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Systematic profiling of conditional degron tag technologies for target validation studies
Daniel P Bondeson1, Zachary Mullin-Bernstein1, Sydney Oliver1
1The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Nature Communications
|September 20, 2022
Summary
Conditional degron tags (CDTs) enable rapid protein manipulation for target validation. A new system efficiently identifies the best CDT fusion for specific protein targets, streamlining research.
Area of Science:
- Molecular Biology
- Biochemistry
- Drug Discovery
Background:
- Conditional degron tags (CDTs) offer tunable protein degradation.
- Designing effective CDT fusion proteins typically involves lengthy, iterative optimization.
Purpose of the Study:
- To develop a system for rapid comparison of five distinct CDTs.
- To identify optimal CDT fusions for 16 diverse protein targets.
Main Methods:
- Established a system to test five CDTs: AID/AID2, IKZF3d, dTAG, HaloTag, and SMASh.
- Evaluated CDT performance across 16 different protein targets.
Main Results:
- Protein expression and degradation varied significantly based on CDT, construct, and target.
- No single CDT was universally effective across all targets.
- An optimal CDT fusion was identified for each tested protein target.
Conclusions:
- A systematic approach rapidly identifies effective CDT fusions for target validation.
- The developed system and reagents are available as a community resource to advance CDT adoption.
