A combination of computational and experimental approaches identifies DNA sequence constraints associated with target site binding specificity of the transcription factor CSL
Author(s) -
Rubben Torella,
Jinghua Li,
E. Kinrade,
Gustavo CerdaMoya,
Ashley N. Contreras,
Robert Foy,
Robert Stojnic,
Robert C. Glen,
Rhett A. Kovall,
Boris Adryan,
Sarah J. Bray
Publication year - 2014
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gku730
Subject(s) - biology , in silico , transcription factor , computational biology , dna , dna binding site , genetics , transcription (linguistics) , repressor , dna sequencing , hairless , dna binding domain , gene , microbiology and biotechnology , promoter , gene expression , linguistics , philosophy
Regulation of transcription is fundamental to development and physiology, and occurs through binding of transcription factors to specific DNA sequences in the genome. CSL (CBF1/Suppressor of Hairless/LAG-1), a core component of the Notch signaling pathway, is one such transcription factor that acts in concert with co-activators or co-repressors to control the activity of associated target genes. One fundamental question is how CSL can recognize and select among different DNA sequences available in vivo and whether variations between selected sequences can influence its function. We have therefore investigated CSL-DNA recognition using computational approaches to analyze the energetics of CSL bound to different DNAs and tested the in silico predictions with in vitro and in vivo assays. Our results reveal novel aspects of CSL binding that may help explain the range of binding observed in vivo. In addition, using molecular dynamics simulations, we show that domain-domain correlations within CSL differ significantly depending on the DNA sequence bound, suggesting that different DNA sequences may directly influence CSL function. Taken together, our results, based on computational chemistry approaches, provide valuable insights into transcription factor-DNA binding, in this particular case increasing our understanding of CSL-DNA interactions and how these may impact on its transcriptional control.
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