Evidence map›Paper›PMID 31244950›Full record

ReviewTheranostics2019

Supramolecular Assemblies of Peptides or Nucleopeptides for Gene Delivery.

Huaimin Wang, Zhaoqianqi Feng, Bing Xu

Abstract readReview
In one paragraph

Review in Theranostics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. 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.

Huaimin WangDepartment of Chemistry, Brandeis University, 415 South Street, Waltham, MA 02453, USA.
Zhaoqianqi FengDepartment of Chemistry, Brandeis University, 415 South Street, Waltham, MA 02453, USA.
Bing XuDepartment of Chemistry, Brandeis University, 415 South Street, Waltham, MA 02453, USA.

Funding

Subcellular Enzyme-instructed self-assembly for molecular anticancer nanomedicinesR01CA142746 · NCI · BRANDEIS UNIVERSITY · PI Bing Xu · 2010 to 2026
$6.4M
Overcoming Tumor Resistance with Enzyme-Instructed Nanoscale Assemblies and ImmunotherapiesF99CA234746 · NCI · BRANDEIS UNIVERSITY · PI FENG, ZHAOQIANQI · 2018 to 2019
$62k
NCI NIH HHS F99 CA234746NCI NIH HHS R01 CA142746
6 · The paper itself

Abstract

Using non-covalent interactions between nucleic acids (DNA, siRNA, miRNA, and mRNA) with peptides or nucleopeptides is a promising strategy to construct supramolecular assemblies for gene delivery and therapy. Comparing to conventional strategies for gene delivery, the assemblies of peptides or nucleopeptides provide several unique advantages: i) reversible interactions between the assemblies and the nucleic acids; ii) minimal immunogenicity; iii) biocompatibility. This field has advanced considerably in recent years so that it is worth summarizing the recent progresses and future challenges. In this review, we introduce the development of assemblies of peptides or nucleopeptides for applications in gene delivery and related fields. After introducing the promises of gene therapy and the current strategies for the delivery, we discuss the unique advantage of using peptide assemblies for gene delivery. Then we describe several representative strategies for gene delivery by the assemblies of peptides or nucleopeptides. Finally, we discuss the key factors for designing such assemblies for gene delivery, and speculate future directions and challenges in the field, particularly the rational design and the spatiotemporally controlled release in live cells.

Indexed as

Gene Transfer TechniquesDNAGenetic TherapyHumansMacromolecular SubstancesNucleoproteinsPeptidesProtein BindingRNADNAMacromolecular SubstancesNucleoproteinsPeptidesRNAEnzymeGene deliveryNanostructuresNon-viral vectorNucleopeptidePeptideSelf-assembly

Identifiers

PMID31244950
PMCPMC6567966

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.