Recognition-Enabled Automated Analyte Identification via 19F NMR

Nuclear magnetic resonance (NMR) is an indispensable tool for structural elucidation and noninvasive analysis. Automated identification of analytes with NMR is highly pursued in metabolism research and disease diagnosis; however, this process is often complicated by the signal overlap and the sample matrix. We herein report a detection scheme based on ¹⁹F NMR spectroscopy and dynamic recognition, which effectively simplifies the detection signal and mitigates the influence of the matrix on the detection. It is demonstrated that this approach can not only detect and differentiate capsaicin and dihydrocapsaicin in complex real-world samples but also quantify the ibuprofen content in sustained-release capsules. Based on the ¹⁹F signals obtained in the detection using a set of three ¹⁹F probes, automated analyte identification is achieved, effectively reducing the odds of misrecognition caused by structural similarity.

Microorganisms: the secret agents of the biosphere, and their key roles in biotechnology

Abstract We present a survey of projects that have been funded by FAPESP under the BIOTA-Microorganisms program. These projects generated a wide variety of results, including the identification of novel antibacterial-producing microorganisms, the characterization of novel microbial enzymes for industrial applications, taxonomic classification of novel microorganisms in several environments, investigation of the soil and mangrove microbial ecosystems and its influence on endangered plant species, and the sequencing of novel metagenome-assembled genomes. The results surveyed demonstrate the importance of microorganisms in environments that play important roles in human activities as well as the potential that many of these microorganisms have in contributing to biotechnological applications crucial for human survival in the 21st century.

Database Independent Automated Structure Elucidation of Organic Molecules Based on IR, 1H NMR, 13C NMR, and MS Data

Herein, we report a computational algorithm that follows a spectroscopist-driven elucidation process of the structure of an organic molecule based on IR, 1H and 13C NMR, and MS tabular data. The algorithm is independent from database searching and is based on a bottom-up approach, building the molecular structure from small structural fragments visible in spectra. It employs an analytical combinatorial approach with a graph search technique to determine the connectivity of structural fragments that is based on the analysis of the NMR spectra, to connect the identified structural fragments into a molecular structure. After the process is completed, the interface lists the compound candidates, which are visualized by the WolframAlpha computational knowledge engine within the interface. The candidates are ranked according to the predefined rules for analyzing the spectral data. The developed elucidator has a user-friendly web interface and is publicly available (http://schmarnica.si).