The Viral AlphaFold Database of monomers and homodimers reveals conserved protein folds in viruses of bacteria, archaea, and eukaryotes
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Abstract
Viruses are the most abundant and genetically diverse entities on Earth, yet the functions and evolution of most viral proteins remain poorly understood. Their rapid evolution often obscures evolutionary relationships, limiting the ability to assign functions using sequence-based methods. Although the conservation of protein fold can reveal deep homologies, viral proteins remain underrepresented in structural databases. We address this by clustering viral sequences from RefSeq and predicting the structures of ~27,000 representative proteins using AlphaFold2 to create the Viral AlphaFold Database (VAD). We uncover conserved folds in diverse viruses infecting bacteria, archaea, and eukaryotes. We predict homodimers and make comparisons to the Protein Data Bank, providing data on oligomerization potential. We reveal considerable functional darkness in the viral protein universe and report the discovery and validation of an uncharacterized toxin-antitoxin system. The VAD provides a foundation for exploring viral structure-function relationships, including ancient folds shaping viral interactions across all life.
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data-sharing.atkinson-lab.com/vad/.
I really appreciate that you have made the structures available and also appreciate the detailed metadata in the supp table (associated host, 'brightness' etc.). It would be great if you could set up a web portal to host all of this to make it easier for others to view and reuse your dataset (download structures per host or per cluster, etc.)
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Recent viral structure databases, such as the BFVD [18] and ViralZone [10] projects, have addressed this gap to a large extent. However, these resources rely on less accurate methods than the reference AlphaFold2 implementation and are limited to monomeric structural predictions.
https://www.biorxiv.org/content/10.1101/2024.12.19.629443v1.full
It might be nice to also compare your study to the Viro3D work, which combines AlphaFold2-ColabFold and ESMFold to predict structures from animal-infecting viruses
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