MHV68

MHV68 ORF64

Predicted structure model: AlphaFold 2.

The model was generated using AlphaFold 2.

Predicted Structure (AlphaFold 2)
Predicted Aligned Error (PAE) Click image to open full size
Predicted Aligned Error (PAE)
Structural Homologs
Virus Protein Uniprot pTM
HSV-1 UL36 P10220 0.43
HSV-2 UL36 P89459 0.43
VZV ORF22 P09278 0.42
MDV MDV049 Q9E6N3 n/a
PrV UL36 G3G960 n/a
HCMV UL48 Q6SW84 0.33
RCMV e48.2 K7YNK6 n/a
HHV-6A U31 P52340 0.31
HHV-6B U31 Q9QJ37 0.40
HHV-7 U31 O56278 0.30
EBV BPLF1 P03186 0.28
KSHV ORF64 Q2HR64 0.38
MHV68 ORF64 O41965 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