RCMV

RCMV E86

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 UL19 P06491 0.76
HSV-2 UL19 P89442 0.80
VZV ORF40 P09245 0.79
MDV MDV031 Q9E6P8 n/a
PrV UL19 G3G8T2 n/a
HCMV UL86 F5HGT1 0.77
RCMV E86 K7XY07 n/a
HHV-6A U57 P17887 0.76
HHV-6B U57 Q9QJ26 0.77
HHV-7 U57 Q77Y62 0.77
EBV BcLF1 P03226 0.79
KSHV ORF25 Q2HRA7 0.79
MHV68 ORF25 O41943 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