Abstract 6408: E3<i>scan</i>™ ligand binding assay platform for targeted protein degradation and PROTAC discovery
Bibliographic record
Abstract
Abstract E3 ligases have emerged as pivotal targets for a next generation protein degradation-based drug discovery paradigm. This new paradigm includes both ligand binding-directed “reprogramming” of E3 substrate specificity approaches and a more directed approach, using small molecule proteolysis-targeting chimeras (PROTACs), to selectively degrade disease-driving proteins. As there are hundreds of diverse putative E3 ligases with differentiated tissue expression, this new paradigm may well define a next dimension of precision medicine defined by an axis of tissue-specific activity. While there have been some early successes, the E3 drug discovery field has a significant unmet need for a standardized biochemical ligand binding assay platform. A platform is required that: 1) Can measure ligand binding across the E3 family using a standardized method enabling “apples to apples” comparisons; 2), Is highly scalable and rapid; 3) Has an exquisite dynamic range for the measurement of accurate KD values as low as digit picomolar (pM). Eurofins DiscoverX herein presents its novel E3scan™ technology that addresses each of these unmet needs. E3scan, based upon well-established KINOMEscan® technology, has been successfully applied to diverse E3 ligases, including CRBN, VHL, MDM2, MDMX, cIAP1, cIAP2, and XIAP, with many other E3 assays in progress. We shall present assay validation data for these targets, including data for ligands with KD values in the low to mid pM range. In conclusion, we present Eurofins DiscoverX's novel E3scan platform that shall enable accelerated screening and SAR analysis in the E3 drug discovery field, with rapid turnaround times for discovery library screens (20 business day TAT) and weekly SAR (5 business day TAT) and the largest assay panel available on a single technology platform. Citation Format: Ksenya Cohen Katsenelson, Luis Gonzalez, Gabriel Pallares, Alastair J. King, Daniel K. Treiber. E3scan™ ligand binding assay platform for targeted protein degradation and PROTAC discovery [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6408.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.012 |
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".