Evidence map›Paper›PMID 33860009›Full record

ArticleJournal of advanced veterinary and animal research2021

Molecular optimization, docking, and dynamic simulation profiling of selective aromatic phytochemical ligands in blocking the SARS-CoV-2 S protein attachment to ACE2 receptor: an

Dipta Dey, Parag Kumar Paul, Salauddin Al Azad, Mohammad Faysal Al Mazid, Arman Mahmud Khan, Md Arman Sharif, Md Hafijur Rahman

Open access · goldAbstract read
In one paragraph

Article in Journal of advanced veterinary and animal research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
5.7field-weighted citation impact, top 4% 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

28 citing papers in PubMed, 61 citations in OpenAlex.

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  16. Study ofMolecules (Basel, Switzerland) · 2023
    Article
  17. Article
  18. Article
  19. Small molecules in the treatment of COVID-19.Signal transduction and targeted therapy · 2022
    Review
  20. Molecular identification, characterization, and antagonistic activity profiling ofJournal of advanced veterinary and animal research · 2022
    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

7 authors at 4 institutions in 2 countries.

Dipta DeyBiochemistry and Molecular Biology Department, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh.
Parag Kumar PaulCentre for Energy Research, Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh.
Salauddin Al AzadFermentation Engineering Major, School of Biotechnology, Jiangnan University, Wuxi, China.
Mohammad Faysal Al MazidDepartment of Biomedical Science, Korea Institute of Science and Technology, Seongbuk-gu, Seoul-02792, Republic of Korea.
Arman Mahmud KhanBiotechnology and Genetic Engineering Discipline, Life Science School, Khulna University, Khulna, Bangladesh.
Md Arman SharifBiotechnology and Genetic Engineering Discipline, Life Science School, Khulna University, Khulna, Bangladesh.
Md Hafijur RahmanBiotechnology and Genetic Engineering Discipline, Life Science School, Khulna University, Khulna, Bangladesh.
Khulna University · BDBangabandhu Sheikh Mujibur Rahman Science and Technology University · BDKorea University of Science and Technology · KRUnited International University · BD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe comprehensive MATERIALS AND

methodsA library of 57 aromatic pharmacophore phytochemical ligands was prepared from where the top five ligands depending on Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) and quantitative structure-activity relationship (QSAR)-based pharmacokinetic properties were considered. The selected ligands were optimized for commencing molecular docking and dynamic simulation as a complex with the ACE2 receptor to compare their blocking efficacy with the control drug. The ligand-receptor complexes' accuracy in preventing the Spike (S) protein of SARS-CoV-2 penetration inside the host cells has been analyzed through hydrogen-hydrophobic bond interactions, principal component analysis (PCA), root mean square deviation (RMSD), root mean square fluctuation (RMSF), and B-Factor. Advanced

resultsADMET and QSAR revealed Rhamnetin, Lactupicrin, Rhinacanthin D, Flemiflavanone D, and Exiguaflavanone A as the ligands of our interest to be compared with the control Cassiarin D. According to the molecular docking binding affinity to block ACE2 receptor, the efficiency mountings were Rhinacanthin D > Flemiflavanone D > Lactupicrin > Exiguaflavanone A > Rhamnetin. The binding affinity of the Cassiarin D-ACE2 complex was (-10.2 KJ/mol) found inferior to the Rhinacanthin D-ACE2 complex (-10.8 KJ/mol), referring to Rhinacanthin D as a more stable candidate to use as drugs. The RMSD values of protein-ligand complexes evaluated according to their structural conformation and stable binding pose ranged between 0.1~2.1 Å. The B-factor showed that very few loops were present in the protein structure. The RMSF peak fluctuation regions ranged 5-250, predicting efficient ligand-receptor interactions.

conclusionThe experiment sequentially measures all the parameters required in referring to any pharmacophore as a drug, considering which all aromatic components analyzed in the study can strongly be predicted as target-specific medication against the novel coronavirus 2019 infection.

Indexed as

Antiviral efficacydynamic simulationmolecular dockingprincipal component analysistargeted drug designing

Identifiers

PMID33860009
PMCPMC8043340
OpenAlexW3138291079

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.