Back

A basic leucine zipper uses a dimer pathway to locate its targets in DNA mixtures

Kuravsky, M.; Grey, G.; Kelly, C. F.; Sarkar, P. D.; Gaudez, J.; Shammas, S. L.

2025-08-28 biophysics
10.1101/2025.08.25.672131 bioRxiv
Show abstract

The operation of Eukaryotic transcription factors remains enigmatic. Cyclic AMP-responsive element-binding protein (CREB) is a member of the basic zipper family, a superfamily of transcription factors which operate exclusively in eukaryotes and bind DNA targets as homodimers or heterodimers. Modulation of oligomerization provides an additional opportunity for transcriptional control by this (and similar) families over monomeric transcription factors. However, when dimerization occurs - before or after target binding - is not known. We performed a suite of in vitro stopped-flow kinetic measurements, including CREB basic zippers target search amongst excess non-target DNA. The extensive dataset enabled a kinetic and thermodynamic understanding of DNA binding that demonstrated most productive search is performed by dimeric, rather than monomeric, CREB. Equilibrium is approached very rapidly under physiologically relevant concentrations, where relative flux through the monomer pathway is only around 1 in every 10,000 complexes formed. This preference of mechanism is driven by CREB monomer having a substantially higher affinity for another CREB monomer than for its DNA target. Equilibrium experiments with eight other monomeric peptides further suggest this as a common feature amongst the bZIP proteins, with only one peptide (Jun) displaying similar affinities for both. The work has implications for understanding the nature of DNA target search, as well as designing efficient artificial transcription factors and transcriptional inhibitors.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.