Proton chemical shift prediction of A.A mismatches in B-DNA duplexes

Polymorphic potential of SRF binding site of c-Fos gene promoter: in vitro study

Recently published in vivo observations have highlighted the presence of cruciform structures within the genome, suggesting their potential significance in the rapid recognition of the target sequence for transcription factor binding. In this in vitro study, we investigate the organization and stability of the sense (coding) strand within the Serum Response Element of the c-Fos gene promoter (c-Fos SRE), specifically focusing on segments spanning 12 to 36 nucleotides, centered around the CArG-box. Through a thorough examination of UV absorption patterns with varying temperatures, we identified the emergence of a remarkably stable structure, which we conclusively characterized as a hairpin using complementary 1H NMR experiments. Our research decisively ruled out the formation of homoduplexes, as confirmed by supplementary fluorescence experiments. Utilizing molecular dynamics simulations with atomic distance constraints derived from NMR data, we explored the structural intricacies of the compact hairpin. Notably, the loop consisting of the six-membered A/T sequence demonstrated substantial stabilization through extensive stacking, non-canonical inter-base hydrogen bonding, and hydrophobic clustering of thymine methyl groups. These findings suggest the potential of the c-Fos SRE to adopt a cruciform structure (consisting of two opposing hairpins), potentially providing a topological recognition site for the SRF transcription factor under cellular conditions. Our results should inspire further biochemical and in vivo studies to explore the functional implications of these non-canonical DNA structures.

NMR chemical shift assignments of RNA oligonucleotides to expand the RNA chemical shift database

RNAs play myriad functional and regulatory roles in the cell. Despite their significance, three-dimensional structure elucidation of RNA molecules lags significantly behind that of proteins. NMR-based studies are often rate-limited by the assignment of chemical shifts. Automation of the chemical shift assignment process can greatly facilitate structural studies, however, accurate chemical shift predictions rely on a robust and complete chemical shift database for training. We searched the Biological Magnetic Resonance Data Bank (BMRB) to identify sequences that had no (or limited) chemical shift information. Here, we report the chemical shift assignments for 12 RNA hairpins designed specifically to help populate the BMRB.

Prediction of hydrogen and carbon chemical shifts from RNA using database mining and support vector regression

The Biological Magnetic Resonance Data Bank (BMRB) contains NMR chemical shift depositions for over 200 RNAs and RNA-containing complexes. We have analyzed the (1)H NMR and (13)C chemical shifts reported for non-exchangeable protons of 187 of these RNAs. Software was developed that downloads BMRB datasets and corresponding PDB structure files, and then generates residue-specific attributes based on the calculated secondary structure. Attributes represent properties present in each sequential stretch of five adjacent residues and include variables such as nucleotide type, base-pair presence and type, and tetraloop types. Attributes and (1)H and (13)C NMR chemical shifts of the central nucleotide are then used as input to train a predictive model using support vector regression. These models can then be used to predict shifts for new sequences. The new software tools, available as stand-alone scripts or integrated into the NMR visualization and analysis program NMRViewJ, should facilitate NMR assignment and/or validation of RNA (1)H and (13)C chemical shifts. In addition, our findings enabled the re-calibration a ring-current shift model using published NMR chemical shifts and high-resolution X-ray structural data as guides.

NMR proton chemical shift prediction of C·C mismatches in B-DNA

Accurate prediction of DNA chemical shifts facilitates resonance assignment and allows recognition of different conformational features. Based on the nearest neighbor model and base pair replacement approach, we have determined a set of triplet chemical shift values and correction factors for predicting the proton chemical shifts of B-DNA containing an internal C·C mismatch. Our results provide a reliable chemical shift prediction with an accuracy of 0.07 ppm for non-labile protons and 0.09 ppm for labile protons. In addition, we have also shown that the correction factors for C·C mismatches can be used interchangeably with those for T·T mismatches. As a result, we have generalized a set of correction factors for predicting the flanking residue chemical shifts of pyrimidine·pyrimidine mismatches.

NMR proton chemical shift prediction of T·T mismatches in B-DNA duplexes

A proton chemical shift prediction scheme for B-DNA duplexes containing a T·T mismatch has been established. The scheme employs a set of T·T mismatch triplet chemical shift values, 5'- and 3'-correction factors extracted from reference sequences, and also the B-DNA chemical shift values predicted by Altona et al. The prediction scheme was tested by eight B-DNA duplexes containing T·T mismatches. Based on 560 sets of predicted and experimental proton chemical shift values, the overall prediction accuracy for non-labile protons was determined to be 0.07 ppm with an excellent correlation coefficient of 0.9996. In addition, the prediction accuracy for 96 sets of labile protons was found to be 0.22 ppm with a correlation coefficient of 0.9961. The prediction scheme developed herein can facilitate resonance assignments of B-DNA duplexes containing T·T mismatches and be generalized for the chemical shift prediction of other DNA mismatches. Our chemical shift data will also be useful for establishing structure-chemical shift information in B-DNA containing mismatches.