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The nucleotide sequence representation of DNA can be inadequate for resolvingprotein-DNA binding sites and regulatory substrates, such as those involved ingene expression and horizontal gene transfer. Considering that sequence-likerepresentations are algorithmically very useful, here we fused over 60currently available DNA physicochemical and conformational variables intocompact structural representations that can encode single DNA binding sites towhole regulatory regions. We find that the main structural components reflectkey properties of protein-DNA interactions and can be condensed to the amountof information found in a single nucleotide position. The most accuratestructural representations compress functional DNA sequence variants by 30% to50%, as each instance encodes from tens to thousands of sequences. We show thata structural distance function discriminates among groups of DNA substratesmore accurately than nucleotide sequence-based metrics. As this opens up avariety of implementation possibilities, we develop and test a distance-basedalignment algorithm, demonstrating the potential of using the structuralrepresentations to enhance sequence-based algorithms. Due to the bias of mostcurrent bioinformatic methods to nucleotide sequence representations, it ispossible that considerable performance increases might still be achievable withsuch solutions.

Structural representations of DNA regulatory substrates can enhance sequence-based algorithms by associating functional sequence variants