Evidence map›Paper›PMID 38307890›Full record

ArticleScientific reports2024

Targeting the receptor binding domain and heparan sulfate binding for antiviral drug development against SARS-CoV-2 variants.

Zi-Sin Yang, Tzong-Shiun Li, Yu-Sung Huang, Cheng-Chung Chang, Ching-Ming Chien

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.3field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

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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

5 authors at 4 institutions in 1 country.

Zi-Sin Yang *Department of Medical Sciences Industry, College of Health Sciences, Chang Jung Christian University, Tainan, 711, Taiwan.
Tzong-Shiun Li *Graduate Institute of Biomedical Engineering, National Chung Hsing University, Taichung, 402, Taiwan.
Yu-Sung HuangInstitute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, 300, Taiwan.
Cheng-Chung ChangGraduate Institute of Biomedical Engineering, National Chung Hsing University, Taichung, 402, Taiwan.
Ching-Ming ChienDepartment of Medical Sciences Industry, College of Health Sciences, Chang Jung Christian University, Tainan, 711, Taiwan. cmchien@mail.cjcu.edu.tw.
Chang Jung Christian University · TWChang Bing Show Chwan Memorial Hospital · TWNational Chung Hsing University · TWNational Tsing Hua University · TW

Funding

the Ministry of Science and Technology, Taiwan NSTC 111-2311-B-309-001-MY3 to C.-M.C.
6 · The paper itself

Abstract

The emergence of SARS-CoV-2 variants diminished the efficacy of current antiviral drugs and vaccines. Hence, identifying highly conserved sequences and potentially druggable pockets for drug development was a promising strategy against SARS-CoV-2 variants. In viral infection, the receptor-binding domain (RBD) proteins are essential in binding to the host receptor. Others, Heparan sulfate (HS), widely distributed on the surface of host cells, is thought to play a central role in the viral infection cycle of SARS-CoV-2. Therefore, it might be a reasonable strategy for antiviral drug design to interfere with the RBD in the HS binding site. In this study, we used computational approaches to analyze multiple sequences of coronaviruses and reveal important information about the binding of HS to RBD in the SARS-CoV-2 spike protein. Our results showed that the potential hot-spots, including R454 and E471, in RBD, exhibited strong interactions in the HS-RBD binding region. Therefore, we screened different compounds in the natural product database towards these hot-spots to find potential antiviral candidates using LibDock, Autodock vina and furthermore applying the MD simulation in AMBER20. The results showed three potential natural compounds, including Acetoside (ACE), Hyperoside (HYP), and Isoquercitrin (ISO), had a strong affinity to the RBD. Our results demonstrate a feasible approach to identify potential antiviral agents by evaluating the binding interaction between viral glycoproteins and host receptors. The present study provided the applications of the structure-based computational approach for designing and developing of new antiviral drugs against SARS-CoV-2 variants.

Indexed as

COVID-19SARS-CoV-2Spike Glycoprotein, CoronavirusAntiviral AgentsBinding SitesDrug DevelopmentHumansProtein BindingAntiviral AgentsSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2

Identifiers

PMID38307890
PMCPMC10837157
OpenAlexW4391483614

What OpenQuestion holds

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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.