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Record W2566638276 · doi:10.1158/1538-7445.am2015-3653

Abstract 3653: Structure-based study to overcome cross-reactivity of novel androgen receptor inhibitors

2015· article· en· W2566638276 on OpenAlexaff
Huifang Li, Nada Lallous, Kush Dalal, Eric Leblanc, Fuqiang Ban, Fabrice Ciesielski, Paul S. Rennie, Artem Cherkasov

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAndrogen receptorChemistryLigand (biochemistry)MorpholineReactivity (psychology)ReceptorPartial agonistProstate cancerAntiandrogensStereochemistryBiochemistryInternal medicineAgonistCancerMedicine

Abstract

fetched live from OpenAlex

Abstract The mutation-driven transformation of clinically used anti-androgens into agonists of human androgen receptor (AR) represents a major challenge in the current treatment of prostate cancer (PCa). To address this problem, we have developed a novel class of AR inhibitors targeting the DNA-binding domain (DBD) of the receptor, which is distanced from the mutations-prone androgen binding site (ABS) in the ligand-binding domain (LBD) of the AR, targeted by all conventional antiandrogens. While many members of the developed phenyl-thiazol-2-yl-morpholine series demonstrated potent sub-micromolar inhibition of the wild-type AR, some compounds also exhibited an undesired partial agonistic effect toward the T877A mutated form of the receptor, implying their cross-interaction with the AR ABS. To study the molecular basis of the cross-reactivity, we have solved the T877A mutated form of the AR LBD in complex with one developed compound exhibiting such unwanted partial agonism. Based on the resolved crystal structure, we have identified critical protein-ligand interactions and conformational changes in wild-type and T877A forms of AR that drive observed agonistic effects. The identified structural basis has further been used to modify the scaffold of developed AR DBD binders to eliminate their cross-reactivity toward T877A mutated AR LBD. In particular, the replacement of the phenyl ring with less hydrophobic heterocycles resulted in a series of inhibitors that did not demonstrate affinity toward ABS or exhibit an undesired agonistic effect on AR. This study provides insights into the development of AR inhibitors with high specificity, which may help overcome the mutation-driven resistance of anti-AR drugs in the treatment of PCa. Citation Format: Huifang Li, Nada Lallous, Kush Dalal, Eric Leblanc, Fuqiang Ban, Fabrice Ciesielski, Paul S. Rennie, Artem Cherkasov. Structure-based study to overcome cross-reactivity of novel androgen receptor inhibitors. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3653. doi:10.1158/1538-7445.AM2015-3653

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.216
GPT teacher head0.513
Teacher spread0.297 · 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
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
Published2015
Admission routes1
Has abstractyes

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