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Record W4396578192 · doi:10.1016/j.xcrp.2024.101960

Thalidomide derivatives degrade BCL-2 by reprogramming the binding surface of CRBN

2024· article· en· W4396578192 on OpenAlexaff
Jianhui Wang, Marcel Heinz, Kang Han, Varun Jayeshkumar Shah, Sebastian Hasselbeck, Martin P. Schwalm, Rajeshwari Rathore, Gerhard Hummer, Jun Zhou, Ivan Đikić, Xinlai Cheng

Bibliographic record

VenueCell Reports Physical Science · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsStructural Genomics Consortium
FundersHessisches Ministerium für Wissenschaft und KunstHunan Provincial Science and Technology DepartmentHunan UniversityBundesministerium für Bildung und ForschungMax-Planck-GesellschaftDeutsche ForschungsgemeinschaftNational Natural Science Foundation of ChinaVerband der Chemischen IndustrieCalifornia Department of Fish and Game
KeywordsThalidomideReprogrammingChemistryStereochemistryPharmacologyBiologyBiochemistryMedicineInternal medicineCell

Abstract

fetched live from OpenAlex

Recent studies demonstrate that modified thalidomide chemically alters the binding surface of its binding E3 ligase, CRBN, leading to the degradation of new substrate proteins. In this study, we conduct a proteome-wide analysis of thalidomide-like compounds and pinpoint three derivatives (C5, C6, and C7) that specifically target and degrade the BCL-2 protein. Using AlphaFold-driven molecular modeling combined with experimental data, we suggest that GLY128, ALA131, and THR132 are crucial in forming a CRBN-C5-BCL-2 ternary complex. This interaction is notably distinct from that of venetoclax, a known clinical BCL-2 inhibitor that interacts with the BH3 domain. Significantly, these thalidomide derivatives have the ability to degrade BCL-2 mutations that are resistant to venetoclax, thereby enhancing survival rates in a Notch-depleted Drosophila intestinal tumor model. Our findings highlight the critical role of targeted modifications to the E3 ligase surface in altering its binding affinity and achieving a new substrate protein profile.

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 score0.001
Threshold uncertainty score0.002

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)0.0010.000

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 head0.008
GPT teacher head0.265
Teacher spread0.257 · 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

Citations12
Published2024
Admission routes1
Has abstractyes

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