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Record W2987423170 · doi:10.7554/elife.11306.017

Author response: ABHD17 proteins are novel protein depalmitoylases that regulate N-Ras palmitate turnover and subcellular localization

2015· peer-review· en· W2987423170 on OpenAlexaff
David Lin, Elizabeth Conibear

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPalmitoylationBiologyCell biologyCytosolBiochemistryAnkyrin repeatSerineSubcellular localizationEnzymeCysteineGene

Abstract

fetched live from OpenAlex

Proteins play important roles in many processes in cells. Some of these proteins can be modified by the addition of a molecule called palmitate. This process, termed “palmitoylation”, helps direct these proteins to the compartments within the cell where they are needed to carry out their roles. One target of palmitoylation is N-Ras, which is a protein that can promote the development of cancer. We understand quite a lot about how palmitate is added to proteins, but much less about how it is removed. So far, researchers have only identified two enzymes – known as APT1 and APT2 – that can remove palmitate from proteins, but it is possible that there are others. Identifying other “depalmitoylase” enzymes could help us find ways to block the removal of palmitate from N-Ras, which could lead to new treatments for some cancers. Lin and Conibear used several biochemical techniques to search for depalmitoylase enzymes in human cells. The experiments reveal that although APT1 and APT2 are important for removing palmitate from some proteins, they are not needed to remove palmitate from N-Ras. Instead, Lin and Conibear found that an enzyme called ABHD17 removes palmitate from N-Ras. The next step following on from this work will be to find out what other proteins ABHD17 acts on in cells. A longer-term challenge will be to develop specific chemicals that inhibit ABHD17 activity and test if they are able to reduce the growth of cancer cells.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.082
GPT teacher head0.330
Teacher spread0.247 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2015
Admission routes1
Has abstractyes

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