MétaCan
Menu
Back to cohort
Record W4391442510 · doi:10.1002/advs.202307526

Development of Complementary Photo‐arginine/lysine to Promote Discovery of Arg/Lys hPTMs Interactomes

2024· article· en· W4391442510 on OpenAlexaff
Yu Zong, Nicole Weiss, Ke Wang, Alexandra E. Pagano, Søren Heissel, Sumera Perveen, Jian Huang

Bibliographic record

VenueAdvanced Science · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsStructural Genomics ConsortiumUniversity of Toronto
FundersNational Cancer Institute
KeywordsLysineArginineChemistryBiochemistryComputational biologyAmino acidBiology

Abstract

fetched live from OpenAlex

Arginine and lysine, frequently appearing as a pair on histones, have been proven to carry diverse modifications and execute various epigenetic regulatory functions. However, the most context-specific and transient effectors of these marks, while significant, have evaded study as detection methods have thus far not reached a standard to capture these ephemeral events. Herein, a pair of complementary photo-arginine/δ-photo-lysine (R-dz/K-dz) probes is developed and involve these into histone peptide, nucleosome, and chromatin substrates to capture and explore the interactomes of Arg and Lys hPTMs. By means of these developed tools, this study identifies that H3R2me2a can recruit MutS protein homolog 6 (MSH6), otherwise repelDouble PHD fingers 2 (DPF2), Retinoblastoma binding protein 4/7 (RBBP4/7). And it is disclosed that H3R2me2a inhibits the chromatin remodeling activity of the cBAF complex by blocking the interaction between DPF2 (one component of cBAF) and the nucleosome. In addition, the novel pairs of H4K5 PTMs and respective readers are highlighted, namely H4K5me-Lethal(3)malignant brain tumor-like protein 2 (L3MBTL2), H4K5me2-L3MBTL2, and H4K5acK8ac-YEATS domain-containing protein 4 (YEATS4). These powerful tools pave the way for future investigation of related epigenetic mechanisms including but not limited to hPTMs.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.303
Teacher spread0.293 · 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
GenreEmpirical

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

Citations9
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueAdvanced ScienceSame topicCancer-related gene regulationFrench-language works237,207