Evidence map›Paper›PMID 36691520›Full record

ArticleApplied nanoscience2023

Density functional theory and molecular docking study to lutein molecule for COVID-19 protease inhibitors.

Dhaidan Khalaf Kafi, Adil N Ayyash

Abstract read
In one paragraph

Article in Applied nanoscience, 2023. 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
–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

2 citing papers in PubMed.

  1. Review
  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

2 authors.

Dhaidan Khalaf KafiDepartment of Medical Physics, College of Applied Science, University of Fallujah, Baghdad, Iraq.ORCID 0000-0003-1505-4020
Adil N AyyashDepartment of Physics, College of Science, University of Anbar, Ramadi, Iraq.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the beginning of the corona pandemic, numerous scientific projects have been conducted worldwide to investigate how the new virus can be combated. Researchers are developing various vaccines and drugs at full speed - with varying degrees of success. In this work, silico screening (molecular docking analysis) is performed on twenty natural compounds, which are expected to provide valuable lead molecules and medication to treat a new condition SARS-CoV-2. Our results indicate that out of the 20 compounds on the candidate list, lutein and Polydatin, natural components of fruits and vegetables (especially egg yolk and maize) have shown an excellent performance in our docking studies through a minimum binding energy of - 9.8 kcal/mol also - 7.4 kcal/mol, separately. This indicates their potential for the inhibitory molecular interactions against COVID-19. The main intent of the research is to analyse the protein components and investigate the molecules.

Indexed as

Active sites.LuteinCOVID-19Molecular dockingPolyphenols

Identifiers

PMID36691520
PMCPMC9850325

What OpenQuestion holds

Textmetadata
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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.