Evidence map›Paper›PMID 40733589›Full record

ArticleViruses2025

Repurposing of Some Nucleoside Analogs Targeting Some Key Proteins of the Avian H5N1 Clade 2.3.4.4b to Combat the Circulating HPAI in Birds: An In Silico Approach.

Mohd Yasir Khan, Abid Ullah Shah, Nithyadevi Duraisamy, Mohammed Cherkaoui, Maged Gomaa Hemida

Abstract read
In one paragraph

Article in Viruses, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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.

Mohd Yasir KhanDepartment of Computer Science, College of Digital Engineering and Artificial Intelligence, Long Island University, Brooklyn, NY 11201, USA.ORCID 0000-0003-1107-7428
Abid Ullah ShahDepartment of Veterinary Biomedical Sciences, College of Veterinary Medicine, Long Island University, 720 Northern Boulevard, Brookville, NY 11548, USA.
Nithyadevi DuraisamyDepartment of Computer Science, College of Digital Engineering and Artificial Intelligence, Long Island University, Brooklyn, NY 11201, USA.
Mohammed CherkaouiDepartment of Computer Science, College of Digital Engineering and Artificial Intelligence, Long Island University, Brooklyn, NY 11201, USA.
Maged Gomaa HemidaDepartment of Veterinary Biomedical Sciences, College of Veterinary Medicine, Long Island University, 720 Northern Boulevard, Brookville, NY 11548, USA.ORCID 0000-0003-1663-5820

Funding

Heilbrunn Family College of Veterinary Medicine Research and Scholarship Fund RESEARCH PROJECT 1Long Island Univeristy 40262Long Island University 36524USDA-NIFA Animal Health and Disease NI24AHDRXXXXG066
6 · The paper itself

Abstract

(1) Background: The highly pathogenic avian influenza virus H5N1 clade 2.3.4.4b is an emerging threat that poses a great risk to the poultry industry. A few human cases have been linked to the infection with this clade in many parts of the world, including the USA. Unfortunately, there are no specific vaccines or antiviral drugs that could help prevent and treat the infection caused by this virus in birds. Our major objective is to identify/repurpose some (novel/known) antiviral compounds that may inhibit viral replication by targeting some key viral proteins. (2) Methods: We used state-of-the-art machine learning tools such as molecular docking and MD-simulation methods from Biovia Discovery Studio (v24.1.0.321712). The key target proteins such as hemagglutinin (HA), neuraminidase (NA), Matrix-2 protein (M2), and the cap-binding domain of PB2 (PB2/CBD) homology models were validated through structural assessment via DOPE scores, Ramachandran plots, and Verify-3D metrics, ensuring reliable structural representations, confirming their reliability for subsequent in silico approaches. These approaches include molecular docking followed by molecular dynamics simulation for 50 nanoseconds (ns), highlighting the structural stability and compactness of the docked complexes. (3) Results: Molecular docking revealed strong binding affinities for both sofosbuvir and GS441524, particularly with the NA and PB2/CBD protein targets. Among them, GS441524 exhibited superior interaction scores and a greater number of hydrogen bonds with key functional residues of NA and PB2/CBD. The MM-GBSA binding free energy calculations further supported these findings, as GS441524 displayed more favorable binding energies compared to several known standard inhibitors, including F0045S for HA, Zanamivir for NA, Rimantadine and Amantadine for M2, and PB2-39 for PB2/CBD. Additionally, 50 ns molecular dynamics simulations highlighted the structural stability and compactness of the GS441524-PB2/CBD complex, further supporting its potential as a promising antiviral candidate. Furthermore, hydrogen bond monitor analysis over the 50 ns simulation confirmed persistent and specific interactions between the ligand and proteins, suggesting that GS441524 may effectively inhibit the NA, and PB2/CBD might potentially disrupt PB2-mediated RNA synthesis. (4) Conclusions: Our findings are consistent with previous evidence supporting the antiviral activity of certain nucleoside analog inhibitors, including GS441524, against various coronaviruses. These results further support the potential repurposing of GS441524 as a promising therapeutic candidate against H5N1 avian influenza clade 2.3.4.4b. However, further functional studies are required to validate these in silico predictions and support the inhibitory action of GS441524 against the targeted proteins of H5N1, specifically clade 2.3.4.4b.

Indexed as

Antiviral AgentsDrug RepositioningInfluenza A Virus, H5N1 SubtypeInfluenza in BirdsNucleosidesViral ProteinsAnimalsBirdsComputer SimulationMolecular Docking SimulationMolecular Dynamics SimulationVirus ReplicationAntiviral AgentsNucleosidesViral Proteinsclade 2.3.4.4bH5N1highly pathogenic avian influenza virushomology modelhydrogen bond monitormolecular dockingnucleoside analog

Identifiers

PMID40733589
PMCPMC12299010

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Registered trials

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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.