PI BRUSCHWEILER, RAFAEL · 2002 to 2019
$3.3M
NIGMS NIH HHS R01 GM066041
6 · The paper itself

Abstract

Elucidation of the driving forces that govern interactions between nanoparticles and intrinsically disordered proteins (IDP) is important for the understanding of the effect of nanoparticles in living systems and for the design of new nanoparticle-based assays to monitor health and combat disease. The quantitative interaction profile of the intrinsically disordered transactivation domain of p53 and its mutants with anionic silica nanoparticles is reported at atomic resolution using nuclear magnetic spin relaxation experiments. These profiles are analyzed with a novel interaction model that is based on a quantitative nanoparticle affinity scale separately derived for the 20 natural amino acids. The results demonstrate how the interplay of attractive and repulsive Coulomb interactions with hydrophobic effects is responsible for the sequence-dependent binding of a disordered protein to nanoparticles.

Identifiers

PMID28337243
PMCPMC5358802
OpenAlexW2523231813

What OpenQuestion holds

Textmetadata
LicenceTDM
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.