Evidence map›Paper›PMID 35980981›Full record

ArticleACS nano2022

Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein-DNA Nanostructures.

Raghu Pradeep Narayanan, Jonah Procyk, Purbasha Nandi, Abhay Prasad, Yang Xu, Erik Poppleton, Dewight Williams, Fei Zhang, Hao Yan, Po-Lin Chiu and 2 more

Abstract read
In one paragraph

Article in ACS nano, 2022. 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. Review
  3. 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

12 authors.

Raghu Pradeep NarayananSchool of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States.
Jonah ProcykSchool of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States.
Purbasha NandiSchool of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States.
Abhay PrasadSchool of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States.
Yang XuCenter for molecular design and biomimetics, The Biodesign Institute, Arizona State University, Tempe, Arizona 85287, United States.
Erik PoppletonCenter for molecular design and biomimetics, The Biodesign Institute, Arizona State University, Tempe, Arizona 85287, United States.ORCID 0000-0002-5146-5970
Dewight WilliamsEyring Materials Center, Office of Knowledge Enterprise Development, Arizona State University, Tempe, Arizona 85287, United States.
Fei ZhangDepartment of Chemistry, Rutgers University, Newark, New Jersey 07102, United States.ORCID 0000-0002-3177-7547
Hao YanSchool of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States.ORCID 0000-0001-7397-9852
Po-Lin ChiuSchool of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States.
Nicholas StephanopoulosSchool of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States.ORCID 0000-0001-7859-410X
Petr ŠulcSchool of Molecular Sciences, Arizona State University, Tempe, Arizona 85287, United States.ORCID 0000-0003-1565-6769

Funding

Chemical synthesis of G protein-coupled receptors using sequential DNA-templated reactionsDP2GM132931 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI STEPHANOPOULOS, NICHOLAS · 2018 to 2018
$2.2M
NIGMS NIH HHS DP2 GM132931
6 · The paper itself

Abstract

We present here the combination of experimental and computational modeling tools for the design and characterization of protein-DNA hybrid nanostructures. Our work incorporates several features in the design of these nanostructures: (1) modeling of the protein-DNA linker identity and length; (2) optimizing the design of protein-DNA cages to account for mechanical stresses; (3) probing the incorporation efficiency of protein-DNA conjugates into DNA nanostructures. The modeling tools were experimentally validated using structural characterization methods like cryo-TEM and AFM. Our method can be used for fitting low-resolution electron density maps when structural insights cannot be deciphered from experiments, as well as enable

Indexed as

Molecular Dynamics SimulationNanostructuresCryoelectron MicroscopyDNADNAcoarse-grained modelscryo-EM fittingDNA nanotechnologymolecular dynamicsprotein−DNA

Identifiers

PMID35980981
PMCPMC9590280

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.