<![CDATA[Background Indonesia’s ethnic heterogeneity contributes to substantial human genetic diversity, including variation in genes associated with malaria susceptibility and severity. Single Nucleotide Polymorphisms (SNPs) in host genes encoding immune receptors and adhesion molecules may influence malaria pathogenesis by modulating inflammatory signaling and parasite–host cell interactions. Aims: This study aimed to evaluate the potential structural and functional impact of selected malaria-associated SNPs in human genes using a systematic in silico approach. Methods: A literature-guided and database-driven screening (dbSNP and UniProt) was used to identify relevant SNPs previously reported to be associated with malaria infection and/or the severity of infection. Inclusion criteria were: (1) localization within coding regions, (2) prior evidence of clinical relevance, (3) resulting in a nonsynonymous amino acid substitution, and (4) annotated with a reference SNP ID (rsID). Selected SNPs were subjected to protein structural modelling. Native and mutant protein structures were compared using PyMOL, conformational changes and differences were quantified using Root Mean Square Deviation (RMSD). Results: A total of 38 SNPs in TLR4, ICAM1, and IL-22 gene with reported clinical relevance to infection were identified, of which 6 SNPs (TLR4: n=2; ICAM1: n=3; IL-22: n=1) met all inclusion criteria for malaria-associated variants. Five selected SNPs were located in coding regions and resulted in amino acid substitutions, several of which involved changes in residue polarity, whereas one SNPs was located in non-coding region. Structural comparison showed detectable but minimal conformational differences between the native and mutant proteins, with low RMSD values (maximum 0.014 Å in TLR4 variant rs4986790). Conclusion:This in silico analysis suggests that the selected malaria-associated SNPs in TLR4, ICAM-1, and IL-22 genes are unlikely to induce major structural rearrangements but may contribute to localized changes that affect protein interaction interfaces or signaling functions. Their potential contribution to malaria severity may therefore involve minor structural deviation rather than large conformational changes. This study provides a systematic computational framework for prioritizing host genetic variants for further functional validation, particularly in genetically diverse populations such as Indonesia. ]]>
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