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Record W4362459844 · doi:10.1101/pdb.over107784

Generation and Characterization of Engineered Ubiquitin Variants to Modulate the Ubiquitin Signaling Cascade

2023· article· en· W4362459844 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCold Spring Harbor Protocols · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsCanadian Institute for Advanced ResearchUniversity of Guelph
Fundersnot available
KeywordsUbiquitinComputational biologyProteasomeDeubiquitinating enzymeBiologySignal transductionCell biologyDrug developmentGeneticsDrugGene

Abstract

fetched live from OpenAlex

The ubiquitin signaling cascade plays a crucial role in human cells. Consistent with this, malfunction of ubiquitination and deubiquitination is implicated in the initiation and progression of numerous human diseases, including cancer. Therefore, the development of potent and specific modulators of ubiquitin signal transduction has been at the forefront of drug development. In the past decade, a structure-based combinatorial protein-engineering approach has been used to generate ubiquitin variants (UbVs) as protein-based modulators of multiple components in the ubiquitin-proteasome system. Here, we review the design and generation of phage-displayed UbV libraries, including the processes of binder selection and library improvement. We also provide a comprehensive overview of the general in vitro and cellular methodologies involved in characterizing UbV binders. Finally, we describe two recent applications of UbVs for developing molecules with therapeutic potential.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.272
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it