UC San Diego
Computational tools based on energy landscape theory to predict structurally diverse ensembles of transcription factors
- Author(s): Lätzer, Joachim
- et al.
The NF-KB/IKB system provides a challenge to the structure -function paradigm since both binding partners are partially disordered in the monomeric form. The experimental study of this system gives rise to many interesting questions. Can one describe the kinetics of coupled folding and binding? Can one faithfully invert the available low resolution data for partially folded ensembles to provide a picture of the underlying molecular details? What happens upon phosphorylation? In this thesis I show how tools to adequately answer these questions can be obtained using energy landscape theory . These tools are validated on test systems of transcription factors where experimental data are available. I demonstrate that replica simulation algorithms based on a strict Bayesian interpretation of the data can successfully invert low resolution data into the correct partially folded ensembles. In order to study the kinetics of the NF-KB/IKB system I also show that simulations with an energy function that yields a funneled but rugged energy landscape can predict the observed binding mode of the crystal structure as well as an alternative binding mode. A method for computing the frustration of partially structured ensembles is also presented. Finally I present an energy function that can predict phosphorylation induced conformational changes for the NtrC transcription factor