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A deterministic code for transcription factor-DNA recognition through computation of binding interfaces

The recognition code between transcription factor (TF) amino acids and DNA bases remains poorly understood. Here, the determinants of TF amino acid-DNA base binding selectivity were identified through the analysis of crystals of TF-DNA complexes. Selective, high-frequency interactions were identifie...

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Autores principales: Trerotola, Marco, Antolini, Laura, Beni, Laura, Guerra, Emanuela, Spadaccini, Mariano, Verzulli, Damiano, Moschella, Antonino, Alberti, Saverio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896162/
https://www.ncbi.nlm.nih.gov/pubmed/35261972
http://dx.doi.org/10.1093/nargab/lqac008
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author Trerotola, Marco
Antolini, Laura
Beni, Laura
Guerra, Emanuela
Spadaccini, Mariano
Verzulli, Damiano
Moschella, Antonino
Alberti, Saverio
author_facet Trerotola, Marco
Antolini, Laura
Beni, Laura
Guerra, Emanuela
Spadaccini, Mariano
Verzulli, Damiano
Moschella, Antonino
Alberti, Saverio
author_sort Trerotola, Marco
collection PubMed
description The recognition code between transcription factor (TF) amino acids and DNA bases remains poorly understood. Here, the determinants of TF amino acid-DNA base binding selectivity were identified through the analysis of crystals of TF-DNA complexes. Selective, high-frequency interactions were identified for the vast majority of amino acid side chains (‘structural code’). DNA binding specificities were then independently assessed by meta-analysis of random-mutagenesis studies of Zn finger-target DNA sequences. Selective, high-frequency interactions were identified for the majority of mutagenized residues (‘mutagenesis code’). The structural code and the mutagenesis code were shown to match to a striking level of accuracy (P = 3.1 × 10(−33)), suggesting the identification of fundamental rules of TF binding to DNA bases. Additional insight was gained by showing a geometry-dictated choice among DNA-binding TF residues with overlapping specificity. These findings indicate the existence of a DNA recognition mode whereby the physical-chemical characteristics of the interacting residues play a deterministic role. The discovery of this DNA recognition code advances our knowledge on fundamental features of regulation of gene expression and is expected to pave the way for integration with higher-order complexity approaches.
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spelling pubmed-88961622022-03-07 A deterministic code for transcription factor-DNA recognition through computation of binding interfaces Trerotola, Marco Antolini, Laura Beni, Laura Guerra, Emanuela Spadaccini, Mariano Verzulli, Damiano Moschella, Antonino Alberti, Saverio NAR Genom Bioinform Standard Article The recognition code between transcription factor (TF) amino acids and DNA bases remains poorly understood. Here, the determinants of TF amino acid-DNA base binding selectivity were identified through the analysis of crystals of TF-DNA complexes. Selective, high-frequency interactions were identified for the vast majority of amino acid side chains (‘structural code’). DNA binding specificities were then independently assessed by meta-analysis of random-mutagenesis studies of Zn finger-target DNA sequences. Selective, high-frequency interactions were identified for the majority of mutagenized residues (‘mutagenesis code’). The structural code and the mutagenesis code were shown to match to a striking level of accuracy (P = 3.1 × 10(−33)), suggesting the identification of fundamental rules of TF binding to DNA bases. Additional insight was gained by showing a geometry-dictated choice among DNA-binding TF residues with overlapping specificity. These findings indicate the existence of a DNA recognition mode whereby the physical-chemical characteristics of the interacting residues play a deterministic role. The discovery of this DNA recognition code advances our knowledge on fundamental features of regulation of gene expression and is expected to pave the way for integration with higher-order complexity approaches. Oxford University Press 2022-03-04 /pmc/articles/PMC8896162/ /pubmed/35261972 http://dx.doi.org/10.1093/nargab/lqac008 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Standard Article
Trerotola, Marco
Antolini, Laura
Beni, Laura
Guerra, Emanuela
Spadaccini, Mariano
Verzulli, Damiano
Moschella, Antonino
Alberti, Saverio
A deterministic code for transcription factor-DNA recognition through computation of binding interfaces
title A deterministic code for transcription factor-DNA recognition through computation of binding interfaces
title_full A deterministic code for transcription factor-DNA recognition through computation of binding interfaces
title_fullStr A deterministic code for transcription factor-DNA recognition through computation of binding interfaces
title_full_unstemmed A deterministic code for transcription factor-DNA recognition through computation of binding interfaces
title_short A deterministic code for transcription factor-DNA recognition through computation of binding interfaces
title_sort deterministic code for transcription factor-dna recognition through computation of binding interfaces
topic Standard Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896162/
https://www.ncbi.nlm.nih.gov/pubmed/35261972
http://dx.doi.org/10.1093/nargab/lqac008
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