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The recognition of specific DNA sequences by proteins is thought to depend on two types of mechanism: one that involves the formation of hydrogen bonds with specific bases, primarily in the major groove, and one involving sequence-dependent deformations of the DNA helix. By comprehensively analysing the three-dimensional structures of protein-DNA complexes,(More)
Specific interactions between proteins and DNA are fundamental to many biological processes. In this review, we provide a revised view of protein-DNA interactions that emphasizes the importance of the three-dimensional structures of both macromolecules. We divide protein-DNA interactions into two categories: those when the protein recognizes the unique(More)
It has been known for some time that the double-helix is not a uniform structure but rather exhibits sequence-specific variations that, combined with base-specific intermolecular interactions, offer the possibility of numerous modes of protein-DNA recognition. All-atom simulations have revealed mechanistic insights into the structural and energetic basis of(More)
Proteins rely on a variety of readout mechanisms to preferentially bind specific DNA sequences. The nucleosome offers a prominent example of a shape readout mechanism where arginines insert into narrow minor groove regions that face the histone core. Here we compare DNA shape and arginine recognition of three nucleosome core particle structures, expanding(More)
DNA shape variation and the associated variation in minor groove electrostatic potential are widely exploited by proteins for DNA recognition. Here we show that the hydroxyl radical cleavage pattern is a quantitative measure of DNA backbone solvent accessibility, minor groove width, and minor groove electrostatic potential, at single nucleotide resolution.(More)
Since the explosive influx of biological data obtained from high-throughput medical instruments, the ability to leverage the currently available data to extract useful knowledge has become one of the most challenging problems in biomedical research. The analysis of such data is particularly complex not only due to its massive size but also due to its(More)
The influx of high-throughput biotechnologies has resulted in considerable amounts of available and untapped data, useful for both interpretation and extrapolation. Due to the fact that the noise to signal ratio in most biological databases are non-trivial, single source analysis techniques may suffer from relatively high false-positive and false-negative(More)
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