Abstract 7: Discovery of OICR-10268: A potent and selective BCL6 inhibitor
Bibliographic record
Abstract
Abstract The transcription factor B cell lymphoma 6 (BCL6) is required for the generation of an effective humoral immune response through the development and maintenance of germinal centers (GCs). The inhibition of the protein−protein interaction between BCL6 and its corepressors has been implicated as a therapeutic target for diffuse large B-cell lymphoma (DLBCL), a type of non-Hodgkin’s lymphoma (NHL). Using structure-based drug design, we initiated a program to identify novel BCL6 inhibitors. We identified a high micromolar virtual screening hit which was then optimized for potent biophysical binding and anti-proliferative cellular activity resulting in the identification of OICR-10268, a potent and selective Bcl6 inhibitor. Citation Format: Iain D. Watson, Methvin Isaac, Brian Wilson, Anh Chau, Justin Morin, Pandiaraju Subramanian, Ahmed Mamai, Babu Joseph, Michael Prakesch, David Uehling, Ayome Abibi, Richard Marcellus, Craig Strathdee, Ratheesh Subramaniam, Brigitte Theriault, Jeffrey Winston, Manuel Chan, Carly Griffin, Herman Cheung, Taira Kiyota, Elijus Undzys, Ahmed Aman, Gennady Poda, Doug Kuntz, Neil C. Pomroy, Gil G. Privé, Rima Al-awar. Discovery of OICR-10268: A potent and selective BCL6 inhibitor [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 7.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".