Evidence map›Paper›PMID 34827585›Full record

ArticleBiomolecules2021

Glycan Epitopes and Potential Glycoside Antagonists of DC-SIGN Involved in COVID-19: In Silico Study.

Meina Gao, Hui Li, Chenghao Ye, Kaixian Chen, Hualiang Jiang, Kunqian Yu

Open access · goldAbstract read
In one paragraph

Article in Biomolecules, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 46% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

6 authors at 3 institutions in 1 country.

Meina GaoSchool of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China.
Hui LiDrug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 200031, China.ORCID 0000-0002-9639-4301
Chenghao YeDepartment of Chemistry, Shantou University, Shantou 515063, China.
Kaixian ChenSchool of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China.
Hualiang JiangSchool of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing 210023, China.
Kunqian YuDrug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 200031, China.
Nanjing University of Chinese Medicine · CNChinese Academy of Sciences · CNShantou University · CN

Funding

National Key R & D Program of China (2020YFC0841400) 2020YFC0841400Strategic Priority Research Program of the Chinese Academy of Sciences XDPB2505the National Science and Technology Major Project of the Ministry of Science and Technology of China 2018ZX09711002the Shanghai Municipal Science and Technology Major Project, the National Natural Science Foundation of China 81773634
6 · The paper itself

Abstract

Glycosylation is an important post-translational modification that affects a wide variety of physiological functions. DC-SIGN (Dendritic Cell-Specific Intercellular adhesion molecule-3-Grabbing Non-integrin) is a protein expressed in antigen-presenting cells that recognizes a variety of glycan epitopes. Until now, the binding of DC-SIGN to SARS-CoV-2 Spike glycoprotein has been reported in various articles and is regarded to be a factor in systemic infection and cytokine storm. The mechanism of DC-SIGN recognition offers an alternative method for discovering new medication for COVID-19 treatment. Here, we discovered three potential pockets that hold different glycan epitopes by performing molecular dynamics simulations of previously reported oligosaccharides. The "EPN" motif, "NDD" motif, and Glu354 form the most critical pocket, which is known as the Core site. We proposed that the type of glycan epitopes, rather than the precise amino acid sequence, determines the recognition. Furthermore, we deduced that oligosaccharides could occupy an additional site, which adds to their higher affinity than monosaccharides. Based on our findings and previously described glycoforms on the SARS-CoV-2 Spike, we predicted the potential glycan epitopes for DC-SIGN. It suggested that glycan epitopes could be recognized at multiple sites, not just Asn234, Asn149 and Asn343. Subsequently, we found that Saikosaponin A and Liquiritin, two plant glycosides, were promising DC-SIGN antagonists in silico.

Indexed as

Amino Acid MotifsBinding SitesCell Adhesion MoleculesComputer SimulationCOVID-19CytokinesDC-Specific ICAM-3 Grabbing NonintegrinEpitopesFlavanonesGlucosidesGlycosidesHumansLectins, C-TypeLigandsMolecular Docking SimulationMolecular Dynamics SimulationCell Adhesion MoleculesCytokinesDC-Specific ICAM-3 Grabbing NonintegrinEpitopesFlavanonesGlucosidesGlycosidesLectins, C-TypeLigandsliquiritinMonosaccharidesOleanolic AcidPolysaccharidesReceptors, Cell Surfacesaikosaponin DSaponinsSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2carbohydrate recognition mechanismCOVID-19DC-SIGNglycan epitopesmolecular dynamics simulationsnatural glycoside antagonists

Identifiers

PMID34827585
PMCPMC8615854
OpenAlexW3211263342

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.