In silico profiling of the plasmodium knowlesi 32 kDa antigen: Diversity, epitope prediction, and structural modeling

The emergence of Plasmodium knowlesi malaria in Southeast Asia, particularly Malaysia, necessitates effective interventions. However, high polymorphism often limits the utility of key merozoite surface proteins (MSPs) as viable vaccine candidates. Pk32, a predicted glycosylphosphatidylinositol (GPI)-anchored protein in P. knowlesi, shares homology with the relatively conserved Plasmodium vivax Pv32, suggesting it may be a promising vaccine candidate. We analyzed the genetic diversity, polymorphism, and signatures of natural selection and 3-D structure using 39 full-length Pk32 sequences, primarily from Malaysian Borneo. Sequence analysis showed low nucleotide diversity (π = 0.0061) and limited polymorphism. Phylogenetic analysis indicated no geographical clustering. Natural selection tests; codon-based Z-test, tajima's D, codon-based site-by-site analysis (FEL, MEME, FUBAR, SLAC) provided strong evidence of purifying selection acting on Pk32, suggesting functional constraint alongside population expansion. In silico B-cell epitope prediction identified three common epitomes. Crucially, two epitopes (145PKERES150 and 167DIGKKQNS174) were conserved in all sequences. Mapping these conserved epitopes onto the predicted and refined 3D structure of Pk32 highlights specific stable targets. The observed combination of limited genetic variation and the presence of stable, conserved B-cell epitopes strongly suggests that Pk32 is a compelling candidate for inclusion in a blood-stage vaccine against P. knowlesi.

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Publication Details

Journal
Infection Genetics and Evolution
Published
2025-12-31
DOI
https://doi.org/10.1016/j.meegid.2025.105871
Primary Topic
vaccines and immunoinformatics approaches
Type
article
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article

In silico profiling of the plasmodium knowlesi 32 kDa antigen: Diversity, epitope prediction, and structural modeling

Jin-Hee Han, Ahmed Saif, Pratisthita Baruah, Md Atique Ahmed et al.
Infection Genetics and Evolution
vaccines and immunoinformatics approaches
article

In silico profiling of the plasmodium knowlesi 32 kDa antigen: Diversity, epitope prediction, and structural modeling

Jin-Hee Han, Ahmed Saif, Pratisthita Baruah, Md Atique Ahmed, Rudraangsh Acharyya, Jawahir Marzouq Alghamdi, Yee Ling Lau
article en

Abstract

The emergence of Plasmodium knowlesi malaria in Southeast Asia, particularly Malaysia, necessitates effective interventions. However, high polymorphism often limits the utility of key merozoite surface proteins (MSPs) as viable vaccine candidates. Pk32, a predicted glycosylphosphatidylinositol (GPI)-anchored protein in P. knowlesi, shares homology with the relatively conserved Plasmodium vivax Pv32, suggesting it may be a promising vaccine candidate. We analyzed the genetic diversity, polymorphism, and signatures of natural selection and 3-D structure using 39 full-length Pk32 sequences, primarily from Malaysian Borneo. Sequence analysis showed low nucleotide diversity (π = 0.0061) and limited polymorphism. Phylogenetic analysis indicated no geographical clustering. Natural selection tests; codon-based Z-test, tajima's D, codon-based site-by-site analysis (FEL, MEME, FUBAR, SLAC) provided strong evidence of purifying selection acting on Pk32, suggesting functional constraint alongside population expansion. In silico B-cell epitope prediction identified three common epitomes. Crucially, two epitopes (145PKERES150 and 167DIGKKQNS174) were conserved in all sequences. Mapping these conserved epitopes onto the predicted and refined 3D structure of Pk32 highlights specific stable targets. The observed combination of limited genetic variation and the presence of stable, conserved B-cell epitopes strongly suggests that Pk32 is a compelling candidate for inclusion in a blood-stage vaccine against P. knowlesi.

Infection Genetics and EvolutionVol. 138
Kangwon National University (KR), King Saud University (SA), Regional Medical Research Centre (IN), University of Malaya (MY), King Khalid University (SA)
Good health and well-being
Openalex Percentile: Top 35%
vaccines and immunoinformatics approaches
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