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1.
bioRxiv ; 2024 Jun 12.
Article in English | MEDLINE | ID: mdl-38915612

ABSTRACT

Chronic hepatitis B virus (HBV) infection is an incurable global health threat responsible for causing liver disease and hepatocellular carcinoma. During the genesis of infection, HBV establishes an independent minichromosome consisting of the viral covalently closed circular DNA (cccDNA) genome and host histones. The viral X gene must be expressed immediately upon infection to induce degradation of the host silencing factor, Smc5/6. However, the relationship between cccDNA chromatinization and X gene transcription remains poorly understood. Establishing a reconstituted viral minichromosome platform, we found that nucleosome occupancy in cccDNA drives X transcription. We corroborated these findings in cells and further showed that the chromatin destabilizing molecule CBL137 inhibits X transcription and HBV infection in hepatocytes. Our results shed light on a long-standing paradox and represent a potential new therapeutic avenue for the treatment of chronic HBV infection.

2.
Proc Natl Acad Sci U S A ; 120(1): e2213703120, 2023 01 03.
Article in English | MEDLINE | ID: mdl-36574706

ABSTRACT

The Ufd1/Npl4/Cdc48 complex is a universal protein segregase that plays key roles in eukaryotic cellular processes. Its functions orchestrating the clearance or removal of polyubiquitylated targets are established; however, prior studies suggest that the complex also targets substrates modified by the ubiquitin-like protein SUMO. Here, we show that interactions between Ufd1 and SUMO enhance unfolding of substrates modified by SUMO-polyubiquitin hybrid chains by the budding yeast Ufd1/Npl4/Cdc48 complex compared to substrates modified by polyubiquitin chains, a difference that is accentuated when the complex has a choice between these substrates. Incubating Ufd1/Npl4/Cdc48 with a substrate modified by a SUMO-polyubiquitin hybrid chain produced a series of single-particle cryo-EM structures that reveal features of interactions between Ufd1/Npl4/Cdc48 and ubiquitin prior to and during unfolding of ubiquitin. These results are consistent with cellular functions for SUMO and ubiquitin modifications and support a physical model wherein Ufd1/Npl4/Cdc48, SUMO, and ubiquitin conjugation pathways converge to promote clearance of proteins modified with SUMO and polyubiquitin.


Subject(s)
Polyubiquitin , Saccharomyces cerevisiae Proteins , Polyubiquitin/metabolism , Saccharomyces cerevisiae Proteins/metabolism , Valosin Containing Protein/genetics , Valosin Containing Protein/metabolism , Ubiquitin/metabolism , Endoplasmic Reticulum/metabolism , Cell Cycle Proteins/genetics , Cell Cycle Proteins/metabolism
3.
Proc Natl Acad Sci U S A ; 118(10)2021 03 09.
Article in English | MEDLINE | ID: mdl-33674381

ABSTRACT

Kinases play important roles in diverse cellular processes, including signaling, differentiation, proliferation, and metabolism. They are frequently mutated in cancer and are the targets of a large number of specific inhibitors. Surveys of cancer genome atlases reveal that kinase domains, which consist of 300 amino acids, can harbor numerous (150 to 200) single-point mutations across different patients in the same disease. This preponderance of mutations-some activating, some silent-in a known target protein make clinical decisions for enrolling patients in drug trials challenging since the relevance of the target and its drug sensitivity often depend on the mutational status in a given patient. We show through computational studies using molecular dynamics (MD) as well as enhanced sampling simulations that the experimentally determined activation status of a mutated kinase can be predicted effectively by identifying a hydrogen bonding fingerprint in the activation loop and the αC-helix regions, despite the fact that mutations in cancer patients occur throughout the kinase domain. In our study, we find that the predictive power of MD is superior to a purely data-driven machine learning model involving biochemical features that we implemented, even though MD utilized far fewer features (in fact, just one) in an unsupervised setting. Moreover, the MD results provide key insights into convergent mechanisms of activation, primarily involving differential stabilization of a hydrogen bond network that engages residues of the activation loop and αC-helix in the active-like conformation (in >70% of the mutations studied, regardless of the location of the mutation).


Subject(s)
Anaplastic Lymphoma Kinase/chemistry , Machine Learning , Molecular Dynamics Simulation , Mutation , Anaplastic Lymphoma Kinase/deficiency , Enzyme Activation/genetics , Humans , Protein Conformation, alpha-Helical
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