MHV68

MHV68 ORF24

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
HCMV UL87 Q6SW55 0.41
RCMV E87 K7XR28 n/a
HHV-6A U58 P24437 0.45
HHV-6B U58 Q9QJ25 0.51
HHV-7 U58 O56290 0.46
EBV BcRF1-UL87 P25215 0.46
KSHV ORF24 F5HFD2 0.37
MHV68 ORF24 O41942 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