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Record W7132901038

The Discovery and Characterization of Chemical Degraders of the Histone Methyltransferase NSD2

2024· dissertation· W7132901038 on OpenAlexaff
David Yan Nie

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHistone methyltransferaseChromatinUbiquitin ligaseHistoneEpigeneticsMethyltransferaseHistone H2AHistone methylation
DOInot available

Abstract

fetched live from OpenAlex

Epigenetics describes changes in chromosome and gene expression without alterations in the DNA sequence. Nuclear receptor-binding SET domain-containing 2 (NSD2) is a histone methyltransferase responsible for the formation of dimethylated lysine 36 on histone 3 (H3K36me2) – an epigenetic mark that is associated with chromatin regions of active transcription. For that, NSD2 plays a significant role in gene regulation. NSD2 dysregulation, caused by either a gain-of-function mutation (resulting in NSD2 hyperactivity) or a translocation (resulting in NSD2 overexpression), is associated with oncogenesis in blood cancers. However, there are only limited available effective and selective modulators of NSD2 activity. This thesis describes the development of the first-in-class NSD2 selective chemical degrader, UNC8153, which can reduce the cellular levels of NSD2 and the associated H3K36me2 mark. UNC8153 targets the non-catalytic PWWP1 domain of NSD2 and contains a simple primary alkylamine moiety that recruits a previously unexploited E3 ubiquitin ligase to confer neddylation-, ubiquitination- and proteosome-dependent degradation of NSD2. The degradation of NSD2 by UNC8153 results in reduced pathological phenotypes in multiple myeloma cells with dysregulated NSD2. Subsequent optimization of UNC8153 to UNC8732 by modifying its linker achieved five-times greater potency. UNC8732 facilitates targeted degradation of NSD2 in acute lymphoblastic leukemia cells harboring the NSD2 gain-of-function mutation, resulting in growth suppression, apoptosis, and reversal of drug resistance. Through a BioID-based proteomics approach, I shed light on the previously unknown mechanism of action by discovering a targeted protein degradation strategy involving the recruitment of the SCFFBXO22 E3 ubiquitin ligase complex. The primary amine of UNC8732 was shown to be metabolized to an aldehyde species, which engages cysteine 326 of FBXO22 covalently and reversibly to recruit the SCFFBXO22 complex. I also demonstrate that a previously reported alkyl amine-containing chemical degrader targeting XIAP similarly depends on the SCFFBXO22 complex, suggesting the broader applicability of this TPD strategy. Overall, this thesis describes the first chemical probe for modulating NSD2 activity, meeting the stringent criteria for potency, selectivity, and in-cell activity, as well as one of the first recruiters of FBXO22 E3 ubiquitin ligase. This marks significant achievements in NSD2-targeting therapeutics and targeted protein degradation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: none
Teacher disagreement score0.000
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.009
GPT teacher head0.299
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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