T-cell acute lymphocytic leukemia (T-ALL) protein 1 (TAL1) is an important transcription factor in the specification of myeloid cells and positively regulates the differentiation of red blood cells. Aberrant, high-level expression of TAL1, mediated by insertions of short DNA sequences that recruit the transcription factor MYB and establish the formation of super-enhancers, causes T-ALL. Synthetic zinc finger (ZF) DNA-binding proteins targeting the MYB binding site (ZF-Myb) in Jurkat cells, a T-ALL cell line harboring the TAL1-associated mutation, bind the DNA with high affinity and efficiently outcompete MYB. Expression of ZF-Myb reduced expression of TAL1 and cell proliferation in Jurkat cells. Inclusion of a Krüppel-associated Box (KRAB) increased the ZF-Myb DNA-binding affinity four-fold and conferred more efficient reduction of TAL1 expression and Jurkat cell growth. Direct KRAB-ZF-Myb protein delivery was strongly enhanced by novel peptides (CATCH: Co-Assembling Tags based on CHarge complementarity) that form protein granules. Transcriptomic analysis revealed that downregulation of TAL1 using the synthetic KRAB-ZF-Myb protein disrupts the TAL1-MYB oncogenic axis and induces expression of pro-apoptotic genes. In summary, using a novel and highly efficient direct protein delivery system, synthetic ZF proteins targeting a single site in a super-enhancer disrupt oncogenic pathways in T-ALL.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
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It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.