Computational Modeling of Novel Anti-HpaA Protein Antibodies Targeting Helicobacter pylori in Gastric Cancer

Helicobacter pylori adhesin A (HpaA) is a surface-associated protein critical for the adhesion of H. pylori to gastric epithelial cells, which is strongly associated with an increased risk of gastric cancer. Recent elucidation of the 3D structure of HpaA offers novel opportunities for targeted therapeutic strategies to inhibit bacterial adhesion. This study aims to computationally characterize the interactions between HpaA and antibodies to identify potential candidates for therapeutic intervention against H. pylori infection. I hypothesize that high-affinity binding of specific antibodies to the specific binding site of the HpaA protein can effectively block bacterial adherence to gastric epithelial cells, thereby mitigating H. pylori-induced pathogenesis. AlphaFold 3 obtained the HpaA three-dimensional structure, providing a foundation for in-silico docking studies. Molecular docking simulations using HDOCK predicted antibody binding interactions and were validated using ScanNet, a deep learning-based method. Binding energy was calculated using the PRODIGY software, and hydrogen bond analysis was performed. Antibody 1IL1 demonstrated the strongest binding affinity to the HpaA protein. Additionally, to understand the binding interactions between the HpaA and annexin proteins, I performed AlphaFold 3 simulations, which showed that the apical region of the HpaA was involved in the annexin interaction. The results were consistent with lab experimental findings, and to the best of my knowledge, this is the first computational study on HpaA-mediated prevention of H. pylori interaction with the gut lining. These discoveries will contribute to our knowledge of HpaA-antibody interactions and offer a foundation for creating targeted antibody-based treatments for illnesses caused by H. pylori.