EBV

EBV BFRF3

Predicted structure model: AlphaFold 2.

The model was generated using AlphaFold 2.

Predicted Structure (AlphaFold 2)
Structural Homologs
Virus Protein Uniprot pTM
HSV-1 UL35 P10219 0.56
HSV-2 UL35 P89458 0.44
VZV ORF23 P09279 0.33
MDV MDV048 Q9E6N4 n/a
PrV UL35 Q77KA6 n/a
HCMV UL48A F5HEN7 0.67
HHV-6A U32 Q69560 0.56
HHV-6B U32 Q9WT32 0.55
HHV-7 U32 Q77Y76 0.59
EBV BFRF3 P14348 0.33
KSHV ORF65 Q2HR63 0.36
MHV68 ORF65 O41966 n/a

This page uses Mol* for molecular visualization, with JSmol as a fallback when WebGL is unavailable.

Predictions were run with Colabfold by the Steinegger lab:
Mirdita M, Schutze K, Moriwaki Y, Heo L, Ovchinnikov S, Steinegger M. "ColabFold: Making protein folding accessible to all". Nature Methods (2022) doi: 10.1038/s41592-022-01488-1

Foldseek is developed by the Steinegger lab:
van Kempen M, Kim S, Tumescheit C, Mirdita M, Soding J, and Steinegger M. "Fast and accurate protein structure search with Foldseek". Nature Biotechnology (2023) doi: 10.1038/s41587-023-01773-0

Alphafold2 was developed by Deepmind:
Jumper et al. "Highly accurate protein structure prediction with AlphaFold." Nature (2021) doi: 10.1038/s41586-021-03819-2

Signal peptide predictions were performed with DeepTMHMM
Jeppe Hallgren, Konstantinos D. Tsirigos, Mads Damgaard Pedersen, Jose Juan Almagro Armenteros, Paolo Marcatili, Henrik Nielsen, Anders Krogh, Ole Winther. "DeepTMHMM predicts alpha and beta transmembrane proteins using deep neural networks." bioRxiv (2022) doi: 10.1101/2022.04.08.487609

AlphaFold3 models were generated through the Alphafold Server, which uses Google DeepMind's AlphaFold technology
Abramson J, et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature (2024). doi: 10.1038/s41586-024-07487-w