ArticleACS physical chemistry Au2025
Insights into Antiviral Candidates against Oropouche Virus: A Molecular Dynamics Study.
Article in ACS physical chemistry Au, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
Who cites it
2 citing papers in PubMed.
- Review
- Oropouche virus: transmission, epidemiology, genetic diversity, and public health implications.EClinicalMedicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Oropouche virus (OROV), an emerging arbovirus from the Peribunyaviridae family, represents a growing public health concern in Latin America, particularly due to its rapid urban spread and lack of specific treatments. In this study, we employed an integrated computational strategy combining molecular docking and molecular dynamics (MD) simulations to evaluate the potential of HIV protease inhibitors as candidates for repurposing against the Gc glycoprotein of OROV, a critical component in viral fusion and host cell entry. While docking initially ranked Saquinavir as the top binder, subsequent MD simulations revealed that nelfinavir and indinavir exhibited superior performance across multiple criteria, including binding energy, structural stability, center-of-mass distance maintenance, and consistent hydrogen bonding. These findings emphasize the limitations of docking-only approaches and highlight the importance of dynamic and energetic analyses for accurate inhibitor selection. The proposed computational pipeline demonstrates its value in identifying stable, high-affinity ligands and offers a promising route for accelerating drug discovery against neglected viral diseases such as OROV.
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Registered trials
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