Evidence map›Paper›PMID 39052567›Full record

ArticlePloS one2024

In silico exploration of deep-sea fungal metabolites as inhibitor of Ebola and Marburg VP35 and VP40.

Abdullah R Alanzi, Mohammed F Alajmi, Mohammed S Al-Dosari, Mohammad K Parvez, Moneerah J Alqahtani

Abstract read
In one paragraph

Article in PloS one, 2024. 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

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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. Article
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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

5 authors.

Abdullah R AlanziDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.ORCID 0009-0000-2565-6573
Mohammed F AlajmiDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Mohammed S Al-DosariDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Mohammad K ParvezDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Moneerah J AlqahtaniDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

VP30 and VP40 proteins of Ebola and Marburg viruses have been recognized as potential targets for antiviral drug development due to their essential roles in the viral lifecycle. Targeting these proteins could disrupt key stages of the viral replication process, inhibiting the viruses' ability to propagate and cause disease. The current study aims to perform molecular docking and virtual screening on deep-sea fungal metabolites targeting Marburg virus VP40 Dimer, matrix protein VP40 from Ebola virus Sudan, Ebola VP35 Interferon Inhibitory Domain, and VP35 from Marburg virus. The top ten compounds for each protein target were chosen using the glide score. All the compounds obtained indicate a positive binding interaction. Furthermore, AdmetSAR was utilized to investigate the pharmacokinetics of the inhibitors chosen. Gliotoxin was used as a ligand with Marburg virus VP40 Dimer, Austinol with matrix protein VP40 from Ebola virus Sudan, Ozazino-cyclo-(2,3-dihydroxyl-trp-tyr) with Ebola VP35 Interferon Inhibitory Domain, and Dehydroaustinol with VP35 from Marburg virus. MD modeling and MMPBSA studies were used to provide a better understanding of binding behaviors. Pre-clinical experiments can assist validate our in-silico studies and assess whether the molecule can be employed as an anti-viral drug.

Indexed as

Antiviral AgentsEbolavirusMarburgvirusMolecular Docking SimulationComputer SimulationHemorrhagic Fever, EbolaHumansMolecular Dynamics SimulationViral Matrix ProteinsViral Regulatory and Accessory ProteinsAntiviral AgentsViral Matrix ProteinsViral Regulatory and Accessory ProteinsVP35 protein, filovirusVP40 protein, virus

Identifiers

PMID39052567
PMCPMC11271895

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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.