Evidence map›Paper›PMID 34911426›Full record

ReviewCurrent topics in medicinal chemistry2022

Nanoscale Structures and Materials from the Self-assembly of Polypeptides and DNA.

Julio Bernal-Chanchavac, Md Al-Amin, Nicholas Stephanopoulos

Open access · greenAbstract readReview
In one paragraph

Review in Current topics in medicinal chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 37% 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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. 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

3 authors at 1 institution in 1 country.

Julio Bernal-ChanchavacSchool of Molecular Sciences, Arizona State University, Tempe AZ 85251, USA.
Md Al-AminSchool of Molecular Sciences, Arizona State University, Tempe AZ 85251, USA.
Nicholas StephanopoulosSchool of Molecular Sciences, Arizona State University, Tempe AZ 85251, USA.
Arizona State University · US

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
National Institute of General Medical Sciences of the National Institutes of Health DP2GM132931National Science Foundation (DMR-BMAT CAREER award) 1753387NIGMS NIH HHS DP2 GM132931
6 · The paper itself

Abstract

The use of biological molecules with programmable self-assembly properties is an attractive route to functional nanomaterials. Proteins and peptides have been used extensively for these systems due to their biological relevance and a large number of supramolecular motifs, but it is still difficult to build highly anisotropic and programmable nanostructures due to their high complexity. Oligonucleotides, by contrast, have the advantage of programmability and reliable assembly, but lack biological and chemical diversity. In this review, we discuss systems that merge protein or peptide self-assembly with the addressability of DNA. We outline the various self-assembly motifs used, the chemistry for linking polypeptides with DNA, and the resulting nanostructures that can be formed by the interplay of these two molecules. Finally, we close by suggesting some interesting future directions in hybrid polypeptide-DNA nanomaterials, and potential applications for these exciting hybrids.

Indexed as

DNANanostructuresNanotechnologyOligonucleotidesPeptidesDNAOligonucleotidesPeptidesBiomaterialsDNA nanotechnologyNanotechnologyPeptidesProteinsSelf-assembly

Identifiers

PMID34911426
PMCPMC9590279
OpenAlexW4200594596

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.