HHV-6A

HHV-6A U70

Predicted structure model: ColabFold (3x recycles).

The model was generated using ColabFold with 3 recycles.

Predicted Structure (ColabFold (3x recycles))
Predicted Aligned Error (PAE) Click image to open full size
Predicted Aligned Error (PAE)
Structural Homologs
Virus Protein Uniprot pTM
HSV-1 UL12 P04294 0.72
HSV-2 UL12 P89435 0.73
VZV ORF48 P09253 0.81
MDV MDV024 Q9E6Q5 n/a
PrV UL12 G3G984 n/a
HCMV UL98 F5HF49 0.84
RCMV E98a K7YNQ4 n/a
HHV-6A U70 P24447 0.91
HHV-6B U70 P52448 0.91
HHV-7 U70 Q77Y54 0.92
EBV BGLF5 P03217 0.89
KSHV ORF37 Q2HR95 0.90
MHV68 ORF37 O41954 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