VZV

VZV ORF49

Predicted structure model: AlphaFold 2.

Warning: Models failed the quality scores.

The model was generated using AlphaFold 2.

Predicted Structure (AlphaFold 2)
Structural Homologs
Virus Protein Uniprot pTM
HSV-1 UL11 P04289 0.27
HSV-2 UL11 P13294 0.26
VZV ORF49 P09297 0.27
MDV MDV023 Q77MS5 n/a
PrV UL11 G3G985 n/a
HCMV UL99 F5HI87 0.17
RCMV E99 K7XWE0 n/a
HHV-6A U71 P24448 0.25
HHV-6B U71 P52459 0.25
HHV-7 U71 Q77Y53 0.25
EBV BBLF1 P0CK51 0.24
KSHV ORF38 F5HHY1 0.22
MHV68 ORF38 O41955 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