Evidence map›Paper›PMID 33074111›Full record

ArticleComputers in biology and medicine2020

Structural and molecular basis of the interaction mechanism of selected drugs towards multiple targets of SARS-CoV-2 by molecular docking and dynamic simulation studies- deciphering the scope of repurposed drugs.

Sinosh Skariyachan, Dharshini Gopal, Shweta Chakrabarti, Priya Kempanna, Akshay Uttarkar, Aditi G Muddebihalkar, Vidya Niranjan

Open access · greenAbstract read
In one paragraph

Article in Computers in biology and medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
5.6field-weighted citation impact, top 3% 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

22 citing papers in PubMed, 51 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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 3 institutions in 2 countries.

Sinosh SkariyachanDepartment of Microbiology, St. Pius X College Rajapuram, Kasaragod, Kerala, India. Electronic address: sinoshmicro@stpius.ac.in.
Dharshini GopalDepartment of Bioinformatics, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Shweta ChakrabartiDepartment of Bioinformatics, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Priya KempannaDepartment of Biotechnology, Dayananda Sagar College of Engineering, Bangalore, India.
Akshay UttarkarDepartment of Biotechnology, RV College of Engineering, Bengaluru, Karnataka, India.
Aditi G MuddebihalkarDepartment of Biotechnology, RV College of Engineering, Bengaluru, Karnataka, India.
Vidya NiranjanDepartment of Biotechnology, RV College of Engineering, Bengaluru, Karnataka, India.
Manipal Academy of Higher Education · INDr. Hari Singh Gour University · INEngeniusMicro (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The repurposing of FDA approved drugs is presently receiving attention for COVID-19 drug discovery. Previous studies revealed the binding potential of several FDA-approved drugs towards specific targets of SARS-CoV-2; however, limited studies are focused on the structural and molecular basis of interaction of these drugs towards multiple targets of SARS-CoV-2. The present study aimed to predict the binding potential of six FDA drugs towards fifteen protein targets of SARS-CoV-2 and propose the structural and molecular basis of the interaction by molecular docking and dynamic simulation. Based on the literature survey, fifteen potential targets of SARS-CoV-2, and six FDA drugs (Chloroquine, Hydroxychloroquine, Favipiravir, Lopinavir, Remdesivir, and Ritonavir) were selected. The binding potential of individual drug towards the selected targets was predicted by molecular docking in comparison with the binding of the same drugs with their usual targets. The stabilities of the best-docked conformations were confirmed by molecular dynamic simulation and energy calculations. Among the selected drugs, Ritonavir and Lopinavir showed better binding towards the prioritized targets with minimum binding energy (kcal/mol), cluster-RMS, number of interacting residues, and stabilizing forces when compared with the binding of Chloroquine, Favipiravir, and Hydroxychloroquine, later drugs demonstrated better binding when compared to the binding with their usual targets. Remdesvir showed better binding to the prioritized targets in comparison with the binding of Chloroquine, Favipiravir, and Hydroxychloroquine, but showed lesser binding potential when compared to the interaction between Ritonavir and Lopinavir and the prioritized targets. The structural and molecular basis of interactions suggest that the FDA drugs can be repurposed towards multiple targets of SARS-CoV-2, and the present computational models provide insights on the scope of repurposed drugs against COVID-19.

Indexed as

Molecular Docking SimulationMolecular Dynamics SimulationViral ProteinsAntiviral AgentsBetacoronavirusCoronavirus InfectionsCOVID-19Drug RepositioningHumansPandemicsPneumonia, ViralSARS-CoV-2Antiviral AgentsViral ProteinsComputational modelsCOVID-19Potential molecular targetsRepurposed drugsSARS-CoV-2Structural and molecular mechanism

Identifiers

PMID33074111
PMCPMC7554297
OpenAlexW3093319400

What OpenQuestion holds

Textmetadata
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.