Optimizing computational prediction of shrimp-WSSV protein interactions through integration of homology- and...

Understanding and predicting protein-protein interactions (PPIs) between Penaeus vannamei and white spot syndrome virus (WSSV) is essential for elucidating viral infection mechanisms and developing antiviral strategies in shrimp aquaculture. Traditional experimental methods and classical homology-based computational approaches such as STRING have been used to identify shrimp-WSSV PPIs, but both face inherent limitations in accuracy and scalability. Recently, the breakthrough of AlphaFold3 has enabled PPI prediction from the perspective of complex structures, although its performance requires systematic evaluation. To address these gaps, this study establishes an integrated computational framework that combines homology-based network inference and structure-based (topology-based) complex modeling for predicting shrimp-WSSV PPIs. Homology-based interaction networks and 3D structural models of putative PPIs between three WSSV proteins and host proteins were constructed, including 2580 PPIs of wsv067, 389 PPIs of wsv172, and 2310 PPIs of wsv188. Notably, we found substantial discrepancies between STRING- and AlphaFold3-derived predictions, indicating that reliance on a single method may yield an numerous false positives. Nevertheless, interactions with high STRING scores showed a greater likelihood of forming structurally stable complexes in AlphaFold3. By applying dual thresholds (STRING score > 700 and composite AlphaFold3 score > 0.7) and validating representative complexes using molecular dynamics simulations, we identified a small but reliable set of high-confidence PPIs. These host proteins were primarily enriched in DNA replication, highlighting potential targets that may facilitate WSSV replication after invasion. Together, this work establishes a practical framework for prioritizing virus-host PPIs and reveals mechanistically plausible interactions between WSSV and shrimp, offering promising perspectives for antiviral target discovery and health management in aquaculture.