Evidence map›Paper›PMID 33532671›Full record

ArticleComputational toxicology (Amsterdam, Netherlands)2021

From genomes to molecular dynamics - A bottom up approach in extrication of SARS CoV-2 main protease inhibitors.

S Aishwarya, K Gunasekaran, R Sagaya Jansi, G Sangeetha

Open access · greenAbstract read
In one paragraph

Article in Computational toxicology (Amsterdam, Netherlands), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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 at 1 institution in 1 country.

S AishwaryaDepartment of Bioinformatics, Stella Maris College (Autonomous), Chennai 600086, India.
K GunasekaranCentre for Advanced Studies in Crystallography and Biophysics, University of Madras, Chennai 600025, India.
R Sagaya JansiDepartment of Bioinformatics, Stella Maris College (Autonomous), Chennai 600086, India.
G SangeethaCentre for Advanced Studies in Crystallography and Biophysics, University of Madras, Chennai 600025, India.
University of Madras · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recent pandemic Coronavirus disease-19 outbreak had traumatized global countries since its origin in late December 2019. Though the virus originated in China, it has spread rapidly across the world due its firmly established community transmission. To successfully tackle the spread and further infection, there needs a clear multidimensional understanding of the molecular mechanisms. Henceforth, 942 viral genome sequences were analysed to predict the core genomes crucial in virus life cycle. Additionally, 35 small interfering RNA transcripts were predicted that can target specifically the viral core proteins and reduce pathogenesis. The crystal structure of Covid-19 main protease-6LU7 was chosen as an attractive target due to the factors that there were fewer mutations and whose structure had significant identity to the annotated protein sequence of the core genome. Drug repurposing of both recruiting and non recruiting drugs was carried out through molecular docking procedures to recognize bitolterol as a good inhibitor of Covid-19 protease. The study was extended further to screen antiviral phytocompounds through quantitative structure activity relationship and molecular docking to identify davidigenin, from licorice as the best novel lead with good interactions and binding energy. The docking of the best compounds in all three categories was validated with molecular dynamics simulations which implied stable binding of the drug and lead molecule. Though the studies need clinical evaluations, the results are suggestive of curbing the pandemic.

Indexed as

Covid-19Drug repurposingMolecular dynamicsPangenomicsProteomicssRNA transcriptomics

Identifiers

PMID33532671
PMCPMC7844360
OpenAlexW3128163801

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.