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Record W3161615669 · doi:10.1038/s41467-021-23152-6

Discovery of first-in-class inhibitors of ASH1L histone methyltransferase with anti-leukemic activity

2021· article· en· W3161615669 on OpenAlexfundno aff
David Rogawski, Jing Deng, Hao Li, Hongzhi Miao, Dmitry Borkin, Trupta Purohit, Jiho Song, Jennifer Chase, Shuangjiang Li, Juliano Ndoj, Szymon Kłossowski, Eungi Kim, Fengbiao Mao, Bo Zhou, James Ropa, Marta Z. Krotoska, Zhuang Jin, Patricia Ernst, Xiaomin Feng, Gang Huang, Kenichi Nishioka, Samantha Kelly, Miao He, Bo Wen, Duxin Sun, Andrew G. Muntean, Yali Dou, Ivan Maillard, Tomasz Cierpicki, Jolanta Grembecka

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsnot available
FundersCenter for Scientific ReviewDivision of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institute of General Medical SciencesNational Institute on AgingMichigan Technology Tri-CorridorNational Cancer InstituteUniversity of TorontoNational Institutes of HealthU.S. Department of Health and Human ServicesMichigan Economic Development CorporationNational Institute of Diabetes and Digestive and Kidney DiseasesOffice of ScienceUniversity of MichiganLeukemia and Lymphoma SocietyNational Heart, Lung, and Blood InstituteArgonne National LaboratoryU.S. Department of Energy
KeywordsDruggabilityChemistryHistone methyltransferaseSmall moleculeDrug discoveryLeukemiaCell biologyComputational biologyCancer researchBiologyBiochemistryEpigeneticsGeneGenetics

Abstract

fetched live from OpenAlex

ASH1L histone methyltransferase plays a crucial role in the pathogenesis of different diseases, including acute leukemia. While ASH1L represents an attractive drug target, developing ASH1L inhibitors is challenging, as the catalytic SET domain adapts an inactive conformation with autoinhibitory loop blocking the access to the active site. Here, by applying fragment-based screening followed by medicinal chemistry and a structure-based design, we developed first-in-class small molecule inhibitors of the ASH1L SET domain. The crystal structures of ASH1L-inhibitor complexes reveal compound binding to the autoinhibitory loop region in the SET domain. When tested in MLL leukemia models, our lead compound, AS-99, blocks cell proliferation, induces apoptosis and differentiation, downregulates MLL fusion target genes, and reduces the leukemia burden in vivo. This work validates the ASH1L SET domain as a druggable target and provides a chemical probe to further study the biological functions of ASH1L as well as to develop therapeutic agents.

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 score0.011
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.277
Teacher spread0.267 · 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

Citations43
Published2021
Admission routes1
Has abstractyes

Explore more

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