Evidence map›Paper›PMID 40390487›Full record

ArticleJournal, genetic engineering & biotechnology2025

Comparative proteomics and structure-based approach to unravel the therapeutic drug target of Theileria species.

Anusha Majumder, Jyotisha, Fouzia Nasim, Insaf Ahmed Qureshi

Abstract read
In one paragraph

Article in Journal, genetic engineering & biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Anusha MajumderDepartment of Biotechnology & Bioinformatics, School of Life Sciences, University of Hyderabad, Prof. C.R. Rao Road, Hyderabad 500046, India.
JyotishaDepartment of Biotechnology & Bioinformatics, School of Life Sciences, University of Hyderabad, Prof. C.R. Rao Road, Hyderabad 500046, India.
Fouzia NasimDepartment of Biotechnology & Bioinformatics, School of Life Sciences, University of Hyderabad, Prof. C.R. Rao Road, Hyderabad 500046, India.
Insaf Ahmed QureshiDepartment of Biotechnology & Bioinformatics, School of Life Sciences, University of Hyderabad, Prof. C.R. Rao Road, Hyderabad 500046, India. Electronic address: insaf@uohyd.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Theileriosis, caused by protozoan parasites of genus Theileria, primarily affects both domestic and wild ruminants. It can lead to significant economic losses in livestock farming due to decreased productivity and high mortality rates in susceptible animals, while treatment measures are not cost-effective. Since most of mechanisms of this disease remain unknown, this study investigates the differences in the mode of pathogenesis between transforming and non-transforming groups through an in silico comparative proteomics approach to recognize the key players involved in host cell transformation. Although the major biological processes and molecular functions are almost conserved between the two groups, PEST-motif containing secretory proteins of SfiI, SVSP, and Tash-AT gene families were identified as important candidates with the potential to transform infected host cells. Several members of PEST-motif containing proteins possess signal peptides, nuclear localization signals, and trans-membrane helices, further supporting their potential to transform host cells. Additionally, structural analysis helped in the identification of a parasitic protein (SfiIp) from SfiI family as a plausible drug target. Virtual screening revealed FDA-approved drugs (i.e. atogepant and rimegepant) as promising compounds, showing the highest affinity for SfiIp during molecular docking. Further studies, including molecular dynamics simulation, principal component analysis, and free energy landscape, suggested that these drug molecules exhibit the stable interaction with protein. Therefore, our research could facilitate the identification and targeting of novel drug candidates that may be further implemented to recognize effective therapeutics against Theileria infections.

Indexed as

Comparative proteomicsMolecular dynamics simulationsSfiIpTheileriaTransforming species

Identifiers

PMID40390487
PMCPMC12008689

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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.