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Abstract B224: Structure-based drug design of signal transducers and activator of transcription 5 inhibitors.

2011· article· en· W2073326558 on OpenAlexaff
Abbarna A. Cumaraswamy, Patrick T. Gunning

Bibliographic record

VenueMolecular Cancer Therapeutics · 2011
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsAmgen (Canada)University of Toronto
Fundersnot available
KeywordsSTAT5STAT proteinBiologySH2 domainSTAT3Cancer researchTranscription factorChemistryCell biologySignal transductionTyrosine kinaseBiochemistryGene

Abstract

fetched live from OpenAlex

Abstract Signal Transducer and Activator of Transcription 5 (Stat5) protein has gained notoriety for its aberrant role in many human cancers including breast, liver, prostate, skin, head and neck. Despite the significant evidence showing Stat5's role in cancers, there has been little progress in developing small molecule inhibitors of Stat5 function. In contrast, there has been significant advancements in identifying inhibitors for the Stat3 protein. As a result, several potent and direct small molecule and oligonucleotide-based inhibitors have entered pre-clinical trials as a Stat3 therapeutic. Unfortunately, there has not been progress towards the development of potent Stat5 inhibitors. Stat5 is activated by ligand-receptor binding, which recruits Stat5 to intracellular receptor sites via their SH2 domain. Stat5 is then phosphorylated at conserved tyrosine (Y) residues Y694 and 699, which facilitates the formation of active Stat5 dimers via reciprocal pY-SH2 domain interactions. The dimers then translocate to the nucleus and induce target gene transcription. In cancer cells, Stat5 is constitutively phosphorylated leading to the aberrant expression of anti-apoptotic Stat5 target genes. In an effort to identify direct inhibitors of Stat5, we conducted an in vitro screen of a focused library of SH2 domain binding salicylic acid-containing inhibitors (∼150) against Stat5. Several potent (Ki < 5 μM) and Stat5 selective (>3-fold specificity for Stat5 cf. Stat1 and Stat3) inhibitors were identified which were then evaluated in K562 and MV-4–11 human leukemia cells which are known to harbour constitutively activated Stat5. BP-1–108 was identified as the most potent lead within these cell lines. The lead was further evaluated to show potent induction of apoptosis (IC50's ∼ 20 μM) which correlated with potent and selective suppression of Stat5 phosphorylation. In addition, it inhibited Stat5 target genes; Cyclin D1 & c-myc. BP-1–108 also showed no cytotoxicity against healthy bone marrow cells at concentrations up to 160 μM. These inhibitors represent the most potent and direct inhibitors of Stat5 function reported to date. An in silico docking analysis with BP-1–108 within the Stat5b crystal structure (pdb:1Y1U) revealed a tertrapodal projection of functionality facilitating access to a number of sub pockets within the Stat5 SH2 domain. Currently we are conducting a structure-activity relationship against Stat5's SH2 domain with one projection into the hydrophobic pocket using diverse heterocycles to delineate inhibitor binding to improve the potency of our inhibitors. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr B224.

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 score0.022
Threshold uncertainty score0.545

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 head0.049
GPT teacher head0.277
Teacher spread0.228 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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