Evidence map›Paper›PMID 35811756›Full record

ArticleJournal of King Saud University. Science2022

An in-silico investigation of potential natural polyphenols for the targeting of COVID main protease inhibitor.

Nada H Aljarba, Md Saquib Hasnain, Mashael Mohammed Bin-Meferij, Saad Alkahtani

Open access · goldAbstract read
In one paragraph

Article in Journal of King Saud University. Science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.8field-weighted citation impact, top 13% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

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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 2 institutions in 1 country.

Nada H AljarbaDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Md Saquib HasnainDepartment of Pharmacy, Palamau Institute of Pharmacy, Chianki, Daltonganj 822102, Jharkhand, India.
Mashael Mohammed Bin-MeferijDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Saad AlkahtaniDepartment of Zoology, College of Science, King Saud University, P. O. Box 2455, Riyadh 11451, Saudi Arabia.
Princess Nourah bint Abdulrahman University · SAKing Saud University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The deadliest recent pandemic outbreak of COVID-19 disease has severely damaged the socio-economic health of the people globally. Due to unavailability of any effective vaccine or treatment the human beings are still struggling to overcome the pandemic condition. In an attempt to discover anti-COVID molecule, we used in-silico approach and reported 160 natural polyphenols to identify the most promising druggable HITs that can further used for drug discovery process. The co-crystallized structure COVID protease enzyme (PDB id 6LU7) was used. HTVS, MD simulation, binding energy calculations and in-silico ADME calculation were done and analyzed. Depending upon the scores three compounds galangin, nalsudaldain and rhamnezine were identified and the docking score were found to be -7.704, -6.51, -4.212 respectively. These docked complexes were further subjected to MD simulation runs over a 100 ns time and the RMSD and RMSF values were determined. The RMSD values of three compounds were found to be 2.9 Å, 7.6 Å & 9.5 Å respectively and the lowest RMSF values suggested the steady stability of ligand-protein complexes. The binding free energies (ΔG) of compounds with protein were found to be -49.8, -56.45, -62.87 kJ/mole. Moreover, in-silico ADME calculations indicated the drug likeliness properties of these molecules. By considering all these in-silico results the identified HITs would be the most probable anti-COVID drug molecules that can be further taken in wet lab and can act as lead for development of newer inhibitor of COVID-19 main protease enzyme.

Indexed as

COVID-19HTVSMD simulationsMproPolyphenols

Identifiers

PMID35811756
PMCPMC9250415
OpenAlexW4283788862

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.