HSV-2

HSV-2 UL44

Predicted structure model: ColabFold (3x recycles).

The model was generated using ColabFold with 3 recycles.

Using DeepTMHMM, this protein was identified to contain a signal peptide and a transmembrane domain.

The transmembrane domain spans residues: 448-468

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 UL44 P10228 0.61
HSV-2 UL44 Q89730 0.62
VZV ORF14 P09256 0.49
MDV MDV057 n/a n/a
PrV UL44 G3G968 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