Evidence map›Paper›PMID 36364158›Full record

ArticleMolecules (Basel, Switzerland)2022

Homology Modeling and Molecular Dynamics-Driven Search for Natural Inhibitors That Universally Target Receptor-Binding Domain of Spike Glycoprotein in SARS-CoV-2 Variants.

Olha Ovchynnykova, Karina Kapusta, Natalia Sizochenko, Kostyantyn M Sukhyy, Wojciech Kolodziejczyk, Glake A Hill, Julia Saloni

Open access · goldAbstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 29% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Current computer-aided drug design · 2025
    Article
  3. Article
  4. Article
  5. Review
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.

Olha OvchynnykovaDepartment of Fuel, Polymer, and Polygraphic Materials Technologies, Ukrainian State University of Chemical Technology, 49005 Dnipro, Ukraine.
Karina KapustaDepartment of Chemistry and Physics, Tougaloo College, Tougaloo, MS 39174, USA.
Natalia SizochenkoThe Ronin Institute for Independent Scholarship, Montclair, NJ 07043, USA.ORCID 0000-0002-7039-7969
Kostyantyn M SukhyyDepartment of Fuel, Polymer, and Polygraphic Materials Technologies, Ukrainian State University of Chemical Technology, 49005 Dnipro, Ukraine.
Wojciech KolodziejczykInterdisciplinary Center for Nanotoxicity, Department of Chemistry, Physics and Atmospheric Sciences, Jackson State University, Jackson, MS 39217, USA.ORCID 0000-0002-7754-8969
Glake A HillInterdisciplinary Center for Nanotoxicity, Department of Chemistry, Physics and Atmospheric Sciences, Jackson State University, Jackson, MS 39217, USA.
Julia SaloniInterdisciplinary Center for Nanotoxicity, Department of Chemistry, Physics and Atmospheric Sciences, Jackson State University, Jackson, MS 39217, USA.ORCID 0000-0003-3995-2909
Jackson State University · USUkrainian State University of Chemical Technology · UARonin Institute · USTougaloo College · US

Funding

Training and Mentoring Core P20GM103476 · NIGMS · UNIVERSITY OF SOUTHERN MISSISSIPPI · PI MICHAEL R GARRETT · 2012 to 2026
$60.2M
NIGMS NIH HHS P20 GM103476
6 · The paper itself

Abstract

The rapid spread of SARS-CoV-2 required immediate actions to control the transmission of the virus and minimize its impact on humanity. An extensive mutation rate of this viral genome contributes to the virus' ability to quickly adapt to environmental changes, impacts transmissibility and antigenicity, and may facilitate immune escape. Therefore, it is of great interest for researchers working in vaccine development and drug design to consider the impact of mutations on virus-drug interactions. Here, we propose a multitarget drug discovery pipeline for identifying potential drug candidates which can efficiently inhibit the Receptor Binding Domain (RBD) of spike glycoproteins from different variants of SARS-CoV-2. Eight homology models of RBDs for selected variants were created and validated using reference crystal structures. We then investigated interactions between host receptor ACE2 and RBDs from nine variants of SARS-CoV-2. It led us to conclude that efficient multi-variant targeting drugs should be capable of blocking residues Q(R)493 and N487 in RBDs. Using methods of molecular docking, molecular mechanics, and molecular dynamics, we identified three lead compounds (hesperidin, narirutin, and neohesperidin) suitable for multitarget SARS-CoV-2 inhibition. These compounds are flavanone glycosides found in citrus fruits - an active ingredient of Traditional Chinese Medicines. The developed pipeline can be further used to (1) model mutants for which crystal structures are not yet available and (2) scan a more extensive library of compounds against other mutated viral proteins.

Indexed as

COVID-19 Drug TreatmentSARS-CoV-2Angiotensin-Converting Enzyme 2GlycoproteinsHumansMolecular Docking SimulationMolecular Dynamics SimulationMutationProtein BindingReceptors, VirusSpike Glycoprotein, CoronavirusAngiotensin-Converting Enzyme 2GlycoproteinsReceptors, VirusSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2COVID-19disinfectorshomology modelingmolecular dockingmolecular dynamicsmolecular mechanicsnatural compoundsreceptor-binding domainSARS-CoV-2 mutations

Identifiers

PMID36364158
PMCPMC9657887
OpenAlexW4307940644

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.