@article{168056ea3cb04fc387596b31c8692c4c,
title = "The lac repressor hinge helix in context: The effect of the DNA binding domain and symmetry",
abstract = "The Lac system of genes has been an important model system in understanding gene regulation. When the dimer lac repressor protein binds to the correct DNA sequence, the hinge region of the protein goes through a disorder to order transition. The hinge region is disordered when binding to nonoperator sequences. This region of the protein must pay a conformational entropic penalty to order when it is bound to operator DNA. Structural studies show that this region is flexible. Previous simulations showed that this region is disordered when free in solution without the DNA binding domain present. Our simulations corroborate that this region is extremely flexible in solution, but we find that the presence of the DNA binding domain proximal to the hinge helix and salt make the ordered conformation more favorable even without DNA present.",
keywords = "Disorder to order transition, Disordered proteins, LacI, MD simulations, Metadynamics, Protein, Salt stability",
author = "Danielle Seckfort and Lynch, {Gillian C.} and Pettitt, {B. Montgomery}",
note = "Funding Information: The authors thank Dr. Cheng Zhang for many helpful discussions. The Sealy Center for Structural Biology scientific computing staff is acknowledged for computational support. We gratefully acknowledge the Robert A. Welch Foundation (H-013), and the National Institutes of Health (GM-037657) for partial support of this work. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562. The authors also acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that have contributed to the research results reported within this article. URL: http://www. tacc.utexas.edu Funding Information: The authors thank Dr. Cheng Zhang for many helpful discussions. The Sealy Center for Structural Biology scientific computing staff is acknowledged for computational support. We gratefully acknowledge the Robert A. Welch Foundation ( H-013 ), and the National Institutes of Health ( GM-037657 ) for partial support of this work. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562 . The authors also acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that have contributed to the research results reported within this article. URL: http://www . tacc.utexas.edu Publisher Copyright: {\textcopyright} 2020 Elsevier B.V.",
year = "2020",
month = apr,
doi = "10.1016/j.bbagen.2020.129538",
language = "English (US)",
volume = "1864",
journal = "Biochimica et Biophysica Acta - General Subjects",
issn = "0304-4165",
publisher = "Elsevier",
number = "4",
}