DNA duplexes exist as dynamic ensembles of interconverting conformations in solution. Conventional nuclear magnetic resonance (NMR) data interpretation often simplifies this behavior by assuming one dominant structure, but multiple substates (such as different backbone conformers) can coexist. Here, we present an approach that refines the interpretation of 31P NMR data in the Dickerson-Drew DNA by integrating a nucleotide conformational classification (NtC) (Černý et al., Nucleic Acids Research 2020, 48, 6367-6381) with molecular dynamics (MD) simulations. By finely classifying backbone conformers into distinct NtC-defined states and using MD to predict their populations, we achieve a more nuanced correspondence between experimental NMR observables and DNA structure-dynamical heterogeneity. Application of this framework demonstrates a radical improvement of NMR data interpretation, thereby enhancing the reliability of deducing DNA conformational equilibria in solution.
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Fukal et al. (2025) studied this question.
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