Evidence map›Paper›PMID 40355437›Full record

ArticleScientific reports2025

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Levin John, Leona Dcunha, Mukhtar Ahmed, Sonet Daniel Thomas, Rajesh Raju, Abhithaj Jayanandan

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

6 authors.

Levin JohnCentre for Integrative Omics Data Science, Yenepoya (Deemed to be University), Mangalore, 575018, Karnataka, India.ORCID http://orcid.org/0000-0003-2335-9238
Leona DcunhaCentre for Integrative Omics Data Science, Yenepoya (Deemed to be University), Mangalore, 575018, Karnataka, India.ORCID http://orcid.org/0009-0004-2245-9522
Mukhtar AhmedDepartment of Zoology, College of Science, King Saud University, Kingdom of Saudi Arabia, P. O. Box 2455, Riyadh, 11451, Saudi Arabia.ORCID http://orcid.org/0000-0001-7392-6312
Sonet Daniel ThomasCentre for Integrative Omics Data Science, Yenepoya (Deemed to be University), Mangalore, 575018, Karnataka, India.ORCID http://orcid.org/0000-0003-1672-302X
Rajesh RajuCentre for Integrative Omics Data Science, Yenepoya (Deemed to be University), Mangalore, 575018, Karnataka, India. rajeshraju@yenepoya.edu.in.ORCID http://orcid.org/0000-0003-2319-121X
Abhithaj JayanandanCentre for Integrative Omics Data Science, Yenepoya (Deemed to be University), Mangalore, 575018, Karnataka, India. abhithaj.j.ciods@yenepoya.edu.in.ORCID http://orcid.org/0000-0002-6732-4486

Funding

King Saud University RSPD2025R984
6 · The paper itself

Abstract

Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic diseases. Nipah virus (NiV) of Paramyxoviridae family and Henipavirus genus is transmitted by Pteropus bats. Climate-induced changes in bat migration patterns and food availability enhances the virus's adaptability, in turn increasing the potential for transmission and outbreak risk. NiV infection has high human fatality rate. With no antiviral drugs or vaccines available, exploring the complex machinery involved in viral RNA synthesis presents a promising target for therapy. Drug repurposing provides a fast-track approach by identifying existing drugs with potential to target NiV RNA-dependent RNA polymerase (L), bypassing the time-consuming process of developing novel compounds. To facilitate this, we developed an attention-based deep learning model that utilizes pharmacophore properties of the active sites and their binding efficacy with NiV L protein. Around 500 FDA-approved drugs were filtered and assessed for their ability to bind NiV L protein. Compared to the control Remdesivir, we identified Cangrelor, an antiplatelet drug for cardiovascular diseases, with stronger binding affinity to NiV L (glide score of -12.30 kcal/mol). Molecular dynamics simulations further revealed stable binding (RMSD of 3.54 Å) and a post-MD binding energy of -181.84 kcal/mol. The strong binding of Cangrelor is illustrated through trajectory analysis, principal component analysis, and solvent accessible surface area, further confirming the stable interaction with the active site of NiV RdRp. Cangrelor can interact with NiV L protein and may potentially interfere with its replication. These findings suggest that Cangrelor will be a potential drug candidate that can effectively interact with the NiV L protein and potentially disrupt the viral replication. Further in vivo studies are warranted to explore its potential as a repurposable antiviral drug.

Indexed as

Adenosine MonophosphateAntiviral AgentsDeep LearningDrug RepositioningNipah VirusAlanineAnimalsHenipavirus InfectionsHumansModels, MolecularMolecular Docking SimulationMolecular Dynamics SimulationRNA-Dependent RNA PolymeraseAdenosine MonophosphateAlanineAntiviral AgentscangrelorremdesivirRNA-Dependent RNA PolymeraseAttention based deep learningCangrelorDrug-repurposingNipah virus

Identifiers

PMID40355437
PMCPMC12069662

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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.