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An algorithm for studying cooperative transitions in DNA.

H Marcaud, J Gabarro-Arpa, R Ehrlich

    Nucleic Acids Research
    |January 10, 1986
    PubMed
    Summary
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    This study presents an algorithm to predict DNA conformational changes based on nucleotide sequence. It partitions DNA into domains, enabling cooperative base pair state changes and Z-DNA binding site prediction.

    Area of Science:

    • Molecular Biology
    • Biophysics
    • Genomics

    Background:

    • Cooperative DNA transitions (e.g., B to Z, B to A, helix to coil) are sequence-dependent.
    • Free energy changes during transitions relate to sequence-specific conformational boundaries (delta G(seq) = 2RT log (sigma)).

    Purpose of the Study:

    • To develop a general algorithm for partitioning DNA sequences into domains exhibiting cooperative transitions.
    • To establish a method for predicting DNA conformational states and Z-DNA antibody binding sites.

    Main Methods:

    • Formulating a thermodynamic model for cooperative DNA transitions.
    • Developing an algorithm to partition DNA sequences based on physical parameters.
    • Utilizing a binary tree hierarchy to represent sequence partitions.

    Related Experiment Videos

  • Applying the algorithm to predict Z-DNA antibody binding sites in the phiX174 genome.

    • Main Results:

    • A general algorithm was inferred from the thermodynamic formula for DNA transitions.
    • DNA sequences can be partitioned into cooperative domains.
    • Varying physical parameters generates a hierarchy of sequence partitions.
    • Reliable prediction of Z-DNA antibody binding sites was demonstrated for the phiX174 genome.

    Conclusions:

    • The developed algorithm provides a framework for understanding and predicting cooperative DNA conformational transitions.
    • This approach facilitates the identification of specific DNA domains and their potential biological roles.
    • The method shows promise for applications in genomics, such as predicting antibody binding sites.