Evidence map›Paper›PMID 32426335›Full record

ReviewFrontiers in bioengineering and biotechnology2020

Hierarchical Self-Assembly of Proteins Through Rationally Designed Supramolecular Interfaces.

Hongcheng Sun, Yan Li, Shuangjiang Yu, Junqiu Liu

Abstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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  15. Encoding hierarchical assembly pathways of proteins with DNA.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
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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.

Hongcheng SunCollege of Material, Chemistry and Chemical Engineering, Hangzhou Normal University, Hangzhou, China.
Yan LiKey Laboratory of Organosilicon Chemistry and Material Technology, Ministry of Education, Hangzhou Normal University, Hangzhou, China.
Shuangjiang YuCollege of Material, Chemistry and Chemical Engineering, Hangzhou Normal University, Hangzhou, China.
Junqiu LiuCollege of Material, Chemistry and Chemical Engineering, Hangzhou Normal University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increasing advances in the basic understanding of pathogenesis mechanism and fabrication of advanced biological materials, protein nanomaterials are being developed for their potential bioengineering research and biomedical applications. Among different fabrication strategies, supramolecular self-assembly provides a versatile approach to construct hierarchical nanostructures from polyhedral cages, filaments, tubules, monolayer sheets to even cubic crystals through rationally designed supramolecular interfaces. In this mini review, we will briefly recall recent progress in reconstituting protein interfaces for hierarchical self-assembly and classify by the types of designed protein-protein interactions into receptor-ligand recognition, electrostatic interaction, metal coordination, and non-specific interaction networks. Moreover, some attempts on functionalization of protein superstructures for bioengineering and/or biomedical applications are also shortly discussed. We believe this mini review will outline the stream of hierarchical self-assembly of proteins through rationally designed supramolecular interfaces, which would open minds in visualizing protein-protein recognition and assembly in living cells and organisms, and even constructing multifarious functional bionanomaterials.

Indexed as

biofunctionalizationhierarchical nanostructuresprotein-protein interactionsprotein self-assemblysupramolecular interfaces

Identifiers

PMID32426335
PMCPMC7212437

What OpenQuestion holds

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Registered trials

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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.