Evidence map›Paper›PMID 42749451›Full record

ArticleJournal, genetic engineering & biotechnology2026

RNAi-based therapeutics targeting the F gene in human metapneumovirus: An in-silico approach.

Proshanto Ghosh, Md Nur Islam, Shahriar Hossain, Ayesha Akter, Naima Akter Munni, Md Abunasar Miah, Muhammad Tawhid, Md Easin Mia

Abstract read
In one paragraph

Article in Journal, genetic engineering & biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Proshanto GhoshDepartment of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh.
Md Nur IslamDepartment of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh; Centre for Life-Science Advancement in Bioinformatics (cLAB), Noakhali 3814, Bangladesh.
Shahriar HossainDepartment of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh.
Ayesha AkterDepartment of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh.
Naima Akter MunniDepartment of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh.
Md Abunasar MiahDepartment of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh.
Muhammad TawhidDepartment of Cellular and Molecular Biology, Chattogram Veterinary and Animal Sciences University (CVASU), Hathazari, Chattogram 4330, Bangladesh.
Md Easin MiaDepartment of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh. Electronic address: easin.bge@nstu.edu.bd.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHuman metapneumovirus (HMPV) is a major cause of acute respiratory tract infections, particularly in young children, older adults, and immunocompromised individuals. Despite its significant clinical burden, no approved antiviral therapies or vaccines are currently available. This study aimed to identify potential RNA interference (RNAi)-based therapeutic candidates targeting the highly conserved fusion (F) gene of HMPV.

methodsAn in silico pipeline was employed to design and evaluate small interfering RNA (siRNA) candidates targeting the HMPV F gene. A total of 869 siRNA sequences were initially generated using siDirect 2.1 software, which were sequentially filtered to 34 and then to 10 candidates based on sequence characteristics and predicted silencing efficiency. Molecular docking was performed to assess interactions between selected siRNAs and the human Argonaute-2 (AGO2) protein, followed by 100-ns molecular dynamics simulations to evaluate structural stability. Principal component analysis and free-energy landscape analyses were also performed.

resultsThree siRNA candidates (F11, F19, and F26) demonstrated favorable RNAi characteristics, including high predicted silencing efficiency and strong target binding. Among them, F11 exhibited the highest sequence conservation across global HMPV strains, the highest melting temperature, favorable AGO2 interaction, and stable dynamic behavior. Principal component analysis indicated that F11 sampled the most constrained conformational subspace, which had a well-defined low-energy basin, thereby identifying it as the most promising candidate.

conclusionsThis study identified F11 as the most promising siRNA candidate targeting the highly conserved HMPV fusion (F) gene, demonstrating strong potential as an RNAi-based therapeutic agent according to computational analyses. However, further in vitro and in vivo validation is required to confirm its efficacy and safety.

Indexed as

Argonaute 2 (AGO2)Human metapneumovirus (HMPV)Molecular dynamics (MD) simulationRNA interference (RNAi)Small interfering RNA (siRNA)

Identifiers

PMID42749451
PMCPMC13453447

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