AUTHOR=Shao Nihui , Guo Yunfei 
  
TITLE=Protein embeddings reveal a continuous molecular landscape of host adaptation in waterfowl parvoviruses
  
JOURNAL=Frontiers in Bioinformatics
  
VOLUME=Volume 5 - 2025
  
YEAR=2026
  
URL=https://www.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2025.1738737
  
DOI=10.3389/fbinf.2025.1738737
  
ISSN=2673-7647
  
ABSTRACT=Viral adaptation across closely related hosts often proceeds through subtle molecular changes that escape detection by classical phylogenetic analyses. In waterfowl parvoviruses, we integrate AI-based protein language modeling, structural biophysics, and infection assays to reveal a continuous trajectory of host adaptation linking Goose parvovirus (GPV) and Muscovy duck parvovirus (MDPV). Protein embeddings of VP1 sequences reveal a smooth manifold bridging GPV and MDPV, which softens an apparent phylogenetic dichotomy into a graded molecular topology. Structural modeling identifies a flexible surface loop (residues 300–420) as a biophysical pivot. Along the embedding trajectory, this loop undergoes gradual conformational expansion and electrostatic neutralization, quantitatively linking embedding coordinates to capsid surface remodeling. Experimentally, a GPV-type isolate recovered from naturally diseased ducks replicated efficiently in duck embryos, duck embryo fibroblasts, and live ducklings, producing characteristic lesions. These results show that waterfowl parvoviruses evolve along a continuous molecular–electrostatic landscape in which cumulative structural adjustments enable cross-host infectivity. Our framework connects AI-derived molecular representations to biophysical mechanisms and biological function, supporting a model of viral host adaptation as a predominantly continuous process and providing a foundation for predicting cross-host potential in emerging viral systems.