Evidence map›Paper›PMID 33948424›Full record

ArticleNetwork modeling and analysis in health informatics and bioinformatics2021

Inhibitory effect of anti-HIV compounds extracted from Indian medicinal plants to retard the replication and transcription process of SARS-CoV-2: an insight from molecular docking and MD-simulation studies.

Tanmoy Dutta, Nabajyoti Baildya, Abdul Ashik Khan, Narendra Nath Ghosh

Abstract read
In one paragraph

Article in Network modeling and analysis in health informatics and bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Potential ofBioMed research international · 2022
    Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Inhibitory effect of compounds extracted fromJournal of molecular structure · 2022
    Article
  9. 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

4 authors.

Tanmoy DuttaDepartment of Chemistry, JIS College of Engineering, Kalyani, 741235 India.
Nabajyoti BaildyaDepartment of Chemistry, University of Kalyani, Kalyani, 741235 India.
Abdul Ashik KhanDepartment of Chemistry, Darjeeling Government College, Darjeeling, 734101 India.
Narendra Nath GhoshDepartment of Chemistry, University of Gour Banga, Mokdumpur, Malda, 732103 India.ORCID 0000-0001-6026-4639

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Outbreak of Coronavirus (SARS-CoV-2) has thrown a big challenge to the globe by snatching millions of human lives from the world. In this study, inhibitory efficiency of ten anti-HIV compounds from different Indian medicinal plant parts have been virtually screened against Mpro, PLpro and RdRp proteins of SARS-CoV-2. The molecular docking study reflected that among these compounds, Proptine (PTP) has the highest binding affinity for the three cases. Introduction of PTP molecules within the binding pocket of these proteins showed a large structural and conformational changes on the structure of proteins which is revealed from molecular dynamics (MD) simulation studies. RMSD, RMSF and analysis of thermodynamic parameters also revealed that PTP makes a huge impact on the structures of the respective proteins which will pave an opportunity for doing advanced experimental research to evaluate the potential drug to combat COVID-19. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13721-021-00309-3.

Indexed as

Anti-HIVCOVID-19Molecular dynamics simulationMproPLproProptineRdRpSARS-CoV-2

Identifiers

PMID33948424
PMCPMC8084713

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.