Evidence map›Paper›PMID 36213321›Full record

ArticleChemicke zvesti2023

Potential antiviral peptides against the nucleoprotein of SARS-CoV-2.

Iktedar Mahdi, Humyara Yeasmin, Imtiaz Hossain, Raina Masnoon Badhan, Md Ackas Ali, Md Abdul Kaium, Rajib Islam, Md Abu Sufian, Mohammad A Halim

Open access · greenAbstract read
In one paragraph

Article in Chemicke zvesti, 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
0.3field-weighted citation impact, top 47% 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, 3 citations in OpenAlex.

  1. Article
  2. Review
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

9 authors at 4 institutions in 3 countries.

Iktedar MahdiDivision of Infectious Diseases and Division of Computer-Aided Drug Design, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215 Bangladesh.
Humyara YeasminDivision of Infectious Diseases and Division of Computer-Aided Drug Design, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215 Bangladesh.
Imtiaz HossainDivision of Infectious Diseases and Division of Computer-Aided Drug Design, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215 Bangladesh.
Raina Masnoon BadhanDivision of Infectious Diseases and Division of Computer-Aided Drug Design, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215 Bangladesh.
Md Ackas AliDivision of Infectious Diseases and Division of Computer-Aided Drug Design, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215 Bangladesh.
Md Abdul KaiumDivision of Infectious Diseases and Division of Computer-Aided Drug Design, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215 Bangladesh.
Rajib IslamDivision of Infectious Diseases and Division of Computer-Aided Drug Design, The Red-Green Research Centre, BICCB, 16 Tejkunipara, Tejgaon, Dhaka, 1215 Bangladesh.
Md Abu SufianSchool of Pharmacy, Temple University, Philadelphia, PA 19140 USA.
Mohammad A HalimDepartment of Chemistry and Biochemistry, Kennesaw State University, Kennesaw, GA 30144 USA.ORCID 0000-0002-1698-7044
Bangladesh Jute Research Institute · BDKennesaw State University · USNorwegian University of Science and Technology · NOTemple University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nucleoprotein is a conserved structural protein of SARS-CoV-2, which is involved in several functions, including replication, packaging, and transcription. In this research, 21 antiviral peptides that are known to have inhibitory function against nucleoprotein in several other viruses, were screened computationally against the nucleoprotein of SARS-CoV-2. The complexes of five best performing peptides (AVP1142, AVP1145, AVP1148, AVP1150, AVP1155) with nucleoprotein were selected for subsequent screening via 5 ns molecular dynamics (MD) simulation. Two peptides, namely AVP1145 and AVP1155, came out as promising candidates and hence were selected for 200 ns MD simulation for further validation, incorporating a DMPC-based membrane environment. In the long MD simulation, both AVP1155 and AVP1145 utilized multiple residues-mainly aromatic, acidic, and nonpolar residues-as interacting points to remain in contact with the nucleoprotein and formed predominantly hydrogen bonds along with hydrophobic and electrostatic interactions. However, AVP1155 proved to be superior to AVP1145 when its complex with nucleoprotein was analyzed in terms of root-mean-square deviation, root-mean-square fluctuation, radius of gyration, solvent accessible surface area and free energy landscape. In a nutshell, the findings of this research may guide future studies in the development of selective peptide inhibitors of SARS-CoV-2 nucleoprotein. Supplementary Information: The online version contains supplementary material available at 10.1007/s11696-022-02514-4.

Indexed as

Antiviral peptidesInteracting residuesMolecular dynamics simulationNucleoproteinSARS-CoV-2

Identifiers

PMID36213321
PMCPMC9531640
OpenAlexW4300981349

What Socratic 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 Socratic graph.