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DNA mismatches reveal conformational penalties in protein–DNA recognition

Author

Listed:
  • Ariel Afek

    (Duke University School of Medicine
    Duke University School of Medicine)

  • Honglue Shi

    (Duke University)

  • Atul Rangadurai

    (Duke University School of Medicine)

  • Harshit Sahay

    (Duke University School of Medicine
    Duke University School of Medicine)

  • Alon Senitzki

    (Technion–Israel Institute of Technology)

  • Suela Xhani

    (Georgia State University)

  • Mimi Fang

    (University of Iowa
    University of Iowa)

  • Raul Salinas

    (Duke University School of Medicine)

  • Zachery Mielko

    (Duke University School of Medicine
    Duke University School of Medicine)

  • Miles A. Pufall

    (University of Iowa
    University of Iowa)

  • Gregory M. K. Poon

    (Georgia State University
    Georgia State University)

  • Tali E. Haran

    (Technion–Israel Institute of Technology)

  • Maria A. Schumacher

    (Duke University School of Medicine)

  • Hashim M. Al-Hashimi

    (Duke University
    Duke University School of Medicine)

  • Raluca Gordân

    (Duke University School of Medicine
    Duke University School of Medicine
    Duke University
    Duke University School of Medicine)

Abstract

Transcription factors recognize specific genomic sequences to regulate complex gene-expression programs. Although it is well-established that transcription factors bind to specific DNA sequences using a combination of base readout and shape recognition, some fundamental aspects of protein–DNA binding remain poorly understood1,2. Many DNA-binding proteins induce changes in the structure of the DNA outside the intrinsic B-DNA envelope. However, how the energetic cost that is associated with distorting the DNA contributes to recognition has proven difficult to study, because the distorted DNA exists in low abundance in the unbound ensemble3–9. Here we use a high-throughput assay that we term SaMBA (saturation mismatch-binding assay) to investigate the role of DNA conformational penalties in transcription factor–DNA recognition. In SaMBA, mismatched base pairs are introduced to pre-induce structural distortions in the DNA that are much larger than those induced by changes in the Watson–Crick sequence. Notably, approximately 10% of mismatches increased transcription factor binding, and for each of the 22 transcription factors that were examined, at least one mismatch was found that increased the binding affinity. Mismatches also converted non-specific sites into high-affinity sites, and high-affinity sites into ‘super sites’ that exhibit stronger affinity than any known canonical binding site. Determination of high-resolution X-ray structures, combined with nuclear magnetic resonance measurements and structural analyses, showed that many of the DNA mismatches that increase binding induce distortions that are similar to those induced by protein binding—thus prepaying some of the energetic cost incurred from deforming the DNA. Our work indicates that conformational penalties are a major determinant of protein–DNA recognition, and reveals mechanisms by which mismatches can recruit transcription factors and thus modulate replication and repair activities in the cell10,11.

Suggested Citation

  • Ariel Afek & Honglue Shi & Atul Rangadurai & Harshit Sahay & Alon Senitzki & Suela Xhani & Mimi Fang & Raul Salinas & Zachery Mielko & Miles A. Pufall & Gregory M. K. Poon & Tali E. Haran & Maria A. S, 2020. "DNA mismatches reveal conformational penalties in protein–DNA recognition," Nature, Nature, vol. 587(7833), pages 291-296, November.
  • Handle: RePEc:nat:nature:v:587:y:2020:i:7833:d:10.1038_s41586-020-2843-2
    DOI: 10.1038/s41586-020-2843-2
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    Cited by:

    1. Jinsen Li & Tsu-Pei Chiu & Remo Rohs, 2024. "Predicting DNA structure using a deep learning method," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    2. Erika Schaudy & Kathrin Hölz & Jory Lietard & Mark M. Somoza, 2022. "Simple synthesis of massively parallel RNA microarrays via enzymatic conversion from DNA microarrays," Nature Communications, Nature, vol. 13(1), pages 1-9, December.

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