Evidence map›Paper›PMID 42168870›Full record

ArticleBMC microbiology2026

Computational immunoinformatics and molecular modeling approaches for designing a multi-epitope vaccine against Babesia microti.

Muharib Alruwaili, Intisar Alruwaili, Yasir Alruwaili, Hasan Ejaz, Bi Bi Zainab Mazhari, Muhammad Tahir Ul Qamar, Muhammad Umer Khan

Abstract read
In one paragraph

Article in BMC microbiology, 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

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.

2 · The registry

The trial behind it

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Muharib AlruwailiDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Al-Jouf region, Sakaka, 72388, Saudi Arabia. mfalrwaili@ju.edu.sa.
Intisar AlruwailiDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Al-Jouf region, Sakaka, 72388, Saudi Arabia.
Yasir AlruwailiDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Al-Jouf region, Sakaka, 72388, Saudi Arabia.
Hasan EjazDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Al-Jouf region, Sakaka, 72388, Saudi Arabia.
Bi Bi Zainab MazhariDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Jouf University, Qurayyat, 75911, Saudi Arabia.
Muhammad Tahir Ul QamarDepartment of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan.
Muhammad Umer KhanInstitute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, Pakistan. muhammad.umer4@mlt.uol.edu.pk.

Funding

Al Jouf University (DGSSR-2025-01-01555).
6 · The paper itself

Abstract

Babesia microti is an emerging tick-transmitted agent causing babesiosis in humans, becoming a major concern to public health due to the lack of a vaccine. In silico methods such as reverse vaccinology and immunoinformatics offer a convenient tool for identifying promising vaccine targets. Using computational immunoinformatics and molecular modelling tools, the current study aims to develop a multi-epitope vaccination against B. microti. For identifying the antigenic proteins, subtractive proteomics, NCBI, and PPGA were used, whereas for their screening, ProtParam (ExPASy), VaxiJen 2.0, AllerTOP v2.0, and BLASTp were utilized. For B-cell epitope prediction, IEDB (BepiPred 2.0) was used, and for T-cell epitope prediction, NetMHCpan 4.1 was used, along with other characteristics such as antigenicity, allergenicity, toxicity, and solubility, which were predicted later. A multi-epitope vaccine construct was designed using the selected epitopes linked together with the help of EAAAK and GPGPG linkers, with β-defensin as an adjuvant. For structural modeling and refinement, Scratch Protein Predictor and GalaxyRefine were used, followed by validation using PROCHECK. Further, molecular docking was done using ClusPro, while molecular dynamics simulations were done using AMBER 22. In addition, immune simulation and cloning were conducted. From a total of 3601 proteins, four non-homologous and non-allergenic proteins were selected for use in the design process, from which a total of seven epitopes were selected (MHC class I - 4; MHC class II - 3). Structural analysis of the designed vaccine revealed good stability, which further increased when the vaccine was modified using disulfide bonds. Population coverage revealed that the vaccine had good global coverage (99.74%). Docking revealed good binding of the designed vaccine with the toll-like receptors TLR-2 and TLR-4. Analysis of molecular dynamics and binding energies of TLR-2 (-135.11 kcal/mol), and TLR-4 (-157.27 kcal/mol) receptors further supported the stability of complexes. In summary, the in silico and biophysical studies show that the designed multi-epitope vaccine for B. microti may have desirable stability, immunogenicity, and positive interaction with TLR-2 and TLR-4 receptors. Nevertheless, experimental validation is needed to establish its safety and effectiveness.

Indexed as

Babesia microtiProtozoan VaccinesAnimalsAntigens, ProtozoanComputational BiologyEpitopes, B-LymphocyteEpitopes, T-LymphocyteHumansImmunoinformaticsModels, MolecularMolecular Docking SimulationMolecular Dynamics SimulationProtein Subunit VaccinesReverse VaccinologyAntigens, ProtozoanEpitopes, B-LymphocyteEpitopes, T-LymphocyteProtein Subunit VaccinesProtozoan VaccinesBabesia microtiBabesiosisComputational base vaccine designingDocking and Molecular dynamics simulation

Identifiers

PMID42168870
PMCPMC13374273

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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.