Hepatitis B virus S gene substitutions in Iraqi patients: computational analysis of missense substitutions and functional impact

Abstract

Background

The hepatitis B virus (HBV) continues to be a global health concern, with immune-escape substitutions increasingly reported in regions where genotype D predominates. In Iraq, where genotype D is the dominant strain, the functional impact of naturally occurring S gene substitutions remains poorly understood. This study examined S gene substitutions in 13 chronic hepatitis B patients from Anbar Province, Iraq, and used computational approaches to assess the functional consequences of missense substitutions in the large S protein.

Methods

A 1070 bp PCR fragment covering the S gene coding regions was amplified and sequenced. Missense substitutions were analyzed using five computational prediction tools (SIFT, PolyPhen-2, PROVEAN, PhD-SNP and P-Mut). Three-dimensional modelling, protein–protein docking analysis and epitope mapping were performed for the most consistently predicted potentially disruptive substitutions.

Results

A total of 34 nucleotide substitutions were identified, including 15 missense substitutions, indicating genetic diversity among Iraqi HBV isolates from Anbar Province. Three substitutions (p.159D>A, p.126R>T and p.160P>L) were consistently predicted as functionally impactful by multiple computational tools. Protein–protein docking simulation revealed significant reductions in antibody binding affinity for p.159D>A (45%) and p.126R>T (31%), suggesting potential immune escape mechanisms. Notably, p.126R>T occurs within the vaccine-targeted ‘a’ determinant region, while p.159D>A may contribute to immune escape through predicted conformational changes despite unchanged epitope scores.

Conclusions

This in silico analysis provides an initial functional evaluation of HBV S gene substitutions in Iraqi genotype D isolates and identifies substitutions with potential implications for vaccine efficacy and immune recognition. These findings highlight the value of computational screening in resource-limited settings and underscore the need for expanded molecular surveillance and experimental validation to assess clinical significance.