Evidence map›Paper›PMID 31823246›Full record

ArticleGlycoconjugate journal2020

Multifaceted antibodies development against synthetic α-dystroglycan mucin glycopeptide as promising tools for dystroglycanopathies diagnostic.

Thais Canassa-DeLeo, Vanessa Leiria Campo, Lílian Cataldi Rodrigues, Marcelo Fiori Marchiori, Carlos Fuzo, Marcelo Macedo Brigido, Annamaria Sandomenico, Menotti Ruvo, Andrea Queiroz Maranhão, Marcelo Dias-Baruffi

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Article in Glycoconjugate journal, 2020. 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
0.3field-weighted citation impact, top 42% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. 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

10 authors at 4 institutions in 2 countries.

Thais Canassa-DeLeoFaculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Av. Café S/N, CEP, Ribeirão Preto, SP, 14040-903, Brazil.
Vanessa Leiria CampoFaculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Av. Café S/N, CEP, Ribeirão Preto, SP, 14040-903, Brazil.
Lílian Cataldi RodriguesFaculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Av. Café S/N, CEP, Ribeirão Preto, SP, 14040-903, Brazil.
Marcelo Fiori MarchioriFaculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Av. Café S/N, CEP, Ribeirão Preto, SP, 14040-903, Brazil.
Carlos FuzoFaculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Av. Café S/N, CEP, Ribeirão Preto, SP, 14040-903, Brazil.
Marcelo Macedo BrigidoInstituto de Ciências Biológicas, Universidade de Brasília, Asa Norte, Brasília, DF, CEP 70910-900, Brazil.
Annamaria SandomenicoIstituto di Biostrutture e Bioimmagini, CNR, via Mezzocannone, 16, 80134, Naples, Italy.
Menotti RuvoIstituto di Biostrutture e Bioimmagini, CNR, via Mezzocannone, 16, 80134, Naples, Italy.
Andrea Queiroz MaranhãoInstituto de Ciências Biológicas, Universidade de Brasília, Asa Norte, Brasília, DF, CEP 70910-900, Brazil.
Marcelo Dias-BaruffiFaculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Av. Café S/N, CEP, Ribeirão Preto, SP, 14040-903, Brazil. mdbaruff@fcfrp.usp.br.ORCID 0000-0002-2039-1884
Universidade de São Paulo · BRInstitute of Biostructure and Bioimaging · ITUniversidade de Brasília · BRUniversidade de Ribeirão Preto · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dystroglycanopathies are diseases characterized by progressive muscular degeneration and impairment of patient's quality of life. They are associated with altered glycosylation of the dystrophin-glycoprotein (DGC) complex components, such as α-dystroglycan (α-DG), fundamental in the structural and functional stability of the muscle fiber. The diagnosis of dystroglycanopathies is currently based on the observation of clinical manifestations, muscle biopsies and enzymatic measures, and the available monoclonal antibodies are not specific for the dystrophic hypoglycosylated muscle condition. Thus, modified α-DG mucins have been considered potential targets for the development of new diagnostic strategies toward these diseases. In this context, this work describes the synthesis of the hypoglycosylated α-DG mimetic glycopeptide NHAc-Gly-Pro-Thr-Val-Thr[αMan]-Ile-Arg-Gly-BSA (1) as a potential tool for the development of novel antibodies applicable to dystroglycanopathies diagnosis. Glycopeptide 1 was used for the development of polyclonal antibodies and recombinant monoclonal antibodies by Phage Display technology. Accordingly, polyclonal antibodies were reactive to glycopeptide 1, which enables the application of anti-glycopeptide 1 antibodies in immune reactive assays targeting hypoglycosylated α-DG. Regarding monoclonal antibodies, for the first time variable heavy (VH) and variable light (VL) immunoglobulin domains were selected by Phage Display, identified by NGS and described by in silico analysis. The best-characterized VH and VL domains were cloned, expressed in E. coli Shuffle T7 cells, and used to construct a single chain fragment variable that recognized the Glycopeptide 1 (GpαDG1 scFv). Molecular modelling of glycopeptide 1 and GpαDG1 scFv suggested that their interaction occurs through hydrogen bonds and hydrophobic contacts involving amino acids from scFv (I51, Y33, S229, Y235, and P233) and R8 and α-mannose from Glycopeptide 1.

Indexed as

Antibodies, MonoclonalDystroglycansGlycoproteinsHumansMucinsWalker-Warburg SyndromeAntibodies, MonoclonalDystroglycansGlycoproteinsMucinsAntibodiesGlycopeptideMucinsPhage display, molecular Modellingα-Dystroglycan

Identifiers

PMID31823246
OpenAlexW2995402691

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.