An assessment of three dinucleotide parameters to predict DNA curvature by quantitative comparison with experimental data.

Curved DNA fragments are often found near functionally important sites such as promoters and origins of replication, and hence sequence-dependent DNA curvature prediction is of great utility in genomics and bioinformatics. In light of this, an assessment of three different dinucleotide step parameters (based on gel retardation as well as crystal structure data) is carried out. These parameters (BMHT, LB and CS) are evaluated quantitatively for their ability to predict correctly the experimental results of a large set of nucleic acid sequences containing A-tracts as well as GC-rich motifs. This set contained around 40 synthetic as well as natural sequences whose solution properties have been well characterized experimentally. All three models could account reasonably well for curvature in the various DNA sequences. The CS model, where dinucleotide parameters are calculated from crystal structure data, consistently shows slightly better correlation with experimental data. Our simple analysis also indicates that presently available trinucleotide parameters fail to predict curvature in some of the well-characterized sequences. The study shows that the dinucleotide parameters with some further refinement can be used to predict sequence-dependent curvature correctly in genomic sequences.