Deconvolution of 1D NMR spectra: A deep learning-based approach.

The analysis of nuclear magnetic resonance (NMR) spectra to detect peaks and characterize their parameters, often referred to as deconvolution, is a crucial step in the quantification, elucidation, and verification of the structure of molecular systems. However, deconvolution of 1D NMR spectra is a challenge for both experts and machines. We propose a robust, expert-level quality deep learning-based deconvolution algorithm for 1D experimental NMR spectra. The algorithm is based on a neural network trained on synthetic spectra. Our customized pre-processing and labeling of the synthetic spectra enable the estimation of critical peak parameters. Furthermore, the neural network model transfers well to the experimental spectra and demonstrates low fitting errors and sparse peak lists in challenging scenarios such as crowded, high dynamic range, shoulder peak regions as well as broad peaks. We demonstrate in challenging spectra that the proposed algorithm is superior to expert results.

Influence of pH and Mg(ii) on the catalytic core domain 5 of a bacterial group II intron.

RNA molecules fold into complex structures that allow them to perform specific functions. To compensate the relative lack of diversity of functional groups within nucleotides, metal ions work as crucial co-factors. In addition, shifted pKas are observed in RNA, enabling acid-base reactions at ambient pH. The central catalytic domain 5 (D5) hairpin of the Azotobacter vinelandii group II intron undergoes both metal ion binding and pH dependence, presumably playing an important functional role in the ribozyme's reaction. By NMR spectroscopy we have here characterized the metal ion binding sites and affinities for the hairpin's internal G-A mismatch, bulge, and pentaloop. The influence of Mg(ii) and pH on the local conformation of the catalytically crucial region is also explored by fluorescence spectroscopy.

Characterization of the full-length btuB riboswitch from Klebsiella pneumoniae.

Riboswitches are cis-regulatory RNA elements on the mRNA level that control the expression of the downstream coding region. The interaction of the riboswitch with its specific metabolite, which is related to the function of the controlled gene, induces a structural change of the RNA architecture. Consequently, gene regulation is induced by un/masking of the ribosome binding site (RBS). In the genome of Klebsiella pneumoniae a sequence was identified by bioinformatics and proposed to be a B12 riboswitch regulated by coenzyme B12. Here we study this new coenzyme B12-dependent riboswitch system by in-line probing and ITC. The riboswitch sequence includes the whole expression platform as well as RBS. In-line probing experiments were performed to investigate the structural rearrangement of this 243-nt long RNA sequence while Isothermal Titration Calorimetry (ITC) yielded the thermodynamic parameters of the interaction between the riboswitch and its metabolite. The interaction of coenzyme B12 with the butB riboswitch of K. pneumoniae is an exothermic process with a 1:1 binding stoichiometry and binding affinities of log KA=6.73±0.02 at 15°C and log KA=6.00±0.09 at 30°C.