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A Method for Conditional Regulation of Protein Stability in Native or Near-Native Form.

ABSTRACT: Here, we report a method to regulate cellular protein levels by introducing a ubiquitin variant between a destabilizing domain (DD) and the regulated protein. When produced in the absence of a stabilizing ligand the DD dominates and the entire fusion protein is processively degraded by the proteasome. In the presence of the stabilizing ligand the fusion protein is metabolically stable and becomes a substrate for abundant ubiquitin-specific proteases, liberating a native, or a near-native protein-of-interest. This technique is thus particularly useful for the study of proteins whose free N terminus is required for proper function. In addition, removal of the DD in the presence of stabilizing ligand leads to higher expression levels of regulated protein when cells experience transient exposure to a stabilizing ligand, such as in a living animal receiving a single dose of a pharmacological agent as the stabilizing ligand.

SUBMITTER: Miyamae Y

PROVIDER: S-EPMC7749034 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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A Method for Conditional Regulation of Protein Stability in Native or Near-Native Form.

Miyamae Yusaku Y Chen Ling-Chun LC Utsugi Yuki Y Farrants Helen H Wandless Thomas J TJ

Cell chemical biology 20201001 12

Here, we report a method to regulate cellular protein levels by introducing a ubiquitin variant between a destabilizing domain (DD) and the regulated protein. When produced in the absence of a stabilizing ligand the DD dominates and the entire fusion protein is processively degraded by the proteasome. In the presence of the stabilizing ligand the fusion protein is metabolically stable and becomes a substrate for abundant ubiquitin-specific proteases, liberating a native, or a near-native protein ...[more]

PMID: 33007216

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Project description:Unlike the core structural elements of a protein like regular secondary structure, template based modeling (TBM) has difficulty with loop regions due to their variability in sequence and structure as well as the sparse sampling from a limited number of homologous templates. We present a novel, knowledge-based method for loop sampling that leverages homologous torsion angle information to estimate a continuous joint backbone dihedral angle density at each loop position. The φ,ψ distributions are estimated via a Dirichlet process mixture of hidden Markov models (DPM-HMM). Models are quickly generated based on samples from these distributions and were enriched using an end-to-end distance filter. The performance of the DPM-HMM method was evaluated against a diverse test set in a leave-one-out approach. Candidates as low as 0.45 Å RMSD and with a worst case of 3.66 Å were produced. For the canonical loops like the immunoglobulin complementarity-determining regions (mean RMSD <2.0 Å), the DPM-HMM method performs as well or better than the best templates, demonstrating that our automated method recaptures these canonical loops without inclusion of any IgG specific terms or manual intervention. In cases with poor or few good templates (mean RMSD >7.0 Å), this sampling method produces a population of loop structures to around 3.66 Å for loops up to 17 residues. In a direct test of sampling to the Loopy algorithm, our method demonstrates the ability to sample nearer native structures for both the canonical CDRH1 and non-canonical CDRH3 loops. Lastly, in the realistic test conditions of the CASP9 experiment, successful application of DPM-HMM for 90 loops from 45 TBM targets shows the general applicability of our sampling method in loop modeling problem. These results demonstrate that our DPM-HMM produces an advantage by consistently sampling near native loop structure. The software used in this analysis is available for download at http://www.stat.tamu.edu/~dahl/software/cortorgles/.

Dataset Information

A Method for Conditional Regulation of Protein Stability in Native or Near-Native Form.

Publications

A Method for Conditional Regulation of Protein Stability in Native or Near-Native Form.

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