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Review
. 2021 Apr 21:19:2097-2105.
doi: 10.1016/j.csbj.2021.04.020. eCollection 2021.

How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations

Affiliations
Review

How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations

Fanny Kozak et al. Comput Struct Biotechnol J. .

Abstract

We review recent advances in modeling structural ensembles of transcription factors from nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopic data, integrated with molecular dynamics (MD) simulations. We focus on approaches that confirm computed conformational ensembles by sparse constraints obtained from magnetic resonance. This combination enables the deduction of functional and structural protein models even if nuclear Overhauser effects (NOEs) are too scarce for conventional structure determination. We highlight recent insights into the folding-upon-DNA binding transitions of intrinsically disordered transcription factors that could be assessed using such integrative approaches.

Keywords: EPR; MD simulations; NMR; Structural dynamics; Transcription factors.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

None
Graphical abstract
Fig. 1
Fig. 1
Comparison of experimental and computed PRE effects for the MAX transcription factor. a) Conformations sampled in MD simulations of the MAX:MAX homodimer. The DNA-binding domain (bottom) is intrinsically disordered in the absence of a ligand and samples a heterogeneous conformational space that includes hinged and extended conformations. If a spin-label is attached to the DNA-binding site (e.g. at the site of the yellow dot) NMR signals of amino acids in its vicinity are suppressed by PREs (effect range indicated by the grey shade). Thus, the hinged conformation would lead to the suppression of signals assigned to the remote HLH domain, while the extended conformations would not. The structure of the attached SL is indicated in the dashed box. b) Experimentally observed PRE effects as a function of residue position in MAX:MAX (top) compared to PRE effects extracted from MD simulations (bottom). The match between both data sets is good, such that the conformational ensemble sampled in the MD simulations could be verified by the experimental observations (adapted from reference with permission of the publisher.) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 2
Fig. 2
The conformational tuning of the MAX:MAX dimer in the DNA bound state. MD simulations could confirm NMR and EPR data that suggested strong backbone as well as side-chain motions of the DNA-binding site even in the DNA-bound state where the binding sites fold into a stable helical form. The simulations showed how the bound helices open and close continuously around the DNA-strand. (adapted from reference with permission of the publisher.)
Fig. 3
Fig. 3
DNA binding of the Drosophila melanogaster transcription factor Brinker (BrkDBD) as an example for induced fit upon binding of TFs to their target DNA. The intrinsically disordered TF recruits the DNA and only folds into a helical state after the encounter complex has been formed. The protein binding region is marked in cyan. The black values indicate the timing required (and confidence bounds) for the various steps. (Adapted from reference with permission of the publisher.) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 4
Fig. 4
Analysis of DNA conformation by EPR and MD. a) Snapshot of the simulated DNA molecule in a water box used to predict the experimental distance distributions. b) The experimental distance distribution P(r) (black) obtained by DEER-EPR using Cu(II)–based spin labels could be reproduced by molecular dynamic simulations (red and blue). Reproduced from reference with the permission of the publisher.) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 5
Fig. 5
Assessment of TF conformations in their DNA-bound state by EPR nanoscale distance measurements. a) Rotamer distributions predicted for two spin labels attached to the DNA-binding domain of MAX:MAX. The purple dots indicate the conformational freedom of the nitroxide (MTSL) labels attached to the transcription factor. b) The experimental distance distribution obtained by EPR (black) compared to the distribution computed from the crystal structure through a rotamer analysis (purple). Only the most compact state is represented by the XRD-derived structure, while a broader conformational ensemble is found in solution by EPR. c) The conformational sampling of DNA-bound MAX:MAX found in MD simulations confirmed that the DNA-binding domain opens and closes continuously around the bound DNA-ligand. This conformational tuning results in the broad experimental distance distribution shown in panel b. (adapted from reference with permission of the publisher.) (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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