Combining NMR and MS to Describe Pyrrole-2-Carbaldehydes in Wheat Bran of Radiation.

Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are indispensable analytical tools to provide chemical fingerprints in metabolomics studies. The present study evaluated radiation breeding wheat lines for chemical changes by non-targeted NMR-based metabolomics analysis of bran extracts. Multivariate analysis following spectral binning suggested pyrrole-2-carbaldehydes as chemical markers of four mutant lines with distinct NMR fingerprints in a δH range of 9.28-9.40 ppm. Further NMR and MS data analysis, along with chromatographic fractionation and synthetic preparation, aimed at structure identification of marker metabolites and identified five pyrrole-2-carbaldehydes. Quantum-mechanical driven 1H iterative full spin analysis (QM-HiFSA) on synthetic pyrrole-2-carbaldehydes provided a precise description of complex peak patterns. Biological evaluation of pyrrole-2-carbaldehydes was performed with nine synthetic products, and six compounds showed hepatoprotective effects via modulation of reactive oxygen species production. Given that three out of five identified in wheat bran of radiation were described for hepatoprotective activity, the value of radiation mutation to greatly enhance pyrrole-2-carbaldehyde production was supported.

The qNMR Summit 5.0: Proceedings and Status of qNMR Technology.

The goal of the qNMR Summit is to take stock of the status quo and the recent developments in qNMR research and applications in a timely and accurate manner. It provides a platform for both advanced and novice qNMR practitioners to receive a well-rounded update and discuss potential qNMR-related applications and collaborations. For over a decade, scientists from academia, industry, nonprofit institutions, and governmental bodies have focused on the standardization of qNMR methodology, as well as its metrological and pharmacopeial utility. This paper reviews key content of qNMR Summits 1.0 to 4.0 and puts into perspective the outcomes and available transcripts of the October 2019 Summit 5.0, with attendees from the United States, Canada, Japan, Korea, and several European countries. Summit presentations focused on qNMR methodology in the pharmaceutical industry, advanced quantitation algorithms, and promising developments.

Comprehensive strategy for proton chemical shift prediction: linear prediction with nonlinear corrections.

A fast 3D/4D structure-sensitive procedure was developed and assessed for the chemical shift prediction of protons bonded to sp3carbons, which poses the maybe greatest challenge in the NMR spectral parameter prediction. The LPNC (Linear Prediction with Nonlinear Corrections) approach combines three well-established multivariate methods viz. the principal component regression (PCR), the random forest (RF) algorithm, and the k nearest neighbors (kNN) method. The role of RF is to find nonlinear corrections for the PCR predicted shifts, while kNN is used to take full advantage of similar chemical environments. Two basic molecular models were also compared and discussed: in the MC model the descriptors are computed from an ensemble of the conformers found by conformational search based on Metropolis Monte Carlo (MMC) simulation; in the 4D model the conformational space was further expanded to the fourth dimension (time) by adding molecular dynamics to the MC conformers. An illustrative case study about the application and interpretation of the 4D prediction for a conformationally flexible structure, scopolamine, is described in detail.