Subtopic Deep Dive

Cereblon-Dependent Protein Degradation
Research Guide

What is Cereblon-Dependent Protein Degradation?

Cereblon-dependent protein degradation refers to the mechanism by which cereblon (CRBN), a substrate receptor of the CRL4 E3 ubiquitin ligase complex, recruits neosubstrates induced by small molecules like immunomodulatory drugs (IMiDs) for ubiquitination and proteasomal degradation.

This process underpins PROTAC (PROteolysis TArgeting Chimera) technologies and IMiDs such as lenalidomide, which bind CRBN to degrade specific proteins. Key studies demonstrate CRBN's role in targeted degradation for oncology applications, with over 10 papers from 2016-2022 cited here totaling more than 7,000 citations. Foundational pre-2015 papers are unavailable in this dataset.

Curated Papers

Key Challenges

Why It Matters

Cereblon-dependent degradation enables IMiDs like lenalidomide for multiple myeloma treatment and PROTACs for castration-resistant prostate cancer, as shown by Raina et al. (2016) degrading BET proteins. Békés et al. (2022) highlight its expansion to undruggable targets in oncology and beyond. Zhao et al. (2022) detail strategies for cancer therapy, driving clinical candidates from Crews lab innovations (Smith et al., 2019).

Key Research Challenges

Neosubstrate Specificity Control

Designing molecules that selectively recruit CRBN to desired neosubstrates without off-target degradation remains difficult. Smith et al. (2019) show E3 ligase orientation dictates specificity, complicating PROTAC design. Over 495 citations underscore this persistent issue.

E3 Ligase Recruitment Optimization

Achieving efficient CRBN ternary complex formation for degradation requires balancing linker length and affinity. Békés et al. (2022) review past challenges in PROTAC development, citing 2669 studies. Raina et al. (2016) faced potency hurdles in CRPC models.

Clinical Translation Barriers

Translating CRBN PROTACs to clinic involves pharmacokinetic and toxicity challenges. Zhao et al. (2022) and Li & Song (2020) note resistance mechanisms in cancer therapy. Sun et al. (2019) discuss industry hurdles, with 579 citations.

Essential Papers

PROTAC targeted protein degraders: the past is prologue

Miklós Békés, David R. Langley, Craig M. Crews · 2022 · Nature Reviews Drug Discovery · 2.7K citations

PROTAC-induced BET protein degradation as a therapy for castration-resistant prostate cancer

Kanak Raina, Jing Lü, Yimin Qian et al. · 2016 · Proceedings of the National Academy of Sciences · 797 citations

Significance We describe the development of a small molecule that mediates the degradation of bromodomain and extra-terminal (BET) proteins and its application in the treatment of castration-resist...

Targeted protein degradation: mechanisms, strategies and application

Lin Zhao, Jia Zhao, Kunhong Zhong et al. · 2022 · Signal Transduction and Targeted Therapy · 746 citations

Abstract Traditional drug discovery mainly focuses on direct regulation of protein activity. The development and application of protein activity modulators, particularly inhibitors, has been the ma...

Thirty Years of HDAC Inhibitors: 2020 Insight and Hindsight

Terence C. S. Ho, Alex H. Y. Chan, A. Ganesan · 2020 · Journal of Medicinal Chemistry · 696 citations

It is now 30 years since the first report of a potent zinc-dependent histone deacetylase (HDAC) inhibitor appeared. Since then, five HDAC inhibitors have received regulatory approval for cancer che...

Advances in covalent drug discovery

Lydia Boike, Nathaniel J. Henning, Daniel K. Nomura · 2022 · Nature Reviews Drug Discovery · 686 citations

PROTACs: great opportunities for academia and industry

Xiuyun Sun, Hongying Gao, Yiqing Yang et al. · 2019 · Signal Transduction and Targeted Therapy · 579 citations

Epigenetic modifications of histones in cancer

Zibo Zhao, Ali Shilatifard · 2019 · Genome biology · 561 citations

Abstract The epigenetic modifications of histones are versatile marks that are intimately connected to development and disease pathogenesis including human cancers. In this review, we will discuss ...

Reading Guide

Foundational Papers

No pre-2015 papers available; start with Raina et al. (2016, 797 citations) for first CRBN PROTAC in CRPC and Huang & Dixit (2016, 414 citations) for ubiquitin system entry.

Recent Advances

Prioritize Békés et al. (2022, 2669 citations) for PROTAC overview, Smith et al. (2019, 495 citations) for CRBN specificity, and Zhao et al. (2022, 746 citations) for strategies.

Core Methods

Core techniques: PROTAC synthesis for CRBN recruitment (Raina et al., 2016), ligase orientation analysis (Smith et al., 2019), ubiquitination assays, and neosubstrate proteomics (Zhao et al., 2022).

How PapersFlow Helps You Research Cereblon-Dependent Protein Degradation

Discover & Search

Research Agent uses searchPapers and citationGraph on 'Cereblon PROTAC degradation' to map 50+ papers from Békés et al. (2022, 2669 citations) to Raina et al. (2016), revealing CRBN neosubstrate networks; exaSearch uncovers hidden IMiD studies, while findSimilarPapers expands from Smith et al. (2019) to E3 orientation papers.

Analyze & Verify

Analysis Agent applies readPaperContent to extract CRBN binding motifs from Zhao et al. (2022), verifies degradation efficiencies via verifyResponse (CoVe) against Raina et al. (2016) claims, and runs PythonAnalysis for ubiquitination rate stats with GRADE scoring on PROTAC potency data.

Synthesize & Write

Synthesis Agent detects gaps in CRBN neosubstrate selectivity from Smith et al. (2019) vs. Békés et al. (2022); Writing Agent uses latexEditText, latexSyncCitations for IMiD mechanism reviews, latexCompile for manuscripts, and exportMermaid for ternary complex diagrams.

Use Cases

"Analyze degradation kinetics of BET PROTACs targeting CRBN in Raina et al. 2016"

Research Agent → searchPapers('CRBN BET PROTAC kinetics') → Analysis Agent → readPaperContent(Raina) → runPythonAnalysis(pandas curve fitting on dose-response data) → statistical output with GRADE-verified half-life metrics.

"Write a review section on CRBN E3 orientation effects with citations"

Synthesis Agent → gap detection(Smith 2019, Békés 2022) → Writing Agent → latexEditText('CRBN orientation mechanisms') → latexSyncCitations(10 papers) → latexCompile → LaTeX PDF with formatted CRBN PROTAC figure.

"Find GitHub code for CRBN PROTAC modeling simulations"

Research Agent → paperExtractUrls(Zhao 2022) → paperFindGithubRepo → githubRepoInspect → Code Discovery workflow outputs simulation scripts for neosubstrate docking from related Crews lab supplements.

Automated Workflows

Deep Research workflow conducts systematic review of 50+ CRBN papers: searchPapers → citationGraph(Békés hub) → DeepScan(7-step verify on Raina efficiencies). Theorizer generates hypotheses on IMiD resistance from Sun et al. (2019) + Li & Song (2020), chain-verified via CoVe. DeepScan analyzes PROTAC specificity with runPythonAnalysis checkpoints.

Try Doxa for Cereblon-Dependent Protein Degradation Research

Frequently Asked Questions

What defines cereblon-dependent protein degradation?

It is the CRBN-mediated recruitment of neosubstrates by IMiDs or PROTACs for ubiquitination via CRL4 ligase and proteasomal breakdown, as foundational in Raina et al. (2016).

What are key methods in this subtopic?

Methods include PROTAC design for CRBN ternary complexes (Smith et al., 2019), neosubstrate screening, and degradation assays in oncology models (Raina et al., 2016; Zhao et al., 2022).

What are the most cited papers?

Top papers are Békés et al. (2022, 2669 citations) on PROTAC history, Raina et al. (2016, 797 citations) on BET degradation, and Zhao et al. (2022, 746 citations) on mechanisms.

What open problems exist?

Challenges include off-target effects, E3 specificity (Smith et al., 2019), and clinical resistance (Li & Song, 2020), with gaps in non-oncology applications.