Evidence map›Paper›PMID 34596851›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

The Discovery of Peptide Macrocycle Rescuers of Pathogenic Protein Misfolding and Aggregation by Integrating SICLOPPS Technology and Ultrahigh-Throughput Screening in Bacteria.

Dafni C Delivoria, Georgios Skretas

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 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
1.6field-weighted citation impact, top 17% 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, 4 citations in OpenAlex.

  1. Article
  2. Natural and Man-Made Cyclic Peptide-Based Antibiotics.Antibiotics (Basel, Switzerland) · 2022
    Review
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

2 authors at 1 institution in 1 country.

Dafni C DelivoriaInstitute of Chemical Biology, National Hellenic Research Foundation, Athens, Greece.
Georgios SkretasInstitute of Chemical Biology, National Hellenic Research Foundation, Athens, Greece. gskretas@eie.gr.
National Hellenic Research Foundation · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The phenomenon of protein misfolding and aggregation has been widely associated with numerous human diseases, such as Alzheimer's disease, systemic amyloidosis and type 2 diabetes, the vast majority of which remain incurable. To advance early stage drug discovery against these diseases, investigation of molecular libraries with expanded diversities and ultrahigh-throughput screening methodologies that allow deeper investigation of chemical space are urgently required. Toward this, we describe how Escherichia coli can be engineered so as to enable (1) the production of expanded combinatorial libraries of short, drug-like, head-to-tail cyclic peptides and (2) their simultaneous functional screening for identifying effective inhibitors of protein misfolding and aggregation using a genetic assay that links protein folding and misfolding to cell fluorescence. In this manner, cyclic peptides with the ability to inhibit pathogenic protein misfolding and/or aggregation can be readily selected by flow cytometric cell sorting in an ultrahigh-throughput fashion. This biotechnological approach accelerates significantly the identification of hit/lead molecules with potentially therapeutic properties against devastating diseases.

Indexed as

Protein FoldingDiabetes Mellitus, Type 2Escherichia coliHumansPeptidesPeptides, CyclicProteinsTechnologyPeptidesPeptides, CyclicProteinsCyclic peptidesHigh-throughput screeningProtein aggregationProtein misfolding diseasesSICLOPPS technology

Identifiers

PMID34596851
OpenAlexW3201756604

What OpenQuestion holds

Textmetadata
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.