Evidence map›Paper›PMID 40635997›Full record

ArticleFrontiers in bioinformatics2025

Ayesha Sajjad, Ihteshamul Haq, Rabia Syed, Faheem Anwar, Muhammad Hamza, Muhammad Musharaf, Tehmina Kiani, Faisal Nouroz

Abstract read
In one paragraph

Article in Frontiers in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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

8 authors.

Ayesha SajjadDepartment of Bioinformatics, Govt. Postgraduate College Mandian Abbottabad, Abbotabad, Khyber Pakhtunkhwa, Pakistan.
Ihteshamul HaqCollege of Life Sciences and Technology, Beijing University of Chemical Technology, Beijing, China.
Rabia SyedDepartment of Bioinformatics, Govt. Postgraduate College Mandian Abbottabad, Abbotabad, Khyber Pakhtunkhwa, Pakistan.
Faheem AnwarAcademy of medical engineering and translational medicine Tianjin University China, Tianjin, China.
Muhammad HamzaDepartment of Bioinformatics, Govt. Postgraduate College Mandian Abbottabad, Abbotabad, Khyber Pakhtunkhwa, Pakistan.
Muhammad MusharafDepartment of Bioinformatics, Govt. Postgraduate College Mandian Abbottabad, Abbotabad, Khyber Pakhtunkhwa, Pakistan.
Tehmina KianiDepartment of Bioinformatics, Govt. Postgraduate College Mandian Abbottabad, Abbotabad, Khyber Pakhtunkhwa, Pakistan.
Faisal NourozDepartment of Bioinformatics, Hazara University Mansehra, Dhodial, Khyber Pakhtunkhwa, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The Nipah virus (NiV), a zoonotic paramyxovirus closely related to the Hendra virus, poses a significant global health threat due to its high mortality rate, zoonotic nature, and recurring outbreaks primarily in Malaysia, Bangladesh, and India. Infection with NiV leads to severe encephalitis and carries a case fatality rate ranging from 40% to 75%. The lack of a vaccine and limited understanding of NiV pathogenesis underscore the urgent need for effective therapeutics. This study focuses on identifying viral peptides of the Nipah virus using the peptide mass fingerprinting technique. This approach identified antiviral peptides acting as potent inhibitors, targeting the viral G-protein's interaction with cellular ephrin-B2 and B3 receptors. These receptors are crucial for viral entry into host cells and subsequent pathogenesis. Methods: Identifying NiV viral peptides not only enhances our understanding of the virus's structural and functional properties but also opens avenues for developing novel therapeutic strategies. By blocking the interaction between the viral G-protein and host receptors, these antiviral peptides offer promising prospects for drug development against NiV. Results and Discussion: Twenty-one peptides were identified using peptide mass fingerprinting. These peptides were then subjected to docking analysis with two antiviral peptides of the ephrin B2 receptor and a monoclonal antibody, demonstrating robust stability and binding affinity. These predicted peptides contribute to the broader field of virology by elucidating key aspects of NiV biology and paving the way for the development of targeted antiviral therapies. Future studies may further explore the therapeutic potential of these peptides and their application in combating other viral infections.

Indexed as

ephrin B2 and B3 receptornipah virus (NiV)paramyxoviruspeptide mass fingerprintingviral g protein

Identifiers

PMID40635997
PMCPMC12238059

What Socratic holds

Textmetadata
LicenceCC BY
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.