MétaCan
Menu
Back to cohort
Record W3213089913 · doi:10.3389/fncel.2021.768655

Exploration of Aberrant E3 Ligases Implicated in Alzheimer’s Disease and Development of Chemical Tools to Modulate Their Function

2021· review· en· W3213089913 on OpenAlexfundno aff
Frances Potjewyd, Alison D. Axtman

Bibliographic record

VenueFrontiers in Cellular Neuroscience · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsnot available
FundersEshelman Institute for Innovation, University of North Carolina at Chapel HillGenentechNational Institutes of HealthInnovative Medicines InitiativeMinistero dello Sviluppo EconomicoGenome CanadaFundação de Amparo à Pesquisa do Estado de São PauloEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaANovartis PharmaCanada Foundation for InnovationOntario Ministry of Economic Development and InnovationPfizer
KeywordsUbiquitin ligaseUbiquitinDownregulation and upregulationProteasomeCell biologyBiologyUbiquitin-Protein LigasesProtein degradationComputational biologyBiochemistryGene

Abstract

fetched live from OpenAlex

The Ubiquitin Proteasome System (UPS) is responsible for the degradation of misfolded or aggregated proteins via a multistep ATP-dependent proteolytic mechanism. This process involves a cascade of ubiquitin (Ub) transfer steps from E1 to E2 to E3 ligase. The E3 ligase transfers Ub to a targeted protein that is brought to the proteasome for degradation. The inability of the UPS to remove misfolded or aggregated proteins due to UPS dysfunction is commonly observed in neurodegenerative diseases, such as Alzheimer’s disease (AD). UPS dysfunction in AD drives disease pathology and is associated with the common hallmarks such as amyloid-β (Aβ) accumulation and tau hyperphosphorylation, among others. E3 ligases are key members of the UPS machinery and dysfunction or changes in their expression can propagate other aberrant processes that accelerate AD pathology. The upregulation or downregulation of expression or activity of E3 ligases responsible for these processes results in changes in protein levels of E3 ligase substrates, many of which represent key proteins that propagate AD. A powerful way to better characterize UPS dysfunction in AD and the role of individual E3 ligases is via the use of high-quality chemical tools that bind and modulate specific E3 ligases. Furthermore, through combining gene editing with recent advances in 3D cell culture, in vitro modeling of AD in a dish has become more relevant and possible. These cell-based models of AD allow for study of specific pathways and mechanisms as well as characterization of the role E3 ligases play in driving AD. In this review, we outline the key mechanisms of UPS dysregulation linked to E3 ligases in AD and highlight the currently available chemical modulators. We present several key approaches for E3 ligase ligand discovery being employed with respect to distinct classes of E3 ligases. Where possible, specific examples of the use of cultured neurons to delineate E3 ligase biology have been captured. Finally, utilizing the available ligands for E3 ligases in the design of proteolysis targeting chimeras (PROTACs) to degrade aberrant proteins is a novel strategy for AD, and we explore the prospects of PROTACs as AD therapeutics.

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.

How this classification was reachedexpand

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)0.000
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.554
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.091
GPT teacher head0.293
Teacher spread0.202 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations40
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Cellular NeuroscienceSame topicUbiquitin and proteasome pathwaysFrench-language works237,207