Evidence map›Paper›PMID 32987103›Full record

ArticleInternational journal of antimicrobial agents2020

Design of novel viral attachment inhibitors of the spike glycoprotein (S) of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) through virtual screening and dynamics.

Arafat Rahman Oany, Mamun Mia, Tahmina Pervin, Md Junaid, S M Zahid Hosen, Mohammad Ali Moni

Abstract read
In one paragraph

Article in International journal of antimicrobial agents, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Advancements in the development of antivirals against SARS-Coronavirus.Frontiers in cellular and infection microbiology · 2025
    Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
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  11. Article
  12. Current Strategies of Antiviral Drug Discovery for COVID-19.Frontiers in molecular biosciences · 2021
    Review
  13. Article
  14. 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.

Arafat Rahman OanyDepartment of Biotechnology and Genetic Engineering, Faculty of Life Science, Mawlana Bhashani Science and Technology University, Tangail-1902, Bangladesh; Aristopharma Limited, Bangladesh. Electronic address: arafatr@outlook.com.
Mamun MiaDepartment of Biotechnology and Genetic Engineering, Faculty of Life Science, Mawlana Bhashani Science and Technology University, Tangail-1902, Bangladesh; Department of Medical Biotechnology, Bangladesh University of Health Sciences, Dhaka, Bangladesh.
Tahmina PervinBiotechnology and Genetic Engineering Discipline, Life Science School, Khulna University, Khulna, Bangladesh.
Md JunaidMolecular Modeling Drug-design and Discovery Laboratory, Pharmacology Research Division, BCSIR Laboratories Chattogram, Bangladesh Council of Scientific and Industrial Research, Chattogram, Bangladesh.
S M Zahid HosenMolecular Modeling Drug-design and Discovery Laboratory, Pharmacology Research Division, BCSIR Laboratories Chattogram, Bangladesh Council of Scientific and Industrial Research, Chattogram, Bangladesh; Pancreatic Research Group, South Western Sydney Clinical School, and Ingham Institute for Applied Medical Research, Faculty of Medicine, University of New South Wales, Sydney, Australia.
Mohammad Ali MoniWHO Collaborating Centre on eHealth, UNSW Digital Health, School of Public Health and Community Medicine, Faculty of Medicine, UNSW Sydney, Australia. Electronic address: m.moni@unsw.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To date, the global COVID-19 pandemic has been associated with 11.8 million cases and over 545481 deaths. In this study, we have employed virtual screening approaches and selected 415 lead-like compounds from 103 million chemical substances, based on the existing drugs, from PubChem databases as potential candidates for the S protein-mediated viral attachment inhibition. Thereafter, based on drug-likeness and Lipinski's rules, 44 lead-like compounds were docked within the active side pocket of the viral-host attachment site of the S protein. Corresponding ligand properties and absorption, distribution, metabolism, excretion, and toxicity (ADMET) profile were measured. Furthermore, four novel inhibitors were designed and assessed computationally for efficacy. Comparative analysis showed the screened compounds in this study maintain better results than the proposed mother compounds, VE607 and SSAA09E2. The four designed novel lead compounds possessed more fascinating output without deviating from any of Lipinski's rules. They also showed higher bioavailability and the drug-likeness score was 0.56 and 1.81 compared with VE607 and SSAA09E2, respectively. All the screened compounds and novel compounds showed promising ADMET properties. Among them, the compound AMTM-02 was the best candidate, with a docking score of -7.5 kcal/mol. Furthermore, the binding study was verified by molecular dynamics simulation over 100 ns by assessing the stability of the complex. The proposed screened compounds and the novel compounds may give some breakthroughs for the development of a therapeutic drug to treat SARS-CoV-2 proficiently in vitro and in vivo.

Indexed as

Drug DesignDrug Evaluation, PreclinicalAntiviral AgentsCatalytic DomainCOVID-19 Drug TreatmentHumansMolecular Dynamics SimulationPhylogenySARS-CoV-2Spike Glycoprotein, CoronavirusVirus AttachmentAntiviral AgentsSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2ADMETDrug designingMolecular dockingMolecular dynamicsVirtual screening

Identifiers

PMID32987103
PMCPMC7518233

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.