B-box1 Domain of MID1 Interacts with the Ube2D1 E2 Enzyme Differently Than RING E3 Ligases.
Anupreet KaurErin M GladuKatharine M WrightJessica A WebbMichael A MassiahPublished in: Biochemistry (2023)
The MID1 TRIM protein is important for ventral midline development in vertebrates, and mutations of its B-box1 domain result in several birth defects. The B-box1 domain of the human MID1 protein binds two zinc atoms and adopt a similar ββα-RING structure. This domain is required for the efficient ubiquitination of protein phosphatase 2A, alpha4, and fused kinase. Considering the structural similarity, the MID1 B-box1 domain exhibits mono-autoubiquitination activity, in contrast to poly-autoubiquitination observed for RING E3 ligases. To understand its mechanism of action, the interaction of the B-box1 domain with Ube2D1 (UbcH5a, E2), a preferred E2 ligase, is investigated. Using isothermal titration calorimetry, the MID1 RING and B-box1 domains were observed to have similar binding affinities with the Ube2D1 protein. However, NMR 15 N- 1 H Heteronuclear Single Quantum Coherence titration, 15 N relaxation data, and H igh A mbiguity D riven protein-protein DOCK ing (HADDOCK) calculations show the B-box1 domain binding on a surface distinct from where RING domains bind. The novel binding interaction shows the B-box1 domain partially overlapping the noncovalent Ube2D1 and a ubiquitin binding site that is necessary for poly-autoubiquitination activity. The B-box1 domain also displaces the ubiquitin from the Ube2D1 protein. These studies reveal a novel binding interaction between the zinc-binding ββα-fold B-box1 domain and the Ube2D enzyme family and that this difference in binding, compared to RING E3 ligases, provides a rationale for its auto-monoubiquitination E3 ligase activity.
Keyphrases
- binding protein
- transcription factor
- protein protein
- small molecule
- dna binding
- clinical trial
- magnetic resonance
- endothelial cells
- molecular dynamics
- magnetic resonance imaging
- gene expression
- high resolution
- computed tomography
- mass spectrometry
- atomic force microscopy
- contrast enhanced
- artificial intelligence
- deep brain stimulation
- deep learning